Topic Highlight Open Access
Copyright ©2012 Baishideng Publishing Group Co., Limited. All rights reserved.
World J Biol Chem. Apr 26, 2012; 3(4): 73-92
Published online Apr 26, 2012. doi: 10.4331/wjbc.v3.i4.73
Pharmacokinetics and toxicology of therapeutic proteins: Advances and challenges
Yulia Vugmeyster, Department of Pharmacokinetics, Dynamics, and Metabolism, Pfizer Inc., Andover, MA 01810, United States
Xin Xu, Center for Translational Therapeutics, National Institutes of Health, Rockville, MD 20850, United States
Frank-Peter Theil, UCB Pharma, Braine l’Aleud, B-1420 Brussels, Belgium
Leslie A Khawli, Pharmacokinetic and Pharmacodynamic Sciences, Genentech Inc., South San Francisco, CA 94080, United States
Michael W Leach, Drug Safety Research and Development, Pfizer Inc., Andover, MA 01810, United States
Author contributions: Vugmeyster Y, Leach MW, and Xu X conceived and wrote this review; Theil FP and Khawli LA contributed to the conception of this review and critically reviewed the manuscript.
Correspondence to: Yulia Vugmeyster, PhD, Senior Principal Scientist, Department of Pharmacokinetics, Dynamics, and Metabolism, Pfizer Inc., Andover, MA 01810, United States.
Telephone: +1-978-2471404 Fax: +1-978-2472842
Received: November 10, 2011
Revised: January 18, 2012
Accepted: January 25, 2012
Published online: April 26, 2012


Significant progress has been made in understanding pharmacokinetics (PK), pharmacodynamics (PD), as well as toxicity profiles of therapeutic proteins in animals and humans, which have been in commercial development for more than three decades. However, in the PK arena, many fundamental questions remain to be resolved. Investigative and bioanalytical tools need to be established to improve the translation of PK data from animals to humans, and from in vitro assays to in vivo readouts, which would ultimately lead to a higher success rate in drug development. In toxicology, it is known, in general, what studies are needed to safely develop therapeutic proteins, and what studies do not provide relevant information. One of the major complicating factors in nonclinical and clinical programs for therapeutic proteins is the impact of immunogenicity. In this review, we will highlight the emerging science and technology, as well as the challenges around the pharmacokinetic- and safety-related issues in drug development of mAbs and other therapeutic proteins.

Key Words: Pharmacokinetics, Toxicology, Therapeutic proteins, Biotherapeutics, Monoclonal antibodies


Biotherapeutics are therapeutic agents that are produced from living organisms or their products (including recombinant DNA technology, biotechnological manufacturing, and chemical synthesis using nucleotides or amino acids) and include monoclonal antibodies (mAbs), antibody fragments, peptides, replacement factors, fusion proteins, oligonucleotides and DNA preparations for gene therapy, as well as vaccines. This is a rapidly growing class of therapeutics for a broad spectrum of indications, ranging from oncology and autoimmunity to orphan and genetic diseases.

Pharmacokinetics (PK) refers to the biological processes determining absorption, distribution, metabolism and excretion (ADME) of a drug in an organism. Pharmacodynamics (PD) refers to drug action on a living organism, including the pharmacologic response and the duration and magnitude of response observed relative to the concentration of the drug at an active site in an organism. Significant progress has been made in understanding PK, PD, as well as toxicity profiles of biotherapeutics in animals and humans, especially for proteins and mAbs, which have been in commercial development for more than three decades.

However, many fundamental ADME questions remain to be resolved. Investigative tools need to be established to improve the translation of PK data from animals to humans and from in vitro assays to in vivo readouts, which would ultimately lead to a higher success rate in drug development and provide safer and more effective drugs. In addition, commercial considerations, such as cost of goods and convenience (including less frequent dosing and self-administration), drive the need for a continuous advancement of mechanistic ADME evaluations and structure activity relations (SAR) for protein therapeutics in order to enable rational protein engineering of desired ADME profiles.

The goal of this review is to highlight emerging science and technology, as well as challenges around the pharmacokinetic- and safety-related issues in drug development of mAbs and other therapeutic proteins.

Absorption, distribution, metabolism, and excretion

Absorption: Unlike small molecules, which are frequently delivered via oral administration, therapeutic proteins are almost exclusively administered by parenteral routes, such as intravenous (IV), subcutaneous (SC) or intramuscular (IM) injection. Molecular size, hydrophilicity, and gastric degradation are the main factors that preclude gastrointestinal (GI) absorption of therapeutic proteins[1]. Pulmonary delivery with aerosol formulations or dry powder inhalers has been used for selected proteins, e.g., exubera (TM)[2,3]. Intravitreal injections have been used for peptides and proteins that require only local activity[4], as well as for antisense oligonucleotides[5].

From the convenience standpoint, SC administration of therapeutic proteins is often a preferred route. In particular, the suitability of SC dosing for self-administration translates into significantly reduced treatment costs. Absorption of therapeutic proteins from the SC injection site tends to be slow compared to small molecules, and the absorption rates depend on the size of the molecule. For example, following SC administration, the time to reach the maximum systemic concentration (Tmax) in humans for peptides is in the range of hours, while the Tmax for mAbs is generally several days[6-8]. For mAbs, SC bioavailability for currently marketed products is in the range of 24% to 95% in humans[1,9,10] (Table 1).

Table 1 Examples of proteins and peptides administered subcutaneously[10].
INN/BAN (description)Trade nameMW (kDa)Absolute bioavailability1SC animal models used in drug development
Buserelin acetate (LH-releasing hormone analog)Suprefact1.30Human: 70%Pharm: rat, hamster, guinea pig, rabbit, dog and monkey Tox: mouse, rat, rabbit and dog
Pramlintide acetate (amylin analog)Symlin3.95Human: 30 to 40%Pharm: rat and dog PK: mouse, rat, rabbit and dog Tox: mouse, rat, rabbit and dog
Insulin lispro (insulin analog)Humalog5.81Human: 55 to 77%Pharm: rat, rabbit, dog and pig PK: rat and dog Tox: rat, rabbit and dog
Insulin glulisine (insulin analog)Apidra5.82Human: about 70% Dog: 42% Rat: 96%2Pharm: rat and dog PK: rat and dog Tox: mouse, rat, rabbit and dog
Insulin glargine (insulin analog)Lantus6.06Precipitates in skin-slow uptake in human, dog and ratPharm: mouse, rat, guinea pig, rabbit and dog PK: rat and dog Tox: mouse, rat, guinea pig, rabbit and dog
Mecasermin (IGF-1)Increlex7.65Human: about 100% Rabbit: 47% Rat: 38 to 57%Pharm: mouse, rat, rabbit and monkey PK: rat, rabbit, dog and monkey Tox: rat, dog, rabbit and monkey
IFNβ-1b (cytokine)Betaseron18.5Human: 50% Monkey: 31 to 44%Pharm: monkey PK: monkey Tox: rabbit and monkey
Somatropin (GH)Nutropin22Human: 81%Pharm: rat PK: rat and monkey Tox: mouse, rat, dog and monkey
IFNβ-1a (cytokine)Rebif22.5Human: 6 to 62% Monkey: 12 to 38% Rat: 16%Pharm: mouse and monkey PK: rat and monkey Tox: monkey
PEG-IFNα-2b (cytokine variant)PEG-Intron31Monkey: 57 to 89% Rat: 43 to 51%Pharm: rat and monkey PK: rat and monkey Tox: mouse, rat, rabbit and monkey
Pegfilgrastim (PEG-G-CSF)Neulasta39Monkey: 49 to 68% Rat: < 10% to 30%Pharm: mouse, rat and dog PK: mouse, rat and monkey Tox: rat and monkey
Pegvisomant (PEG-GH)Somavert42, 47 and 523Human: 49 to 65% Monkey: 70 to 81% Mouse: 45 to 73%Pharm: mouse and monkey PK: mouse, rat, rabbit and monkey Tox: mouse, rat, rabbit and monkey
PEG-IFNα-2a (cytokine variant)Pegasys60Human: 61 to 80%Pharm: mouse PK: rat and monkey Tox: mouse, rat and monkey
Certolizumab pegol (PEG-anti-TNFα Fab' fragment)Cimzia91Human: 76 to 88% Rat: 24 to 34%PK: rat and monkey Tox: monkey
Canakinumab (anti-IL-1β mAb)Ilaris145Human: 63 to 67% Monkey: 60%Pharm: mouse, rat and monkey (marmoset) PK: mouse and monkey Tox: mouse and monkey
Adalimumab (anti-TNF mAb)Humira148Human: 64% Monkey: 96%PK: monkey Tox: rabbit and monkey
Omalizumab (anti-IgE mAb)Xolair149Human: 53 to 71% Monkey: 64 to 104% Mouse: 90%Pharm: monkey PK: mouse and monkey Tox: monkey
Golimumab (anti-TNF mAb)Simponi150Human: 53% Monkey: 77%PK: monkey Tox: mouse and monkey
Ustekinumab (anti-p40 mAb)Stelara150Human: 24 to 95% Monkey: 97%Pharm: monkey PK: monkey Tox: monkey
Etanercept (TNF receptor-Fc-IgG1 fusion protein)Enbrel150Human: 76% Monkey: 73% Mouse: 58%Pharm: mouse PK: mouse, rat and monkey Tox: mouse, rat, rabbit and monkey
Rilonacept (IL-1 inhibitor, fusion protein)Arcalyst251Human: 43% Monkey: 70% Rat: 60% Mouse: 78%Pharm: mouse and monkey PK: mouse, rat and monkey Tox: monkey

In general, factors influencing SC absorption parameters are believed to include intrinsic subject characteristics for a given species (such as body weight, sex, age, activity level); species characteristics with regard to skin morphology and physiology (such as the presence or absence of the panniculus carnosus muscle in the skin, maximum SC injection volume which varies by species, catabolic capacity at injection site and/or in the lymphatic system, SC blood flow); drug substance and product characteristics [presence of an Fc (see below), target interactions, charge, formulation, dose concentration, total dose]; and mode of administration (injection site, injection time, depth of injection, anesthesia status), as discussed in references[1,9-14]. However, surprisingly little is known about the mechanisms and pathways of SC absorption and which pathways are affected by a particular factor described above. The emerging science and issues around the mechanisms and factors involved in SC absorption that are not known are further discussed in the “WHAT IS NOT KNOWN” section.

Distribution: Tissue distribution of therapeutic proteins usually is limited because of the size of the molecules, which is in contrast to small molecule drugs that tend to have higher tissue penetration. In addition to size, other factors that influence the tissue distribution of a therapeutic protein include the physical and chemical properties (e.g., shape and charge), binding properties (e.g., receptor-mediated uptake), the route of administration (e.g., IV vs SC, formulation), and the production process (which may affect post-translational modifications, such as glycosylation). These factors can be modulated via rational design to modulate tissue penetration properties of a biotherapeutic molecule. For example, a modeling analysis of the effects of molecular size and binding affinity on tumor targeting was conducted to guide the design of new therapeutic protein drugs[15,16]. A similar approach was used to engineer a novel human IL-2 analog that antagonizes the IL-2 receptor[17]. Tissue- or target-specific delivery of therapeutic biologics is a challenging, yet a very attractive area for pharmaceutical research.

For mAbs and other large therapeutic proteins, the reported volume of distribution after IV administration is close to the plasma volume, suggesting limited distribution into tissues[18]. However, tissue distribution studies with radiolabeled mAbs indicate that many tissues are exposed to mAbs, but at lower concentrations than usually seen in systemic circulation[19]. Despite the limited tissue penetration, large biotherapeutics, such as mAbs, often do have efficacy even in cases when the site of action is believed to be the tissue, indicating that it is possible to design a therapeutic regimen such that the tissue exposure is adequate to modulate the target at the site of action. The therapeutic areas for tissue-acting biotherapeutics are diverse and examples for autoimmunity and oncology are presented in recent reviews[20,21].

Once in the tissue vasculature, the common transport mechanisms for proteins from systemic circulation across capillary endothelial cells and into tissues are listed in Table 2[22]. The uptake of therapeutic proteins into cells may be carried out via receptor-mediated transporters (e.g., Fc receptors, often leading to recycling of the molecule) or other internalization processes, such as endocytosis or pinocytosis (often leading to degradation of the molecule). Target-mediated tissue distribution has also been reported for some mAbs[23,24]. High drug concentrations in kidney and liver have been reported for peptides, low molecular proteins, and oligonucleotides[25,26]. Upon tissue uptake, metabolism/catabolism of protein drugs will occur in tissues before the remnants of the molecules are excreted from the body as smaller peptides and amino acid degradants, or they are recycled for synthesis into other proteins in the body.

Table 2 Transport mechanisms for proteins from systemic circulation across capillary endothelia[22].
Type of capillary endotheliumBarrier/transport mechanismParticle size subject to passageTypical tissues
Continuous (non-fenestrated)Basal lamina membrane supported by collagen50-110 nmMuscle, central nervous system, bone, skin, cardiac muscle
FenestratedLarge pores, open fenestrae, intracellular junctions, basal lamina50-800 nmRenal glomeruli, intestinal villi, synovial tissue, endocrine glands, choroid plexus (brain)
Discontinuous (sinusoidal)Large pores (fenestrae), pinocytotic vesicles1000-10  000 nmLiver, spleen, bone marrow, postcapillary venules of lymph nodes

The high vascular concentrations of the test article provide a potential source for interference of tissue drug concentrations, and should be considered when interpreting biodistribution data for therapeutic proteins. To minimize vascular interference, whole body perfusion is often performed before tissue analysis in biodistribution studies of therapeutic proteins, especially for rodents[19]. Other methods to correct for the contribution of residual drug in tissue blood vessels, such as the use of radiolabeled erythrocytes or the use of dual isotopes of 125I- and/or 131I-labeled proteins, have also been applied[27,28].

Metabolism/Catabolism: Therapeutic proteins are removed from circulation or interstitial fluid via several pathways: degradation by proteolysis, Fcγ receptor-mediated clearance, target-mediated clearance, nonspecific endocytosis, and formation of immune-complexes (ICs) followed by complement- or Fc receptor-mediated clearance mechanisms. While proteolysis occurs widely in the body, its kinetics and mechanistic details are poorly understood, especially for large therapeutic proteins such as mAbs. In vitro incubations with plasma, liver and kidney homogenates have been used for peptides to facilitate the selection of leads in discovery research; however the in vitro in vivo correlations for such an approach remain to be established (see additional discussions in the “WHAT IS NOT KNOWN” section). Once taken up into cells, a biotherapeutic may be metabolized to peptides or amino acids. This may occur in circulation by circulating phagocytic cells or by their target antigen-containing cells, or may occur in tissues by various cells. For molecules with an Fc (including therapeutic mAbs, endogenous Abs, and fusion proteins), binding of the Fc domain to Fc gamma-receptors may result into the internalization and subsequent degradation by lysosomes in the reticuloendothelial system (e.g., macrophages and monocytes)[1,29,30].

Alternatively, molecules with an Fc may be protected from degradation by binding to protective receptors [i.e., the neonatal Fc-receptor (FcRn)] in endothelial cells, explaining the long half-lives (up to 4 wk) of these proteins. The following references provide excellent reviews on the scholarship in this field[1,31-33]. The FcRn receptor is a 52-kDa membrane-bound heterodimeric glycoprotein comprising a heavy chain and a light chain (beta2-microglobulin). Structurally, the FcRn receptor varies only subtly from conventional major histocompatibility complex (MHC) class I proteins protein. Its physiological function and expression in different tissues have been described[1,31-33]. In particular, the FcRn receptor, located in endosomes of endothelial cells, is known to bind to the Fc domain of IgG at pH 6.0-6.5, but only weakly or not at all at pH 7.0-7.5. This unique property allows FcRn to protect Fc-containing molecules from degradation by binding to them in acidic endosomes after uptake into endothelial cells via nonspecific endocytosis or fluid-phase pinocytosis. The IgG-FcRn complex is then transported back to the cell surface and disassociated at physiological pH, releasing the intact Fc-containing molecule back to the circulation. In contrast, Fc-containing molecules that are not bound to FcRn are degraded to amino acids by lysosomes in the cells. The correlation between FcRn binding affinity and systemic half-live has been investigated for a number of mAbs[33-43]. While the contribution of FcRn in prolonging half-lives of Fc-containing proteins is well recognized, other factors may also play a role in determining the elimination rate of these proteins, because the binding affinity to FcRn alone could not explain the variation of half-lives observed for all approved Fc-containing therapeutic proteins (see additional discussions in the “WHAT IS NOT KNOWN” section).

Target-mediated clearance is one of main causes of non-linear elimination kinetics. Upon binding to target on cells, the therapeutic proteins are internalized into the cells and subjected to degradation in lysosomes. For targets such as the endothelial growth factor receptor (EGFR), target-mediated clearance is the predominant clearance pathway at clinical doses, as illustrated by the nonlinear kinetic characteristics of cetuximab[44]. Target-mediated clearance could be demonstrated by comparing the disposition kinetics between normal healthy animals vs animals over expressing the target[23,45]. PK/PD models are usually established to describe saturable kinetic profiles that are associated with the target-mediated clearance in humans[46-50]. Formation of anti-drug antibodies (ADA) followed by formation of biotherapeutic/ADA ICs, is another main cause for the non-linear elimination kinetics, including time-dependent clearance, which is often evidenced by a rapid concentration drop in the PK profiles (discussed below).

It should also be noted that many general factors that contribute to inter-subject variability in PK profiles for small molecule compounds may also apply to therapeutic proteins. These factors can be categorized into intrinsic factors (such as age, sex, body weight, activity level, renal and hepatic impairment) and to extrinsic factors (e.g., concomitant drugs, diet) and there are several examples in the literature describe the role of some of these factors for mAbs[51,52].

Excretion: Renal excretion is thought to play an important role in the elimination of protein degradation products and low molecular weight (MW) biologics (MW < 30 kDa). The process of renal filtration, transport, and metabolism of low-MW proteins has been well discussed in literature[26]. Proteins are hindered at the glomerular filter in proportion to their molecular size, structure, and net charge. However, the mechanisms of reabsorption of peptides and proteins in the kidney need further investigation.

When radiolabeled mAbs or Fc fusion proteins were used in animal disposition studies, a majority of the radioactive dose was recovered in the urine[19]. The sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analysis and trichloroacetic acid (TCA) soluble counts indicated that the radioactive materials in urine were associated with low molecular fragments, suggesting that the excretion of intact parent drug was negligible. Biliary excretion of therapeutic proteins, such as insulin and epidermal growth factor has been reported[53]. It appeared that proteins were subjected to degradation in the liver, and the degradants were subsequently excreted into bile[54].

It has also been reported that plasma protein binding plays an important role in the tissue distribution of several new modalities of biologic therapeutics (e.g., oligomers), resulting in altered excretion profiles. Modification of the lipophilicity of the backbone for oligomers has been used to prolong the in vivo half-life by increasing plasma protein binding in order to reduce the renal excretion[5].

Anti-drug antibodies

Immunogenicity, specifically formation of ADAs, is one of the major complicating issues in nonclinical and clinical programs for therapeutic proteins. There are many factors that contribute to the ability of a therapeutic protein to elicit ADA production[55]. Intrinsic factors affecting immunogenicity are protein sequence (including similarity to endogenous proteins and the presence of T and B cell epitopes), post-translational modification (glycosylation, oxidation), and tertiary structure (including aggregation propensity). Extrinsic factors include the route, dose, and type of formulation (that may affect aggregation), production process (that may affect both aggregation and post-translational modifications), impurities, subject characteristic (disease population, inflammation status, concomitant medications), as well as drug pharmacology (specifically related to immunosuppression). All of the above factors are thought to contribute to variability in ADA responses observed across the biologic modalities, species, and subjects.

ADA may affect both the PK and PD profiles of therapeutic proteins by introducing additional (IC-dependent) clearance and distribution pathways and by modulating biological activity, including neutralization of the test article. In the case of replacement proteins, the ADA can result in neutralization of the endogenous protein as well, as has been described with erythropoietin[56,57] and factor VIII[58] replacement factors.

When a drug/ADA immune complex is formed, the clearance of a therapeutic protein within the IC may be much faster compared to unbound drug, explaining a rapid concentration drop in PK profiles. It is believed that the clearance of IgG-containing ICs (which would include a drug bound to ADA) occurs primarily in the liver[59-63]. This can be facilitated by red blood cells, which can bind ICs in the circulation (via the complement receptor 1) and deliver them to the tissue macrophages of the mononuclear phagocyte system (such as Kupffer cells) in the liver[60]. Because the extent and rate of IC formation varies among human subjects, the IC-related clearance could be considered as a major contributor to the inter-subject variability in clinical and nonclinical PK profiles for therapeutic proteins.

Under some circumstances, ICs (including ADA-bound therapeutic proteins) might not be transported to the liver and cleared properly[59]. Factors that could influence this phenomenon include the IC characteristics (such as nature and quantity of the antigen and the antibody response, including antibody isotype and antigen/antibody stoichiometry) and the state of the systems involved in IC clearance and transport (for example expression of complement components, complement receptors, liver phagocytic system, red blood cells). In these cases, the deposition of circulating complement-fixing IC in various organs (such as the kidney) is observed, with important consequences for safety assessments of biotherapeutics. The impact of ADA on toxicology and PK-PD of therapeutic proteins is further discussed below in the “WHAT IS NOT KNOWN” section.


Glycosylation, most frequently at asparagine residues (“N-linked”) and at serine or threonine residues (“O-linked”), is the most common, complex, and heterogeneic post-translational modification that occurs on endogenous and therapeutic proteins. Recent reviews by Sola et al[64] and

Li et al[65] summarize the current knowledge in this field. The inter- and intra-product heterogeneity in glycosylation profile can arise from the variability in glycan type and structure (including degree of branching), the site of attachment, and the degree of occupancy and can, in part, be controlled by the production system and conditions (such cell-type, cell culture media, and purification process). The glycosylation of proteins is important from the ADME and efficacy standpoint, because improperly glycosylated proteins, whether endogenous or exogenously produced biotherapeutics, may be rapidly cleared from the circulation by specific receptor-based mechanisms, such as high mannose receptor or asialoglycoprotein receptor, and because glycosylation may directly affect biological activity of a biotherapeutic. For many approved protein drugs, clinical efficacy depends on proper glycosylation[64,65]. The ongoing research in the field is discussed below in the “WHAT IS NOT KNOWN” section.


In the past three decades of the development of biotherapeutics, the toxicity of the molecules and the methods and studies by which to measure such toxicity have been refined. In some cases (for example, for mAbs and fusion proteins that block cytokine pathways), no effects may be seen. When effects are seen in toxicity studies with biotherapeutics, in almost all cases the findings have been linked to target-mediated effects. In some cases these target-mediated effects may be undesirable, and are considered to be a result of exaggerated pharmacology. In this regard, they may not be considered to represent primary toxicity.

There are many examples of on-target pharmacologic effects that can be undesirable. For example, a variety of tumor necrosis factor-α (TNF) inhibitors are used to treat inflammatory and autoimmune diseases, including rheumatoid arthritis, psoriasis, inflammatory bowel disease, and multiple sclerosis. B cell depletion therapies are used for the treatment of B cell tumors, and for inflammatory and autoimmune diseases. These therapies have proven to provide life-altering benefits to many patients. However, infections related to immunosuppression, which can be considered exaggerated pharmacology, have occurred in a small number of patients[66-70], although not all studies have demonstrated such a risk relative to treatment with nonbiologic regimens[71]. When they occur, these infections may be associated with latent viral or bacterial infections that recrudesce following the immunosuppression, or infections by organisms that are normally not pathogens in humans, and include Mycobactrium tuberculosis, atypical mycobacterial infections, hepatitis B, and John Cunningham virus [JCV, which causes progressive multifocal leucoencephalopathy (PML)]. It should be noted that because patients often receive multiple immunosuppressive therapies as well as have various diseases, identifying clear casual associations between infections and specific biologics can be challenging[67].

Another example of exaggerated pharmacology comes from the erythropoiesis stimulating agents such as erythropoietins[72]. At higher doses, such as those used in toxicity studies, the animals develop polycythemia, chronic blood hyperviscosity, vascular stasis, thromboses, increased peripheral resistance and hypertension, which can be fatal. Similar adverse effects have been suspected in athletes who are seeking supraphysiological hematocrits[73]. However, in an anemic person or animal, the increased red cell mass can be beneficial. The concept that one scientist’s pharmacology is another scientist’s toxicity is indeed well represented in the field of biotherapeutics. That said, very recently there has been some concern raised regarding off-target effects with biotherapeutics, and this is currently a topic of discussion within the biopharmaceutical industry (a recent case study is reported by Everds et al at the Toxicologic Pathology Annual Symposium, 2011; Abstract 04).

Species selection

Regulations require the use of one rodent and one non-rodent animal species in general toxicity studies to assess the toxicity of biotherapeutics, as long as the species are relevant[74,75]. The selection of species for most biotherapeutics should primarily be based by the presence of pharmacological activity. The specificity and biological activity of the biotherapeutic is typically first evaluated in vitro. This can be done using binding assays and cell-based assays. Ideally the biotherapeutic will be specific and bind only to the intended target. However, from a practical standpoint, only a limited number of targets can be evaluated, and there is always a chance for unintended binding to untested targets to occur. The in vitro activity of the biotherapeutic on the human target should be compared with the activity in commonly used toxicity species. Ideally, the activity in the animal species is similar to that observed in humans. If so, it suggests these species may be relevant for toxicity studies. However, in many cases the activity in animals is lower, and sometimes absent, especially in rodents. When pharmacologic activity is not present in a species, they should generally not be used for toxicity studies (although they may still have value for PK studies). Whenever possible, the presence of partial or full in vitro activity should be followed up with in vivo studies, as the activity in vitro is not always predictive of the in vivo activity. For example, a cell line from a mouse might show only 50% pharmacologic activity in vitro compared with a human cell line. However, the activity in vivo might be greater in the animal (and more similar to humans) if only partial binding or signaling is necessary for a full PD effect. When the biological activity in animals is less than humans, it can sometimes be possible to dose higher and/or more frequently to produce a greater level of activity in the toxicity species, presumably more similar to what would happen in humans. It should be noted that there is no defined rule stating what level of activity compared with humans is needed to suggest inclusion or exclusion of a given species for in vivo toxicity testing, but hopefully full pharmacologic activity can be achieved in at least one toxicity species (see “WHAT IS NOT KNOWN” section).

In most cases, toxicologists prefer to use only certain species for toxicity testing. This is based on having many decades of experience with these species, and having a good understanding of the background findings and diseases that can occur. Specifically, the preferred species for general toxicity testing include the mouse, rat, dog, and cynomolgus monkey (the rhesus monkey is also sometimes used). In the case of small molecules, the rat and dog are most frequently used, unless data exists suggesting alternative species should be used (which might occur in case of species differences in drug metabolism resulting in unique and/or major metabolites). In contrast to the small molecule situation, in many cases the biotherapeutic under development is pharmacologically active only in primates, and thus the large animal species used for general toxicity testing is the cynomolgus monkey. In some cases, the molecule also has activity in mice and/or rats. When this occurs, general toxicity testing should also be conducted in the rodent[74,75]. Unlike the situation with small molecules, metabolites are not a factor in species selection for biotherapeutics.

The need to frequently use the cynomolgus monkey as a primary species for general toxicity testing has highlighted some of the issues with using monkeys in toxicity studies. They are genetically heterogeneous, there are frequently background findings that can mimic test article-related effects, they are expensive and require extensive housing care, their use should be minimized from an animal use perspective, and only small numbers can be used. Nevertheless, there is a good track record in developing biotherapeutics for human use without development of toxicity in humans. In most cases, when effects are seen in humans, they have been related to exaggerated pharmacology, which was considered a possible effect based on known or expected in vitro pharmacology, even if not observed in vivo in animals.

If there is no activity in any commonly used toxicology species, then it may be necessary to consider other species, such as the common marmoset. In addition, the use of surrogate molecules or transgenic animals expressing the human target can be considered; however, this greatly adds to the complexity of the development programs, and may be a reason to look for other candidate molecules (see “WHAT IS NOT KNOWN” section).

Tissue cross-reactivity studies

For biotherapeutics containing a complementarity-determining region (CDR), a tissue cross-reactivity (TCR) study is recommended[76]. This assay involves an immunohistochemical staining of a broad range of tissues from humans primarily to identify off-target binding, and secondarily to identify previously unknown sites of target expression. If human staining is observed, then similar tissues should be stained in the species planned for toxicity testing. In most cases, the TCR studies in at least one of the species planned for in vivo toxicity studies shows a similar pattern of binding. In the unusual cases where no animal staining is observed in human tissues that had staining, other species may need to be considered for the toxicity studies to ensure assessment of the potentially cross-reactive epitope. This topic has recently been reviewed[76].

Cytokine release assays

The implementation of cytokine release assays into nonclinical drug development strategies was driven to a great extent by the unfortunate clinical trial with TGN1412, which resulted in cytokine release in human volunteers and significant morbidity[77-80]. Much effort was put into determining why the nonclinical development studies did not alert the scientists to the cytokine release that occurred in humans. At the present time, in vitro cytokine assays have been developed that are believed to be able to detect biotherapeutics that may result in cytokine release. In addition, methods of determining safe starting doses in humans have been implemented across the world. In particular, one approach often used is termed the MABEL approach, which involves determining the Minimal Anticipated Biological Effect Level, and then applying a safety factor to determine the appropriate starting dose[77,81,82]. In addition, it is recommended that dosing in first in human trials be staggered, so that if adverse effects do occur shortly after dosing, only a few subjects would be impacted.

Studies that are not necessary

In the early days of biotherapeutics development, the testing paradigm for development typically followed a small molecule approach. In this regard, genetic toxicity testing was often done. It is now recognized that biotherapeutics alone do not cause direct genetic damage that results in tumor formation, and such testing is not necessary; regulatory guidances specifically state this[74,75]. However, there are occasions where genetic toxicity may be necessary if the biotherapeutic is linked to molecules for which there is a genetic toxicity risk. Examples of this include antibody drug conjugates, where the antibody is attached to a toxin via a linker. In this case, both the linker and/or the toxin may be genotoxic, and genetic toxicity testing may be necessary. Many of the other assays often conducted for small molecules, such as in vitro toxicity evaluations and the human ether-a-go-go related gene (hERG) assays are typically not conducted with biotherapeutics.

Nonclinical development strategies

A detailed description of possible development strategies for all type of biotherapeutics is beyond the scope of this article. However, some general concepts are applicable to most classes. Once the pharmacologically-relevant species have been identified for the toxicity studies, non-GLP (i.e., not required to follow the good laboratory practice guidelines) exploratory toxicity (dose range finding) studies are typically conducted. These usually use a limited number of animals and usually range from single-dose to two-week studies; the study design should be based on the overall program needs and known pharmacology. In some cases, toxicity evaluations can be conducted in conjunction with efficacy studies, which can provide important information earlier in the program at reduced cost and using fewer animals. It is important, however, that such combination efficacy/toxicity studies do not unduly jeopardize the potential for collecting critical data. For example, if the entire liver needed to be collected for an efficacy evaluation, then it would not be possible to collect it for histopathologic evaluation. In other cases, especially for monkey studies and in cases where little toxicity is expected, assessments can be included in association with non-terminal single-dose PK studies (for example, clinical observations, clinical pathology assessments), minimizing animal use. If pharmacologically relevant, both a small animal (typically mouse or rat) and a large animal (typically cynomolgus monkey) are evaluated in these early studies. Information from the exploratory studies is used to guide the study design for the first-in-human (FIH)-enabling GLP toxicity studies. These are usually also conducted in a rodent and non-rodent species, if pharmacologically relevant. These studies are usually followed by longer-term studies if they are needed.

The current regulatory guidelines suggest chronic toxicity evaluations only need to be in one relevant species[75]. This can mean only the mouse or rat, if this species is relevant, i.e., the monkey is not necessarily the default species that must be used. Some companies have also used the rabbit as the single species for chronic studies.

Safety pharmacology studies are usually included in the GLP toxicity studies if the only relevant species is the monkey, and usually include central nervous system (CNS), cardiovascular (CV), and respiratory evaluations at a minimum. However, some companies conduct separate studies, especially if there is cause for concern. If the biotherapeutic is active in rodents, these species can be used for safety pharmacology studies.

Reproductive toxicity evaluations for biotherapeutics have evolved significantly over the past decade. If the molecule is active in rodents, then fertility, embryo-fetal development, and peri/postnatal evaluations can be conducted in rodents, if such studies are necessary[75]. It is also important to note that the rabbit needs to be considered as a potential species for use in embryo-fetal development studies[75]. The consideration of the rabbit requires conducting appropriate in vitro and/or in vivo studies to determine whether the rabbit is a pharmacologically-relevant species. These assays should be done early enough in the development program to ensure the data are available for making appropriate species selection decisions, and for conducting the necessary studies in time to support the clinical program. In some cases, full reproductive toxicity evaluations are not necessary, such as oncology indications, where only developmental toxicity in one species may be necessary[83], or in cases where the indication does not warrant reproductive toxicity evaluations.

If the biotherapeutic is only active in primates, then a relatively new study design is recommended for most indications that require a complete reproductive toxicity evaluation. The design is termed an enhanced pre/postnatal development (ePPND) study, and involves dosing from early gestation (gestation day 20) to the end of gestation, or into the beginning of the post partum period[75,84]. Fertility assessments can be challenging in monkeys. It is generally recommended that at least one longer-term (i.e., > 3 mo) toxicity study be conducted in mature monkeys, if warranted for the indication, to help assess reproductive effects[75]. This paradigm has put increased pressure on the need for mature monkeys, which are more expensive and require increased animal handling capabilities of the larger animals. In addition, the pretest screening to assist in determination of sexual maturity adds time, and must be considered when planning studies.

Absorption, distribution, metabolism, and excretion

Despite the rapid increase in knowledge of mechanisms involved in protein disposition, many fundamental issues in pharmacokinetics and ADME properties of therapeutic proteins remain to be elucidated. Below we highlight some of the major knowledge and technology gaps, as well as emerging science in ADME investigation of protein therapeutics from the standpoint of commercial development.

Impact of bioanalytical assay on PK characterization: Developing a validated bioanalytical assay is critical in determining the PK of therapeutic proteins. At the present time, the majority of bioanalytical methods for determination of drug concentrations, as well as for the determination of ADA, are ligand binding-based assays. Understanding the assay format is important in PK characterization to accurately describe the in vivo disposition of a protein molecule, especially when linking the PK data with the PD outcomes[85,86].

The commonly used and emerging bioanalytical approaches for quantification of therapeutic proteins in circulation and tissues are summarized in Table 3. There are currently technical limitations associated with measuring tissue drug concentrations for proteins: in general, the currently available technologies for quantification of tissue concentrations of biotherapeutics in support of ADME studies are relatively labor intensive, of low throughput, and often of low sensitivity (Table 3). For therapeutic proteins with a site of action in tissues, accurate quantifications of drug tissue concentrations are needed to establish the PK/PD correlation and guide design of clinically efficacious dose regimens. Different approaches are often pursued to determine tissue drug concentrations on a case-by-case basis. The advantages and disadvantages of using radiolabeled proteins in tissue distribution studies have been discussed[19]. Noninvasive imaging with radiolabeled or fluorescently-labeled proteins and peptides is a fast growing research field and this diagnostic and/or bioanalytical technology has been widely used in different therapeutic areas[87]. For example, Palframan et al[88] examined uptake of several commercially available TNF inhibitors in mouse model of arthritis using a non-invasive biofluorescence imaging method.

Table 3 Bioanalytical methods applied to absorption, distribution, metabolism and excretion studies of therapeutic proteins.
MethodsCapability to assay forCurrent throughputCurrently useCurrent sensitivity
ImmunoassayTotal, free, intactHigh for serum, low for tissues, requires homogenizationMostly serum/plasma, physiological fluids (e.g., synovial and bronchoalveolar lavage )Usually high for serum/plasma
BioassayActivity of targets, biomarker, ex vivo efficacyMedium to low, may require fresh samples for certain assaysSerum/plasma and tissuesVaries depending on individual assay
Radioactivity countingTotal, intact and degradantsHigh, requires probe preparation and characterizationSerum/plasma, tissues, biological fluids, and excretaUsually high, depending on specific activity of labeled materials
MSTotal, free, intact and degradantsHigh for peptides in serum/plasma, requires homogenization for tissuesSerum/plasma, tissues, biological fluids, and excretaUsually high for peptides
Medium to low for proteins in plasma/serum, requires purification (e.g., immunocapture) and digestion for large MW biologicsLow for large proteins
ImagingTotal, intact and degradantsMedium to low, requires probe preparation and characterizationLive animals, clinical studies in humans, cells and tissuesVaries, depending on probes used and study settings
Auto-radiographyTotal, intact and degradantsLow, requires tissue slicing and film developingTissuesVaries, depending on specific activity of labeled materials

The identification and quantification of specific isoforms within the drug product (for example those containing a specific posttranslational modification or bound impurity) in blood and tissues are important because different isoforms may have differential ADME properties, as demonstrated for several therapeutic proteins[89-91]. In vivo measurement of various isoforms may guide the design of drug product with improved ADME profiles; however the current methodology for such studies [mostly based on liquid chromatography-mass spectrometry (LC/MS) technologies] is limited and very labor intensive. While metabolic ID and metabolite quantitation studies for therapeutic proteins are not routinely conducted (and not required by the regulatory agencies), these studies are needed to understand mechanisms of unexpected ADME, PD, or toxicity profiles exhibited by some biotherapeutic drug candidates; however, the available methods for these investigations are in most cases not adequate.

Thus, a breakthrough in bioanalysis methodology will be necessary for advancement of the science of biotherapeutics’ ADME to the next level. The next generation assay platforms, such as non-invasive imaging, LC/MS, immune-polymerase chain reaction (PCR) or aptamer-PCR, that are emerging to meet the demands of rapid growth in biologics discovery research are reviewed in references[87,92,93].

Unusual pharmacokinetic profiles of mAbs: With the advent of novel and advanced engineering tools, mAbs are being optimized to achieve higher affinity to targets, improve target specificity, reduce clearance and prolong half-life. However, an unwanted consequence of mAb optimization appears to be increased incidence of therapeutic candidates with unexpected disposition profiles. The causes of the unexpected pharmacokinetic profiles often remain unknown, including translatability from animals to humans.

Several recent publications illustrate the challenges of unexpected fast clearance and altered distribution behavior of protein therapeutics. Vugmeyster et al[45] and Bumbaca et al[94] case studies provided examples of species-dependent fast clearance, which was attributed to off-target binding in cynomolgus monkey (fibrinogen) and in mice (complement component 3), respectively.

Perhaps the more troublesome from the drug development standpoint are examples of species-independent fast clearance with unidentified causes. The examples include anti-IL-21R antibodies[95,96] and anti-RSV Ab[97] derived via a phage-display optimization, as well as a number of case studies with unrevealed therapeutic targets presented at scientific meetings. In these examples, common factors affecting mAbs/protein disposition (such as target binding, FcRn binding, whole blood stability, and ADA) were determined to be unlikely to account for the observed kinetic profiles. The disposition profiles of these mAbs with faster clearance are suggestive of low affinity and large capacity off-target binding: specifically, the observed early rapid declines in serum concentrations and linear pharmacokinetics over a large dose range. Of note is the possibility of multiple low affinity off-target binding epitopes for a given mAb, resulting in a net large capacity off-target sink. In addition to its impact on ADME profiles, the off-target binding may also be relevant for pharmacological and safety assessments, and may require changing the dosing regimens to improve exposure.

In summary, there is still a significant gap in our understanding of disposition mechanisms of therapeutic proteins, even for the most common class, such as mAbs, which complicates commercial development.

The role of net charge (pI) and local charge clusters on disposition of therapeutic proteins: The role of charge (pI) on PK and biodistribution of therapeutic proteins remains to be systematically characterized. A recent review by Boswell et al[98] summarized the current knowledge. The mechanism behind the impact of charge on PK is believed to be the interaction of positively charged therapeutic proteins with negatively charged endogenous components within cell surface residues (sialic acids, glycosaminoglycans), i.e., a large capacity off-target sink, reminiscent and likely related to the phenomenon described above for mAbs with unexpected PK profiles. However, very few mechanistic studies are reported in the literature.

Charge heterogeneity or variability may be a consequence of deliberate changes, such as protein engineering or chemical modifications, or a result of spontaneous alterations occurring during manufacturing, such as post-translational modifications. In general, cationization is believed to shorten the half-life and decrease exposure, while anionization is believed to prolong the half-life and increase exposure[99-101]. However, the relationship between the net charge and disposition profile is not always straightforward[98]. As proposed by Boswell et al[98], net charge may alter tertiary or quaternary structure of the therapeutic molecule, resulting in indirect effects on disposition profiles, including altered FcRn interactions or altered charge localization. It is possible that the effective exposed local charge clusters, and not necessarily the total net charge, may ultimately account for the extent of interaction of therapeutic proteins with endogenous charged residues. Thus, deliberate engineering out of exposed positive charge clusters (not involved with target interactions) may be a rationale approach for improving PK profile of a therapeutic protein.

In summary, while many case studies that address the relationship between the protein charge and in vivo disposition have been described, a comprehensive assessment, including mechanistic and structural studies, remains to be conducted. The practical application of this emerging science is a potential for rational design of drug variants with desired PK and disposition properties. Thus, charge engineering may provide an alternative approach for modulation of ADME profiles of biotherapeutics and can be used instead of or in combination with other approaches, such as Fc-engineering or PEGylation.

FcRn: Role in absorption, distribution and in vitro/in vivo correlations: While significant scholarship has been acquired on the role of FcRn in disposition of antibodies and other Fc-containing biotherapeutic modalities (see “WHAT IS KNOWN” section), this remains to be a very active area of research with important applications in commercial development. Most published studies on the role of FcRn focus on serum pharmacokinetics and FcRn-mediated protection from lysosomal degradation; in contrast, the mechanistic studies on FcRn-mediated antibody absorption and distribution into tissue are sparse.

Current understanding of the role of FcRn in antibody absorption is limited. Deng et al[38] reported that the FcRn variant of an anti-TNF Ab with stronger affinity for FcRn at neutral pH appeared to have lower bioavailability after SC administration, possibly related to delayed release of the antibody leading to accelerated degradation at the injection site. Recent studies support the role of FcRn in SC absorption of mAbs in rodents[13,102] (and Balthasar lab, unpublished observations). Specifically, the bioavailability of an IgG1 antibody following SC administration was about 3-fold higher in WT mice compared to FcRn-deficient mice[102]. While the mechanism of FcRn-mediated effects on SC bioavailability is not known, it may include the protection during FcRn-mediated transport from interstitial fluid to the blood, as well as protection from catabolism at the site of injection and in the lymphatic system.

A mechanistic understanding of the role of FcRn in antibody distribution is also lacking. Studies with intestinal human cell lines suggested that FcRn transports IgG across cell monolayers, implicating FcRn in transport of mAbs from circulation to the interstitial fluid of tissues[103]. Several physiologically-based pharmacokinetic models that incorporate FcRn-mediated IgG transport have been developed and the model predicted an important role of FcRn-mediated mechanism on antibody distribution to various tissues in mice using a few test IgGs[104,105]. Comprehensive evaluations of the contribution of FcRn to transport of IgGs into various tissues in rodents and primates have not been performed, including quantitative assessment on the contribution of FcRn in tissue distribution of IgGs in animals and humans.

Following the discovery of the role of FcRn on antibody disposition, optimization of protein structures via improving FcRn binding has been pursued by pharmaceutical companies as an approach to produce a drug candidate with the desired half-life. Multiple studies have been performed with IgG variants engineered to have different binding affinities and/or kinetics and tested for the impact on PK profiles[33-43]. The cornerstone for these Fc-engineering efforts has been in vitro assays (such as surface plasmon resonance (SPR) or cell-based binding in FcRn-expressing cell lines) to test engineered variants for modulation of FcRn binding. However, the in vitro and in vivo correlations between the FcRn binding parameters determined from either SPR or cell-based methods remain controversial, with some studies reporting a good correlation of in vitro binding at pH 6.0 and the in vivo PK profiles[34,38-41] and other studies failing to demonstrate such a correlation[36,37,43]. The lack of the correlation between the binding at pH 6.0 and in vitro PK for some mAbs was linked to the hypothesis that efficient binding at pH 6.0 needs to be complemented by the lack of binding and/or fast off-rate at neutral pH in order for IgGs or Fc-containing proteins to be salvaged by FcRn[37,106,107]. In general, it is likely that quantitative modeling that utilizes the combination of the kinetic parameters for FcRn/Fc-containing protein interaction (such as kon and koff rates at acidic and neutral pHs) and other “determinants” of clearance for a particular Fc-containing protein, will be needed to improve the in vitro and in vivo correlations, because the relative contribution of a given in vitro binding parameter to the overall in vivo clearance may differ across Fc-containing proteins (discussed by[38,107]). In addition, very recent studies suggested that mAbs with the same Fc sequence but different CDRs can exhibit differences in FcRn binding parameters and in PK profiles, possibly via CDR-mediated impact on tertiary structures of the Fc region, leading to altered FcRn binding[107,108]. Furthermore, the translation of FcRn effects from animal studies to humans is not straightforward, in part due to species differences in FcRn binding[31,32]. The recent report by Zheng et al[109] on pharmacokinetics of FcRn variants highlights the challenges in translating FcRn-mediated modulation of pharmacokinetics from animals to humans, including the cases when non-human primates are used for nonclinical investigations.

In summary, the role of FcRn in antibody absorption after SC administration and in tissue distribution (after dosing via any route) remains to be characterized and quantified. Potential species differences in the role of FcRn in ADME of IgGs need to be systematically investigated to enable translation of the effects of FcRn modulation from animals to humans. The translation of in vitro FcRn binding kinetics to in vivo PK remains to be understood and is crucial for the success of rational Fc engineering.

Factors influencing SC absorption: Upon comparison of absorption parameters (such as bioavailability and Tmax) across various therapeutic proteins administered by SC injection, a wide range of mean/median values is apparent, especially for biologic modalities beyond mAbs (Table 1)[10,110]. The reason for this variability across different therapeutic proteins is not known, but many factors are likely involved (see “WHAT IS KNOWN” section for the list of possible factors), and the relative contributions of these factors are likely to vary with biologic modality or even a particular therapeutic protein within the same modality. Poor bioavailability translates into higher cost of goods and the need for higher doses and/or more frequent dosing. Therefore, a thorough understanding of key processes and factors that impact SC absorption and application of this knowledge for design of SC-administered biologic drug products with improved systemic exposure has significant commercial implications.

Surprisingly little is known about the mechanisms of absorption of therapeutic proteins following SC administration. In addition, it appears that there are significant species differences in physiology and mechanisms affecting kinetic profiles in disposition of therapeutic proteins upon SC dosing, such that the nonclinical models and methodologies for prediction of human SC profiles need to be further explored (Table 1)[10].

In general, SC bioavailability depends on pre-systemic metabolism/catabolism and systemic absorption[102]. Physiological processes that drive SC absorption of therapeutic proteins are believed to be convective transport across the lymphatic vessels (“lymphatic drainage”), passive diffusion across the blood vessels at the absorption site, and for molecules with an Fc, specific FcRn-mediated transport mechanisms. The relative contribution of these processes to SC absorption for a given biologic modality is controversial. Studies in sheep indicated that the main pathway of SC absorption is via lymphatic drainage for proteins larger than 20 kDa (using mostly non-Fc containing proteins)[111,112]. In contrast, in rodents and rabbits the relative contribution of lymphatic system in SC absorption is small[12,113,114]. There is no similar mechanistic data in monkeys or humans, and it is not known how to extrapolate the existing data to humans.

In summary, a comprehensive evaluation of factors and mechanisms influencing SC absorption in humans and animals needs to be conducted. Then models, including species-specific models that account for the complex interplay of the factors involved in SC absorption (for example, physiologically-based absorption and disposition models), need to be developed. Finally, these models need to be validated for predictability of human PK profiles across therapeutic modalities, species, and subjects.

Complex role of glycans: A variety of mechanisms are believed to account for the effect of glycans on the disposition and biological activity of therapeutic proteins, and the research in this field is rapidly expanding. In general, glycosylation can impact protein ADME properties by (1) masking of proteolytic or immunogenic site (decreasing degradation/clearance), or, conversely by introducing new immunogenic sites (increasing degradation/clearance); (2) changing total or local charge; (3) promoting or interfering with dimerization or multimerization; and (4) changing contribution of clearance and distribution pathways mediated by specific glycan receptors. If the clearance of the protein is increased by any of these mechanisms, then the PD effect is typically decreased.

For mAbs, glycosylation in the Fc region has been shown to modulate binding to Fc gamma receptors and complement components, which can either decrease or increase CDC and/or ADCC functions[115-117], depending on the type of the modification. However, the link between the Fc-related glycosylation and the PK profile of a mAb remains controversial, with some studies supporting such a link but not the others. It is possible that the impact of Fc-linked glycans on the disposition of mAbs is species- and molecule-dependent. Initial studies have indicated that in the Fc region, glycans are not thought to be accessible to receptors that can mediate glycan-dependent clearance and thus have minimal effect on PK[118]. Recent case studies have suggested this may not always be the case, with some studies reporting increased clearance in humans and mice for high mannose enriched and afucosylated Fc-glycovariants of some mAbs[119-121], but not other variants[122,123]. It should be noted that the majority of antibodies (including therapeutic mAbs) have no glycans attached to their variable region, with a few possible exceptions[124,125].

Although glycosylation has also been shown to play a prominent role in both disposition and PD for therapeutic proteins beyond mAbs[64], there are still numerous unanswered questions on mechanisms and predictability from biophysical profiling to in vivo PK and PD profiles. For example, the role of sialic acid in protein disposition and correlations between the extent/site of sialic acid content and effects on clearance and distribution has been an active research topic. Several reports indicate that increased sialic acid content in biotherapeutics is associated with reduced clearance and improved PK profiles[90,126-128]. Conjugation of polysialic acid (PSA) has been shown to increase half-life of several proteins, such as asparaginase, Fab fragment, and insulin[129]. The mechanism behind the beneficial effects of polysialylation on PK profile needs to be investigated and is likely related to be a combination of multiple factors, including masking of proteolytic and/or immunogenic sites and an increase in size beyond the renal filtration cut-off. In addition, relative contributions of these factors are likely to be different for each protein-polymer conjugate. This approach for half-life extension is similar to PEGylation[130], with a potential advantage of employing a natural, biodegradable polymer. Similar to PEGylation, polysialylation may lead to the decrease in biologic activity of a therapeutic protein; therefore for an optimal PD effect, a design that balances effects on PK and biological activity should be considered.

In summary, glycol-engineering and modulation of glycosylation during production of a biotherapeutic is a widely used approach for increasing exposure (by decreasing clearance), and for altering the biological activity of therapeutic proteins. The success of such modification in meeting the planned objective has been variable. Similar to considerations mentioned above for other protein engineering approaches, the key to commercial success of glycol-engineering is a mechanistic understanding of clearance pathway and species differences, as well as translation from the biophysical glycan profiles and in vitro activity to in vivo effects. An additional consideration for glycol-engineering is balancing the effects on PK versus PD to achieve optimal clinical efficacy.

Effect of ADA on clearance and distribution: While the impact of ADA on serum PK and PD profiles has been described qualitatively/semi-quantitatively in many case studies (see “WHAT IS KNOWN” section), the quantitative tools to link ADA characteristics [such as titer (which is related to both avidity and concentrations of ADA), persistence, isotypes, and neutralization potential] to PK or PD are lacking. For development of such a quantitative tool, significant advances in our knowledge of mechanisms behind ADA-driven clearance and distribution processes are needed. However, the mechanistic and quantitative studies on the impact of ADA on clearance and distribution of therapeutic proteins in both nonclinical and clinical settings are sparse[61,131].

The mechanisms responsible for the elimination of ICs in general and biotherapeutic/ADA complexes in particular remain to be fully delineated, although the important role of red blood cells and mononuclear and phagocyte system in the liver have been demonstrated (see “WHAT IS KNOWN” section). For example, both the Kupffer cells and sinusoidal endothelial cells in the liver are thought to be involved in the clearance of these ICs from the circulation via Fc-receptor dependent uptake[61]. However, because Fc receptors are expressed in many other organs, yet the largest relative uptake of ICs is reported in the liver, it is possible that there is an Fc receptor-independent uptake of ICs in this organ. In addition, some but not all studies implicate spleen in the clearance of ICs and suggest that size and type of ICs may influence the relative contribution of different elimination processes for ICs[61,132]. In the case of ADA, which are highly heterogenic across subjects or even in any given subject sample[55], ICs of different types and sizes are expected to form. Therefore, multiple ADA-mediated clearance and distribution pathways may be present for any given subjects or within the study population.

Johansson et al[61] provided a detailed case study on the in vitro IC formation and in vivo clearance and distribution of a model mAb (“Id”) and its monoclonal anti-idiotype (“anti-Id”) in mice. The in vitro results from this study suggested that the relative concentrations of the reactants (related to the dose of a mAb in the in vivo settings) played a role in the type and size of Id/anti-Id immune complexes generated, as examined by electron microscopic and other biochemical techniques. In the in vivo study, mice were given a single dose of the radiolabeled Id, followed by an injection of the unlabeled anti-Id antibody at different Id/anti-Id ratios; the total body clearance of Id, as well as uptake in various organs, were monitored. These studies indicated there is stoichiometric dependence on the impact of anti-Id antibody on the clearance of Id and that the metabolism of the ICs between Id and anti-Id occurred mainly in the liver.

In a study by Rojas et al[131] cynomolgus monkeys were given a single IV dose of a therapeutic antibody infliximab (IFX), followed by injection of either 125I-labeled, purified monkey anti-IFX IgG (test group) or 125I-labeled monkey non-binding control IgG (control group). This study was designed to model the formation of ADA/biotherapeutic ICs in the presence of excess antigenic protein, such that IFX was given in excess of 125I anti-IFX IgG or 125I-control IgG. In vivo formation of IFX/125I anti-IFX ICs of variable size was confirmed by high-performance liquid chromatography analysis. The serum PK profile of IFX, although somewhat lower in concentration over time for the test group (i.e., IFX given in combination with anti-IFX Ab), was not statistically different relative to the control group. In contrast, the terminal half-life and clearance of the 125I- anti-IFX IgG (circulating largely in complex with IFX) was significantly shorter because of more rapid elimination compared with the 125I- control IgG. The authors noted that these data illustrated that detection of ADA-containing ICs may be challenging because of the rapid clearance of the ADA/biotherapeutic ICs, especially in cases when a transient anti-drug immune response is triggered. Interestingly, the authors also provided evidence that red blood cells appeared to play only a limited role in the elimination of ICs.

It should be noted that in some cases the relative impact of ADA on serum drug concentrations cannot be directly extrapolated to tissue profiles[19], which may have significant implications for projections of efficacious dosing regimens for a biotherapeutic which has its site of action in tissues. For an anti-IL-21R Ab administered to wild-type or lupus-prone mice, a differential impact of ADA was shown for tissues serum. Specifically, after a single dose of 125I-labeled anti-IL-21R Ab to mice, there was a rapid decline of serum drug concentrations at 10-21 d post dose, associated with development of ADA. However, tissue drug concentrations declined at a slower rate. Interestingly, the difference between serum and tissue drug concentrations was more pronounced in the disease model vs healthy animals, related primarily to faster clearance in the serum in the disease model. In general, it appears that in single-dose studies in which formation of ADA leads to a reduction in serum drug concentrations, an increase in tissue-to serum concentration ratios is observed and tissue concentrations often approach or even exceed those in serum as the ADA removes the test article from the serum more rapidly than tissues[19]. In these cases, it is likely that the relatively high tissue concentration reflected the high serum concentrations before the onset of ADA.

In summary, comprehensive mechanistic studies on ADA-mediated distribution and elimination of therapeutic proteins in nonclinical and clinical settings will be instrumental in building PK-PD relationship that take into account the ADA-mediated effects, including dose-dependency and inter-subject variability of these effects. However, because of highly heterogenic nature of ADA response, the quantitation of these ADA-mediated effects is expected to be challenging and will require unique modeling approaches.


Species selection: As noted above (in the “WHAT IS KNOWN” section), there are standard paradigms for selecting species for toxicity studies. However, how closely the pharmacologic effects of a biotherapeutic in a given species truly mimics the effects in humans are often not really known. In some cases, in vivo assays, including efficacy models, may be available. This is particularly true when the biotherapeutic has activity in rodents, but is often less common if the molecule only has activity in primates. If a biotherapeutic demonstrates activity in vivo, it is usually based on a limited set of parameters, and it is always possible that other parameters that were not evaluated might also be affected. Furthermore, the translatability of in vitro effects to in vivo effects is often not clear, given the complex, overlapping, and/or redundant pathways that can exist. For example, if a biotherapeutic in an in vitro assay causes a 20% effect, it is possible that a full 100% effect might still occur in vivo. The TGN1412 clinical trial was one case where it is believed that unrecognized species differences led to significant adverse events in human subjects, because the cynomolgus monkey used in the testing were not as sensitive to the biological effects of the test article[133,134].

In cases where there is no pharmacologically-relevant species from standard toxicology species, toxicologists may turn to the use of animal models of disease[135]. While this may be the only option, it should be recognized that little is often known about the model from a toxicology standpoint, historical data may be limited or completely lacking to assist in interpretation of findings, the disease may confound interpretation of toxicological effects, and the models may not be suitable for long-term dosing.

Another option when there is no pharmacologically-relevant toxicity species is to use a surrogate molecule[135]. This surrogate would ideally have activity in a standard species used in toxicity testing, and in particular in the mouse or rat because they represent a more controlled population, smaller size and associated lesser amount of drug needed, lower animal cost, and in keeping with trying to minimize monkey use. However, the use of surrogates requires careful manufacturing and characterization of the surrogate to a degree that may come close to mimicking the efforts required for the actual drug candidate. Because of this extensive effort, most consider the use of a surrogate to be a last resort. If a surrogate is used, questions still remain. Does the surrogate interact with the target in the exact same way and lead to the exact same biological effect? If not, what are the differences? Are the downstream effects the same as those that occur in humans (which is usually not known at the time the studies are conducted because in vivo testing has not occurred in people)? Again, if not, what are the differences? In reality, it is unlikely that the interaction with the target and downstream effects will exactly mimic those in humans, and it is also unlikely that these differences will be completely understood.

Still another option is the use of genetically-modified animals, typically mice[135]. These animals may have reduced or loss of function for a particular target (knockout), or may have gain-of-function to mimic agonists (knock-in). In addition, animals can be constructed to express the human target. In all these cases of using genetically-modified animals, much is unknown. As with disease models, historical data may be limited or completely lacking to assist in interpretation of findings. In the case of loss or gain of function mutations, this alteration is often complete and present from conception. This differs substantially from the therapeutic case, which usually involves variable drug concentrations and corresponding variable PD effects over time, only partial loss or gain of function, or complete loss or gain of function only intermittently. In addition, the therapeutic effect of an exogenously administered drug is typically not present from conception. How these differences affect the toxicity of a biotherapeutic is often not known, but one usually considers such knockout or knock-in animals to represent a worst case scenario for loss or gain of function. Regarding animals which have been modified to express human molecules, whether the cellular distribution, signaling, and function in the animal biologically matches the human is usually not completely clear.

Immunogenicity: The administration of biotherapeutics to animals often results in immune responses to the drug. The immune responses to the drug can take many forms, including production of ADA and cellular immune responses[55,136]. Impact of ADA on PK/PD of therapeutic proteins is discussed above. From the standpoint of clinical signs in a toxicity study, the effects related to immunogenicity can be quite diverse, ranging from no effect to hypersensitivity reactions (up to and including fatal anaphylaxis) to loss of function of the endogenous molecule. For example, in the case of replacement proteins, the ADA can result in neutralization of the endogenous protein as well as the administered protein, as discussed above. From a clinical and anatomic pathology standpoint, effects may also be diverse. One may see subtle evidence of inflammation, with alteration in white cell counts and microscopic evidence of lymphoid hyperplasia from immune stimulation, immune-mediated vasculitis or glomerulonephritis, or effects secondary to loss of function of the endogenous protein (for example, aplastic anemia in the case of neutralization of erythropoietin). It is generally accepted that immune reactions in animals are not predictive of what will occur in humans, and therefore, the effects related to immune reactions in animals are generally not considered to be relevant to humans[136]. However, differentiating these immunogenicity-related findings from direct test article-related effects can be challenging, in particular when the test article is an immunomodulator.

Tools that can assist in determining whether an effect is related to an immune reaction include the presence of ADA, effects on PK, loss of PD effect, activation of complement, the presence of circulation immune complexes, and evidence of histamine release. Clinical signs consistent with anaphylaxis (including having the effects shortly after dosing) can also be useful in determining whether effects are related to an immune response to the biotherapeutic. Microscopically, anti-drug immune responses may result in findings such as vasculitis or glomerulonephritis[137-140]. It may be possible to detect animal IgG, IgM, and/or complement in the lesions. In some cases, it may also be possible to detect the test article in the lesions, for example using specific anti-human antibodies or anti-CDR antibodies that can detect the human biotherapeutic without binding to animal molecules. If the study has a range of doses, as most toxicity studies have, findings overall may exhibit an inverse or bell-shaped dose-response relationship. This pattern may be related to development of tolerance, or may be related to the pharmacologic activity of the test article in the case of immunomodulators that may down regulate the immune response to a greater magnitude at higher doses. When all analyses are done, there are some cases in which there is a strong correlation between animals with clinical or pathologic effects and evidence of ADA. However, in many cases the correlation is not as strong, and findings are somewhat variable between individual animals. In these cases, one must use a weight of evidence approach to reach a final conclusion that the study or program may be impacted by anti-drug immune responses.

When immunogenicity does develop, it is sometimes recommended to dose through the immunogenicity, and perhaps to increase the dose (dose level, dosing frequency, or both). The latter strategy may have several potential effects. It may simply overwhelm the immune response and allow free drug to have whatever biological effects it will have, it may induce tolerance, and/or it may increase immunosuppression in the case of immunosuppressants. On the other hand, the relevance of this situation to humans is often unclear. While some concerns have been raised related to protein overload in situations where doses are high, from a practical standpoint the large amounts of administered protein alone do not appear to cause any significant effects in most cases.

Another concern related to immunogenicity is the impact of previous exposure to other biotherapeutics. As biotherapeutics become more commonly used, there is an increased chance that the patient may have been dosed with other biotherapeutics in the past. The impact of this cannot be modeled well nonclinically, as immune responses in animals are not predictive of what happens in humans. However, several scenarios are possible in humans. There may be no immune response and no impact; there may be an immune response to the previous biotherapeutic that reacts with the new biotherapeutic and potentially results in clearance, neutralization, or hypersensitivity reactions; or the previous biotherapeutic many have modified the immune response to the new biotherapeutic, either increasing or decreasing the response. Because of these variable impacts, clinicians should carefully assess patients who have previously received biotherapeutics.

Latent infections: While rodents, rabbits, and dogs used in toxicity studies are usually purpose-bred and do not contain background infectious agents or parasites, the same is not true for monkeys[141-143]. While the monkeys used in toxicity studies are usually tested for a variety of infectious agents and parasites, and should not have overt infections or parasitic infestations at the time of study initiation (or they should be excluded from the study), there are limits to the number of agents that are tested and the assays are not full proof. For example, recrudescence of malaria, polyomavirus, and lymphocryptovirus can occur in toxicity studies evaluating immunosuppressants. It is possible that unknown agents may also play a role. In a recent study, pretest blood cultures revealed an unspeciated organism in greater than 80% of animals (Leach MW, unpublished data). Differentiating the pharmacologically-mediated effects of immunnosuppressants from secondary stress-induced immunosuppression can be challenging.

Juvenile toxicity assessments: When the clinical population involves children, testing of juvenile animals may be necessary[144]. Paradigms for juvenile toxicity testing have been well established through many years of experience for rodents[145]. However, because many biotherapeutics only have activity in primates, juvenile toxicity evaluations (when they need to be conducted to support the clinical program) may need to be conducted in monkeys. In contrast to rodents, protocols to assess juvenile toxicity in monkeys have only recently been developed and there is very limited experience with these studies[146]. Furthermore, while the time from birth to sexual maturity is only several 2 months in rodents, it is years in monkeys, and covering this entire period in a toxicity study is not practical. How to adequately and rationally address juvenile toxicity when monkeys are the only pharmacologically active toxicology species remains an area of discussion.

Carcinogenicity assessment: The assessment of carcinogenic risk for biotherapeutics can be challenging. Biotherapeutics typically do not have direct effects on DNA, and thus are secondary carcinogens when they cause tumors. Therefore, many of the standard assays for detecting potential carcinogens, such as the Ames test, are not relevant and should not be conducted[74]. For small molecules, many compounds are assessed in lifetime rodent studies. However, because of the lack of pharmacologic activity of many biotherapeutics in rodents, such studies cannot be conducted. Furthermore, immunogenicity can be an issue, resulting in neutralization of the test article and/or in long term immune stimulation. In either case, interpretation of the data and assessment of the relevance to humans can be challenging. Lifetime dosing of monkeys is not considered practical. At the present time, it is recommended that the need for a product-specific assessment of the carcinogenic potential for biopharmaceutical be determined with regard to the intended clinical population and treatment duration[75]. The presence or absence of cell proliferation in general toxicity studies may be useful. If a carcinogenicity assessment is warranted, for example for chronic dosing with a potential mechanistic concern for an increased risk of tumors, then a strategy should be developed to address the potential hazard[75]. It should be noted that standard rodent carcinogenicity studies with the test article, or carcinogenicity studies with homologous products, are not usually considered useful in most situations[75]. As noted above, latent infections can occur, and some of these are known to result in lymphoproliferative disease[141]. In some cases, additional in vitro or in vivo cancer models may be conducted in an attempt to shed some light on the potential risk for carcinogenicity.

Biosimilars: The topic of biosimilars is receiving extensive discussion, as many biotherapeutics are losing patent protection in the near term[147,148]. From a nonclinical perspective, global regulatory agencies are determining what they feel is necessary for development and approval[149-152]. The US Food and Drug Administration (FDA) and European Medicines Agency (EMA) appear to be favoring a scientific approach with relatively limited in vivo toxicity studies, and a greater reliance on in vitro characterization of the product. This is related to relative lack of sensitivity in detecting small differences in innovator vs biosimilar products in vivo toxicity studies under most circumstances. However, it is unclear exactly how similar a biosimilar must be to the innovator, and in what assays, to demonstrate equivalent biologic/therapeutic effect. It is likely that what characteristics matter may differ between molecules, or especially between classes of molecules. As the global scientific community gains additional experience with biosimilars, some of these questions may be answered. Another unresolved issue with biosimilars is related to global harmonization. At the present time it is not clear whether the scientific approach being adopted by some countries and regions that limits animal studies will be accepted globally. Thus, it is possible that different regions of the world will ask for a variety of toxicity studies, increasing the total number of studies required for global registration, and increasing animal use. It is hoped that all regions of the world will utilize strong scientific principles and only require the studies that are truly needed.


Despite the rapid increase in knowledge of mechanisms involved in ADME of therapeutic proteins, many fundamental questions remain answered. Some of the emerging questions and active research topics include the role of charge and glycosylation, factors influencing SC absorption, role of FcRn beyond serum half-life extension, as well as anti-drug antibody-mediated clearance and distribution mechanisms. A comprehensive evaluation of factors influencing ADME of biotherapeutics and mechanistic studies in nonclinical and clinical settings is needed to build in vitro tools that can be used to predict disposition and biological activity profiles and to establish structure activity relations (SARs). The acquisition of mechanistic knowledge is currently hindered by the limited bioanalytical methods to assess the concentration of biotherapeutics in tissues, as well as tools to study metabolism/catabolism in both blood and tissues and to assess potential differences in ADME profiles of drug product isoforms. A breakthrough in bioanalysis, including MS-based techniques and imaging tools, will be instrumental for the success of rational protein engineering aimed at optimizing ADME profiles. In addition, because of complex interplay of factors influencing ADME and biological activity of protein therapeutics and potentially multiple sites of actions, modeling tools ranging from “fit for purpose” and “site of action” to full physiologically-based pharmacokinetic models may be needed to build in vitro/in vivo correlations and enable translation from animals to humans.

In toxicology, much has been learned since the advent of biotherapeutics regarding what studies are needed to safely develop these drug, and what studies do not provide relevant information. The concept of appropriate species selection has become relatively well accepted. However, there is room in some cases to develop better models that more closely mimic the pharmacologic activity in humans. In cases where there is no pharmacologic activity in standard toxicology species, the appropriate design of toxicology programs, including the use of animal models of disease, surrogate molecules, and genetically-modified animals, is still an area of need. The design of reproductive toxicity studies in monkeys has made substantial progress in the past decade. However, these studies lack sufficient power to identify uncommon findings. How to adequately assess juvenile toxicity, when monkeys are the only pharmacologically-relevant toxicology species, remains an area of need. Immunogenicity can cause significant issues in nonclinical development, and strategies to minimize immunogenicity in animals while still testing the molecule in a relevant manner are needed. Despite the issues, a large number of biotherapeutics have been successfully brought to market with acceptable benefit: risk ratios, providing better treatments to innumerable patients.


Peer reviewers: Tatjana Abaffy, Dr., Molecular and Cellular Pharmacology, University of Miami, Miller School of Medicine, 1600 NW 10 Ave, Miami, FL 33136, United States; Conceição Maria Fernandes, Professor, Department of Escola Superior Agrária, Instituto Politécnico de Bragança, Campus de Santa Apolónia, Apartado 1172, 5301-854 Bragança, Portugal; Xiao-Feng Zheng, Professor, Department of Biochemistry and Molecular Biology, Peking University, Beijing 100000, China

S- Editor Cheng JX L- Editor A E- Editor Zhang DN

1.  Keizer RJ, Huitema AD, Schellens JH, Beijnen JH. Clinical pharmacokinetics of therapeutic monoclonal antibodies. Clin Pharmacokinet. 2010;49:493-507.  [PubMed]  [DOI]  [Cited in This Article: ]
2.  Scheuch G, Siekmeier R. Novel approaches to enhance pulmonary delivery of proteins and peptides. J Physiol Pharmacol. 2007;58 Suppl 5:615-625.  [PubMed]  [DOI]  [Cited in This Article: ]
3.  Siekmeier R, Scheuch G. Inhaled insulin--does it become reality? J Physiol Pharmacol. 2008;59 Suppl 6:81-113.  [PubMed]  [DOI]  [Cited in This Article: ]
4.  Suresh PV, Paliwal R, Paliwal SR. Ocular Delivery of Peptides and Proteins. Peptide and Protein Delivery. London: Academic Press 2011; 87-103.  [PubMed]  [DOI]  [Cited in This Article: ]
5.  Geary RS. Antisense oligonucleotide pharmacokinetics and metabolism. Expert Opin Drug Metab Toxicol. 2009;5:381-391.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 215]  [Cited by in F6Publishing: 213]  [Article Influence: 15.2]  [Reference Citation Analysis (0)]
6.  Lichtenstein GR, Panaccione R, Mallarkey G. Efficacy and safety of adalimumab in Crohn's disease. Therap Adv Gastroenterol. 2008;1:43-50.  [PubMed]  [DOI]  [Cited in This Article: ]
7.  Mannaerts BM, Geurts TB, Odink J. A randomized three-way cross-over study in healthy pituitary-suppressed women to compare the bioavailability of human chorionic gonadotrophin (Pregnyl) after intramuscular and subcutaneous administration. Hum Reprod. 1998;13:1461-1464.  [PubMed]  [DOI]  [Cited in This Article: ]
8.  Montagna M, Montillo M, Avanzini MA, Tinelli C, Tedeschi A, Visai L, Ricci F, Vismara E, Morra E, Regazzi M. Relationship between pharmacokinetic profile of subcutaneously administered alemtuzumab and clinical response in patients with chronic lymphocytic leukemia. Haematologica. 2011;96:932-936.  [PubMed]  [DOI]  [Cited in This Article: ]
9.  Gibson CR, Sandu P, Hanley WD. Monoclonal Antibody Pharmacokinetics and Pharmacodynamics. Monoclonal antibody pharmacokinetics and pharmacodynamics, in Therapeutic monoclonal antibodies: From bench to clinic. Hoboken, New Jersey: John Wiley & Son Inc 2009; 439-460.  [PubMed]  [DOI]  [Cited in This Article: ]
10.  McDonald TA, Zepeda ML, Tomlinson MJ, Bee WH, Ivens IA. Subcutaneous administration of biotherapeutics: current experience in animal models. Curr Opin Mol Ther. 2010;12:461-470.  [PubMed]  [DOI]  [Cited in This Article: ]
11.  Beshyah SA, Anyaoku V, Niththyananthan R, Sharp P, Johnston DG. The effect of subcutaneous injection site on absorption of human growth hormone: abdomen versus thigh. Clin Endocrinol (. Oxf). 1991;35:409-412.  [PubMed]  [DOI]  [Cited in This Article: ]
12.  Kagan L, Gershkovich P, Mendelman A, Amsili S, Ezov N, Hoffman A. The role of the lymphatic system in subcutaneous absorption of macromolecules in the rat model. Eur J Pharm Biopharm. 2007;67:759-765.  [PubMed]  [DOI]  [Cited in This Article: ]
13.  Kagan L, Turner MR, Balu-Iyer SV, Mager DE. Subcutaneous absorption of monoclonal antibodies: role of dose, site of injection, and injection volume on rituximab pharmacokinetics in rats. Pharm Res. 2012;29:490-499.  [PubMed]  [DOI]  [Cited in This Article: ]
14.  Lin JH. Pharmacokinetics of biotech drugs: peptides, proteins and monoclonal antibodies. Curr Drug Metab. 2009;10:661-691.  [PubMed]  [DOI]  [Cited in This Article: ]
15.  Schmidt MM, Wittrup KD. A modeling analysis of the effects of molecular size and binding affinity on tumor targeting. Mol Cancer Ther. 2009;8:2861-2871.  [PubMed]  [DOI]  [Cited in This Article: ]
16.  Thurber GM, Schmidt MM, Wittrup KD. Antibody tumor penetration: transport opposed by systemic and antigen-mediated clearance. Adv Drug Deliv Rev. 2008;60:1421-1434.  [PubMed]  [DOI]  [Cited in This Article: ]
17.  Liu DV, Maier LM, Hafler DA, Wittrup KD. Engineered interleukin-2 antagonists for the inhibition of regulatory T cells. J Immunother. 2009;32:887-894.  [PubMed]  [DOI]  [Cited in This Article: ]
18.  Dong JQ, Salinger DH, Endres CJ, Gibbs JP, Hsu CP, Stouch BJ, Hurh E, Gibbs MA. Quantitative prediction of human pharmacokinetics for monoclonal antibodies: retrospective analysis of monkey as a single species for first-in-human prediction. Clin Pharmacokinet. 2011;50:131-142.  [PubMed]  [DOI]  [Cited in This Article: ]
19.  Vugmeyster Y, DeFranco D, Szklut P, Wang Q, Xu X. Biodistribution of [125I]-labeled therapeutic proteins: application in protein drug development beyond oncology. J Pharm Sci. 2010;99:1028-1045.  [PubMed]  [DOI]  [Cited in This Article: ]
20.  Chan AC, Carter PJ. Therapeutic antibodies for autoimmunity and inflammation. Nat Rev Immunol. 2010;10:301-316.  [PubMed]  [DOI]  [Cited in This Article: ]
21.  Oldham RK, Dillman RO. Monoclonal antibodies in cancer therapy: 25 years of progress. J Clin Oncol. 2008;26:1774-1777.  [PubMed]  [DOI]  [Cited in This Article: ]
22.  Taylor AE, Granger DN. Exchange of macromolecules across the microcirculation. The Cardiovascular System, Handbook of Physiology. Baltimore, MD: Williams and Wilkins Company 1984; 467-520.  [PubMed]  [DOI]  [Cited in This Article: ]
23.  Urva SR, Balthasar JP. Target mediated disposition of T84.66, a monoclonal anti-CEA antibody: application in the detection of colorectal cancer xenografts. MAbs. 2010;2:67-72.  [PubMed]  [DOI]  [Cited in This Article: ]
24.  Vugmeyster Y, DeFranco D, Pittman DD, Xu X. Pharmacokinetics and lung distribution of a humanized anti-RAGE antibody in wild-type and RAGE-/- mice. MAbs. 2010;2:571-575.  [PubMed]  [DOI]  [Cited in This Article: ]
25.  Amantana A, Iversen PL. Pharmacokinetics and biodistribution of phosphorodiamidate morpholino antisense oligomers. Curr Opin Pharmacol. 2005;5:550-555.  [PubMed]  [DOI]  [Cited in This Article: ]
26.  Maack T, Johnson V, Kau ST, Figueiredo J, Sigulem D. Renal filtration, transport, and metabolism of low-molecular-weight proteins: a review. Kidney Int. 1979;16:251-270.  [PubMed]  [DOI]  [Cited in This Article: ]
27.  Sampson C Textbook of Radiopharmacy: Theory and practice. 3rd ed. Amsterdam: Gordon and Breach Science 1999; .  [PubMed]  [DOI]  [Cited in This Article: ]
28.  Schümann K, Kreppel H, Elsenhans B. Determination of residual erythrocytes in rat tissue homogenates using commercially available anti-red blood cell sera. J Pharmacol Methods. 1989;21:281-285.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Cited by in F6Publishing: 5]  [Article Influence: 0.1]  [Reference Citation Analysis (0)]
29.  Mould DR, Green B. Pharmacokinetics and pharmacodynamics of monoclonal antibodies: concepts and lessons for drug development. BioDrugs. 2010;24:23-39.  [PubMed]  [DOI]  [Cited in This Article: ]
30.  Raghavan M, Bjorkman PJ. Fc receptors and their interactions with immunoglobulins. Annu Rev Cell Dev Biol. 1996;12:181-220.  [PubMed]  [DOI]  [Cited in This Article: ]
31.  Kuo TT, Baker K, Yoshida M, Qiao SW, Aveson VG, Lencer WI, Blumberg RS. Neonatal Fc receptor: from immunity to therapeutics. J Clin Immunol. 2010;30:777-789.  [PubMed]  [DOI]  [Cited in This Article: ]
32.  Roopenian DC, Sun VZ. Clinical ramifications of the MHC family Fc receptor FcRn. J Clin Immunol. 2010;30:790-797.  [PubMed]  [DOI]  [Cited in This Article: ]
33.  Ghetie V, Ward ES. Multiple roles for the major histocompatibility complex class I- related receptor FcRn. Annu Rev Immunol. 2000;18:739-766.  [PubMed]  [DOI]  [Cited in This Article: ]
34.  Dall'Acqua WF, Kiener PA, Wu H. Properties of human IgG1s engineered for enhanced binding to the neonatal Fc receptor (FcRn). J Biol Chem. 2006;281:23514-23524.  [PubMed]  [DOI]  [Cited in This Article: ]
35.  Dall'Acqua WF, Woods RM, Ward ES, Palaszynski SR, Patel NK, Brewah YA, Wu H, Kiener PA, Langermann S. Increasing the affinity of a human IgG1 for the neonatal Fc receptor: biological consequences. J Immunol. 2002;169:5171-5180.  [PubMed]  [DOI]  [Cited in This Article: ]
36.  Datta-Mannan A, Witcher DR, Tang Y, Watkins J, Jiang W, Wroblewski VJ. Humanized IgG1 variants with differential binding properties to the neonatal Fc receptor: relationship to pharmacokinetics in mice and primates. Drug Metab Dispos. 2007;35:86-94.  [PubMed]  [DOI]  [Cited in This Article: ]
37.  Datta-Mannan A, Witcher DR, Tang Y, Watkins J, Wroblewski VJ. Monoclonal antibody clearance. Impact of modulating the interaction of IgG with the neonatal Fc receptor. J Biol Chem. 2007;282:1709-1717.  [PubMed]  [DOI]  [Cited in This Article: ]
38.  Deng R, Loyet KM, Lien S, Iyer S, DeForge LE, Theil FP, Lowman HB, Fielder PJ, Prabhu S. Pharmacokinetics of humanized monoclonal anti-tumor necrosis factor-{alpha} antibody and its neonatal Fc receptor variants in mice and cynomolgus monkeys. Drug Metab Dispos. 2010;38:600-605.  [PubMed]  [DOI]  [Cited in This Article: ]
39.  Hinton PR, Xiong JM, Johlfs MG, Tang MT, Keller S, Tsurushita N. An engineered human IgG1 antibody with longer serum half-life. J Immunol. 2006;176:346-356.  [PubMed]  [DOI]  [Cited in This Article: ]
40.  Petkova SB, Akilesh S, Sproule TJ, Christianson GJ, Al Khabbaz H, Brown AC, Presta LG, Meng YG, Roopenian DC. Enhanced half-life of genetically engineered human IgG1 antibodies in a humanized FcRn mouse model: potential application in humorally mediated autoimmune disease. Int Immunol. 2006;18:1759-1769.  [PubMed]  [DOI]  [Cited in This Article: ]
41.  Yeung YA, Leabman MK, Marvin JS, Qiu J, Adams CW, Lien S, Starovasnik MA, Lowman HB. Engineering human IgG1 affinity to human neonatal Fc receptor: impact of affinity improvement on pharmacokinetics in primates. J Immunol. 2009;182:7663-7671.  [PubMed]  [DOI]  [Cited in This Article: ]
42.  Zalevsky J, Chamberlain AK, Horton HM, Karki S, Leung IW, Sproule TJ, Lazar GA, Roopenian DC, Desjarlais JR. Enhanced antibody half-life improves in vivo activity. Nat Biotechnol. 2010;28:157-159.  [PubMed]  [DOI]  [Cited in This Article: ]
43.  Gurbaxani B, Dela Cruz LL, Chintalacharuvu K, Morrison SL. Analysis of a family of antibodies with different half-lives in mice fails to find a correlation between affinity for FcRn and serum half-life. Mol Immunol. 2006;43:1462-1473.  [PubMed]  [DOI]  [Cited in This Article: ]
44.  Fracasso PM, Burris H, Arquette MA, Govindan R, Gao F, Wright LP, Goodner SA, Greco FA, Jones SF, Willcut N. A phase 1 escalating single-dose and weekly fixed-dose study of cetuximab: pharmacokinetic and pharmacodynamic rationale for dosing. Clin Cancer Res. 2007;13:986-993.  [PubMed]  [DOI]  [Cited in This Article: ]
45.  Vugmeyster Y, Szklut P, Wensel D, Ross J, Xu X, Awwad M, Gill D, Tchistiakov L, Warner G. Complex pharmacokinetics of a humanized antibody against human amyloid beta peptide, anti-abeta Ab2, in nonclinical species. Pharm Res. 2011;28:1696-1706.  [PubMed]  [DOI]  [Cited in This Article: ]
46.  Gibiansky L, Gibiansky E. Target-mediated drug disposition model: relationships with indirect response models and application to population PK-PD analysis. J Pharmacokinet Pharmacodyn. 2009;36:341-351.  [PubMed]  [DOI]  [Cited in This Article: ]
47.  Gibiansky L, Gibiansky E. Target-mediated drug disposition model: approximations, identifiability of model parameters and applications to the population pharmacokinetic-pharmacodynamic modeling of biologics. Expert Opin Drug Metab Toxicol. 2009;5:803-812.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 87]  [Cited by in F6Publishing: 88]  [Article Influence: 6.3]  [Reference Citation Analysis (0)]
48.  Kagan L, Abraham AK, Harrold JM, Mager DE. Interspecies scaling of receptor-mediated pharmacokinetics and pharmacodynamics of type I interferons. Pharm Res. 2010;27:920-932.  [PubMed]  [DOI]  [Cited in This Article: ]
49.  Ng CM, Stefanich E, Anand BS, Fielder PJ, Vaickus L. Pharmacokinetics/pharmacodynamics of nondepleting anti-CD4 monoclonal antibody (TRX1) in healthy human volunteers. Pharm Res. 2006;23:95-103.  [PubMed]  [DOI]  [Cited in This Article: ]
50.  Urva SR, Yang VC, Balthasar JP. Physiologically based pharmacokinetic model for T84.66: a monoclonal anti-CEA antibody. J Pharm Sci. 2010;99:1582-1600.  [PubMed]  [DOI]  [Cited in This Article: ]
51.  Mould DR, Baumann A, Kuhlmann J, Keating MJ, Weitman S, Hillmen P, Brettman LR, Reif S, Bonate PL. Population pharmacokinetics-pharmacodynamics of alemtuzumab (Campath) in patients with chronic lymphocytic leukaemia and its link to treatment response. Br J Clin Pharmacol. 2007;64:278-291.  [PubMed]  [DOI]  [Cited in This Article: ]
52.  Tabrizi MA, Tseng CM, Roskos LK. Elimination mechanisms of therapeutic monoclonal antibodies. Drug Discov Today. 2006;11:81-88.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 362]  [Cited by in F6Publishing: 343]  [Article Influence: 19.1]  [Reference Citation Analysis (0)]
53.  Ferraiolo BL, Mohler MA. Goals and analytical methodologies for protein disposition studies. Protein Pharmacokinetics and Metabolism. New York: Plenum Press 1992; 1-21.  [PubMed]  [DOI]  [Cited in This Article: ]
54.  LaRusso NF. Proteins in bile: how they get there and what they do. Am J Physiol. 1984;247:G199-G205.  [PubMed]  [DOI]  [Cited in This Article: ]
55.  Koren E, Zuckerman LA, Mire-Sluis AR. Immune responses to therapeutic proteins in humans--clinical significance, assessment and prediction. Curr Pharm Biotechnol. 2002;3:349-360.  [PubMed]  [DOI]  [Cited in This Article: ]
56.  Pollock C, Johnson DW, Hörl WH, Rossert J, Casadevall N, Schellekens H, Delage R, De Francisco A, Macdougall I, Thorpe R. Pure red cell aplasia induced by erythropoiesis-stimulating agents. Clin J Am Soc Nephrol. 2008;3:193-199.  [PubMed]  [DOI]  [Cited in This Article: ]
57.  Rossert J. Erythropoietin-induced, antibody-mediated pure red cell aplasia. Eur J Clin Invest. 2005;35 Suppl 3:95-99.  [PubMed]  [DOI]  [Cited in This Article: ]
58.  Wight J, Paisley S. The epidemiology of inhibitors in haemophilia A: a systematic review. Haemophilia. 2003;9:418-435.  [PubMed]  [DOI]  [Cited in This Article: ]
59.  Schifferli JA, Taylor RP. Physiological and pathological aspects of circulating immune complexes. Kidney Int. 1989;35:993-1003.  [PubMed]  [DOI]  [Cited in This Article: ]
60.  Emlen W, Carl V, Burdick G. Mechanism of transfer of immune complexes from red blood cell CR1 to monocytes. Clin Exp Immunol. 1992;89:8-17.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 27]  [Cited by in F6Publishing: 36]  [Article Influence: 1.1]  [Reference Citation Analysis (0)]
61.  Johansson A, Erlandsson A, Eriksson D, Ullén A, Holm P, Sundström BE, Roux KH, Stigbrand T. Idiotypic-anti-idiotypic complexes and their in vivo metabolism. Cancer. 2002;94:1306-1313.  [PubMed]  [DOI]  [Cited in This Article: ]
62.  Kosugi I, Muro H, Shirasawa H, Ito I. Endocytosis of soluble IgG immune complex and its transport to lysosomes in hepatic sinusoidal endothelial cells. J Hepatol. 1992;16:106-114.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 40]  [Cited by in F6Publishing: 38]  [Article Influence: 1.2]  [Reference Citation Analysis (0)]
63.  Pastuskovas CV, Mallet W, Clark S, Kenrick M, Majidy M, Schweiger M, Van Hoy M, Tsai SP, Bennett G, Shen BQ. Effect of immune complex formation on the distribution of a novel antibody to the ovarian tumor antigen CA125. Drug Metab Dispos. 2010;38:2309-2319.  [PubMed]  [DOI]  [Cited in This Article: ]
64.  Solá RJ, Griebenow K. Glycosylation of therapeutic proteins: an effective strategy to optimize efficacy. BioDrugs. 2010;24:9-21.  [PubMed]  [DOI]  [Cited in This Article: ]
65.  Li H, d'Anjou M. Pharmacological significance of glycosylation in therapeutic proteins. Curr Opin Biotechnol. 2009;20:678-684.  [PubMed]  [DOI]  [Cited in This Article: ]
66.  Bongartz T, Sutton AJ, Sweeting MJ, Buchan I, Matteson EL, Montori V. Anti-TNF antibody therapy in rheumatoid arthritis and the risk of serious infections and malignancies: systematic review and meta-analysis of rare harmful effects in randomized controlled trials. JAMA. 2006;295:2275-2285.  [PubMed]  [DOI]  [Cited in This Article: ]
67.  Cooper N, Arnold DM. The effect of rituximab on humoral and cell mediated immunity and infection in the treatment of autoimmune diseases. Br J Haematol. 2010;149:3-13.  [PubMed]  [DOI]  [Cited in This Article: ]
68.  Curtis JR, Patkar N, Xie A, Martin C, Allison JJ, Saag M, Shatin D, Saag KG. Risk of serious bacterial infections among rheumatoid arthritis patients exposed to tumor necrosis factor alpha antagonists. Arthritis Rheum. 2007;56:1125-1133.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 276]  [Cited by in F6Publishing: 268]  [Article Influence: 15.8]  [Reference Citation Analysis (0)]
69.  Curtis JR, Xie F, Chen L, Baddley JW, Beukelman T, Saag KG, Spettell C, McMahan RM, Fernandes J, Winthrop K. The comparative risk of serious infections among rheumatoid arthritis patients starting or switching biological agents. Ann Rheum Dis. 2011;70:1401-1406.  [PubMed]  [DOI]  [Cited in This Article: ]
70.  Mufti AH, Toye BW, Mckendry RR, Angel JB. Mycobacterium abscessus infection after use of tumor necrosis factor alpha inhibitor therapy: case report and review of infectious complications associated with tumor necrosis factor alpha inhibitor use. Diagn Microbiol Infect Dis. 2005;53:233-238.  [PubMed]  [DOI]  [Cited in This Article: ]
71.  Grijalva CG, Chen L, Delzell E, Baddley JW, Beukelman T, Winthrop KL, Griffin MR, Herrinton LJ, Liu L, Ouellet-Hellstrom R. Initiation of tumor necrosis factor-α antagonists and the risk of hospitalization for infection in patients with autoimmune diseases. JAMA. 2011;306:2331-2339.  [PubMed]  [DOI]  [Cited in This Article: ]
72.  European Medicines Agency (EMA) Epoetin delta review. European Public Assessment Report (Scientific Discussion). 2004; Available from: http//  [PubMed]  [DOI]  [Cited in This Article: ]
73.  Lippi G, Franchini M, Favaloro EJ. Thrombotic complications of erythropoiesis-stimulating agents. Semin Thromb Hemost. 2010;36:537-549.  [PubMed]  [DOI]  [Cited in This Article: ]
74.  International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) S6 Preclinical Safety Evaluation of Biotechnology-Derived Pharmaceuticals. 1997; Available from: http//  [PubMed]  [DOI]  [Cited in This Article: ]
75.  International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) S6(R1) Preclinical Safety Evaluation of Biotechnology-Derived Pharmaceuticals. 2011; Available from: http//  [PubMed]  [DOI]  [Cited in This Article: ]
76.  Leach MW, Halpern WG, Johnson CW, Rojko JL, MacLachlan TK, Chan CM, Galbreath EJ, Ndifor AM, Blanset DL, Polack E. Use of tissue cross-reactivity studies in the development of antibody-based biopharmaceuticals: history, experience, methodology, and future directions. Toxicol Pathol. 2010;38:1138-1166.  [PubMed]  [DOI]  [Cited in This Article: ]
77.  US Food and Drug Administration (FDA). Guidance for industry: Estimating the maximum safe starting dose in initial clinical trials for therapeutics in adult healthy volunteers. 2005; Available from: http//  [PubMed]  [DOI]  [Cited in This Article: ]
78.  Horvath CJ, Milton MN. The TeGenero incident and the Duff Report conclusions: a series of unfortunate events or an avoidable event? Toxicol Pathol. 2009;37:372-383.  [PubMed]  [DOI]  [Cited in This Article: ]
79.  Stebbings R, Findlay L, Edwards C, Eastwood D, Bird C, North D, Mistry Y, Dilger P, Liefooghe E, Cludts I. "Cytokine storm" in the phase I trial of monoclonal antibody TGN1412: better understanding the causes to improve preclinical testing of immunotherapeutics. J Immunol. 2007;179:3325-3331.  [PubMed]  [DOI]  [Cited in This Article: ]
80.  Stebbings R, Poole S, Thorpe R. Safety of biologics, lessons learnt from TGN1412. Curr Opin Biotechnol. 2009;20:673-677.  [PubMed]  [DOI]  [Cited in This Article: ]
81.  81 Department of Health, UK. Expert Group on Phase One Clinical Trials: Final report. 2006; Available from: http//  [PubMed]  [DOI]  [Cited in This Article: ]
82.  Muller PY, Milton M, Lloyd P, Sims J, Brennan FR. The minimum anticipated biological effect level (MABEL) for selection of first human dose in clinical trials with monoclonal antibodies. Curr Opin Biotechnol. 2009;20:722-729.  [PubMed]  [DOI]  [Cited in This Article: ]
83.  International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) S9 Nonclinical Evaluation for Anticancer Pharmaceuticals. 2009; Available from: http//  [PubMed]  [DOI]  [Cited in This Article: ]
84.  Stewart J. Developmental toxicity testing of monoclonal antibodies: an enhanced pre- and postnatal study design option. Reprod Toxicol. 2009;28:220-225.  [PubMed]  [DOI]  [Cited in This Article: ]
85.  Gorovits B. Antidrug antibody assay validation: industry survey results. AAPS J. 2009;11:133-138.  [PubMed]  [DOI]  [Cited in This Article: ]
86.  Swann PG, Shapiro MA. Regulatory considerations for development of bioanalytical assays for biotechnology products. Bioanalysis. 2011;3:597-603.  [PubMed]  [DOI]  [Cited in This Article: ]
87.  Buxton DB, Antman M, Danthi N, Dilsizian V, Fayad ZA, Garcia MJ, Jaff MR, Klimas M, Libby P, Nahrendorf M. Report of the National Heart, Lung, and Blood Institute working group on the translation of cardiovascular molecular imaging. Circulation. 2011;123:2157-2163.  [PubMed]  [DOI]  [Cited in This Article: ]
88.  Palframan R, Airey M, Moore A, Vugler A, Nesbitt A. Use of biofluorescence imaging to compare the distribution of certolizumab pegol, adalimumab, and infliximab in the inflamed paws of mice with collagen-induced arthritis. J Immunol Methods. 2009;348:36-41.  [PubMed]  [DOI]  [Cited in This Article: ]
89.  Keck R, Nayak N, Lerner L, Raju S, Ma S, Schreitmueller T, Chamow S, Moorhouse K, Kotts C, Jones A. Characterization of a complex glycoprotein whose variable metabolic clearance in humans is dependent on terminal N-acetylglucosamine content. Biologicals. 2008;36:49-60.  [PubMed]  [DOI]  [Cited in This Article: ]
90.  Meier W, Gill A, Rogge M, Dabora R, Majeau GR, Oleson FB, Jones WE, Frazier D, Miatkowski K, Hochman PS. Immunomodulation by LFA3TIP, an LFA-3/IgG1 fusion protein: cell line dependent glycosylation effects on pharmacokinetics and pharmacodynamic markers. Ther Immunol. 1995;2:159-171.  [PubMed]  [DOI]  [Cited in This Article: ]
91.  Stork R, Zettlitz KA, Müller D, Rether M, Hanisch FG, Kontermann RE. N-glycosylation as novel strategy to improve pharmacokinetic properties of bispecific single-chain diabodies. J Biol Chem. 2008;283:7804-7812.  [PubMed]  [DOI]  [Cited in This Article: ]
92.  Pan S, Aebersold R, Chen R, Rush J, Goodlett DR, McIntosh MW, Zhang J, Brentnall TA. Mass spectrometry based targeted protein quantification: methods and applications. J Proteome Res. 2009;8:787-797.  [PubMed]  [DOI]  [Cited in This Article: ]
93.  Tremblay GA, Oldfield PR. Bioanalysis of siRNA and oligonucleotide therapeutics in biological fluids and tissues. Bioanalysis. 2009;1:595-609.  [PubMed]  [DOI]  [Cited in This Article: ]
94.  Bumbaca D, Wong A, Drake E, Reyes AE, Lin BC, Stephan JP, Desnoyers L, Shen BQ, Dennis MS. Highly specific off-target binding identified and eliminated during the humanization of an antibody against FGF receptor 4. MAbs. 2011;3:376-386.  [PubMed]  [DOI]  [Cited in This Article: ]
95.  Vugmeyster Y, Allen S, Szklut P, Bree A, Ryan M, Ma M, Spaulding V, Young D, Guay H, Bloom L. Correlation of pharmacodynamic activity, pharmacokinetics, and anti-product antibody responses to anti-IL-21R antibody therapeutics following IV administration to cynomolgus monkeys. J Transl Med. 2010;8:41.  [PubMed]  [DOI]  [Cited in This Article: ]
96.  Vugmeyster Y, Guay H, Szklut P, Qian MD, Jin M, Widom A, Spaulding V, Bennett F, Lowe L, Andreyeva T. In vitro potency, pharmacokinetic profiles, and pharmacological activity of optimized anti-IL-21R antibodies in a mouse model of lupus. MAbs. 2010;2:335-346.  [PubMed]  [DOI]  [Cited in This Article: ]
97.  Wu H, Pfarr DS, Johnson S, Brewah YA, Woods RM, Patel NK, White WI, Young JF, Kiener PA. Development of motavizumab, an ultra-potent antibody for the prevention of respiratory syncytial virus infection in the upper and lower respiratory tract. J Mol Biol. 2007;368:652-665.  [PubMed]  [DOI]  [Cited in This Article: ]
98.  Boswell CA, Tesar DB, Mukhyala K, Theil FP, Fielder PJ, Khawli LA. Effects of charge on antibody tissue distribution and pharmacokinetics. Bioconjug Chem. 2010;21:2153-2163.  [PubMed]  [DOI]  [Cited in This Article: ]
99.  Hong G, Bazin-Redureau MI, Scherrmann JM. Pharmacokinetics and organ distribution of cationized colchicine-specific IgG and Fab fragments in rat. J Pharm Sci. 1999;88:147-153.  [PubMed]  [DOI]  [Cited in This Article: ]
100.  Igawa T, Tsunoda H, Tachibana T, Maeda A, Mimoto F, Moriyama C, Nanami M, Sekimori Y, Nabuchi Y, Aso Y. Reduced elimination of IgG antibodies by engineering the variable region. Protein Eng Des Sel. 2010;23:385-392.  [PubMed]  [DOI]  [Cited in This Article: ]
101.  Kobayashi H, Le N, Kim IS, Kim MK, Pie JE, Drumm D, Paik DS, Waldmann TA, Paik CH, Carrasquillo JA. The pharmacokinetic characteristics of glycolated humanized anti-Tac Fabs are determined by their isoelectric points. Cancer Res. 1999;59:422-430.  [PubMed]  [DOI]  [Cited in This Article: ]
102.  Wang W, Wang EQ, Balthasar JP. Monoclonal antibody pharmacokinetics and pharmacodynamics. Clin Pharmacol Ther. 2008;84:548-558.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 715]  [Cited by in F6Publishing: 716]  [Article Influence: 44.8]  [Reference Citation Analysis (0)]
103.  Dickinson BL, Badizadegan K, Wu Z, Ahouse JC, Zhu X, Simister NE, Blumberg RS, Lencer WI. Bidirectional FcRn-dependent IgG transport in a polarized human intestinal epithelial cell line. J Clin Invest. 1999;104:903-911.  [PubMed]  [DOI]  [Cited in This Article: ]
104.  Ferl GZ, Wu AM, DiStefano JJ. A predictive model of therapeutic monoclonal antibody dynamics and regulation by the neonatal Fc receptor (FcRn). Ann Biomed Eng. 2005;33:1640-1652.  [PubMed]  [DOI]  [Cited in This Article: ]
105.  Garg A, Balthasar JP. Physiologically-based pharmacokinetic (PBPK) model to predict IgG tissue kinetics in wild-type and FcRn-knockout mice. J Pharmacokinet Pharmacodyn. 2007;34:687-709.  [PubMed]  [DOI]  [Cited in This Article: ]
106.  Vaccaro C, Zhou J, Ober RJ, Ward ES. Engineering the Fc region of immunoglobulin G to modulate in vivo antibody levels. Nat Biotechnol. 2005;23:1283-1288.  [PubMed]  [DOI]  [Cited in This Article: ]
107.  Wang W, Lu P, Fang Y, Hamuro L, Pittman T, Carr B, Hochman J, Prueksaritanont T. Monoclonal antibodies with identical Fc sequences can bind to FcRn differentially with pharmacokinetic consequences. Drug Metab Dispos. 2011;39:1469-1477.  [PubMed]  [DOI]  [Cited in This Article: ]
108.  Suzuki T, Ishii-Watabe A, Tada M, Kobayashi T, Kanayasu-Toyoda T, Kawanishi T, Yamaguchi T. Importance of neonatal FcR in regulating the serum half-life of therapeutic proteins containing the Fc domain of human IgG1: a comparative study of the affinity of monoclonal antibodies and Fc-fusion proteins to human neonatal FcR. J Immunol. 2010;184:1968-1976.  [PubMed]  [DOI]  [Cited in This Article: ]
109.  Zheng Y, Scheerens H, Davis JC, Deng R, Fischer SK, Woods C, Fielder PJ, Stefanich EG. Translational pharmacokinetics and pharmacodynamics of an FcRn-variant anti-CD4 monoclonal antibody from preclinical model to phase I study. Clin Pharmacol Ther. 2011;89:283-290.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 37]  [Cited by in F6Publishing: 38]  [Article Influence: 2.7]  [Reference Citation Analysis (0)]
110.  Tang L, Persky AM, Hochhaus G, Meibohm B. Pharmacokinetic aspects of biotechnology products. J Pharm Sci. 2004;93:2184-2204.  [PubMed]  [DOI]  [Cited in This Article: ]
111.  Charman SA, Segrave AM, Edwards GA, Porter CJ. Systemic availability and lymphatic transport of human growth hormone administered by subcutaneous injection. J Pharm Sci. 2000;89:168-177.  [PubMed]  [DOI]  [Cited in This Article: ]
112.  Supersaxo A, Hein WR, Steffen H. Effect of molecular weight on the lymphatic absorption of water-soluble compounds following subcutaneous administration. Pharm Res. 1990;7:167-169.  [PubMed]  [DOI]  [Cited in This Article: ]
113.  Bocci V, Muscettola M, Grasso G, Magyar Z, Naldini A, Szabo G. The lymphatic route. 1) Albumin and hyaluronidase modify the normal distribution of interferon in lymph and plasma. Experientia. 1986;42:432-433.  [PubMed]  [DOI]  [Cited in This Article: ]
114.  Kojima K, Takahashi T, Nakanishi Y. Lymphatic transport of recombinant human tumor necrosis factor in rats. J Pharmacobiodyn. 1988;11:700-706.  [PubMed]  [DOI]  [Cited in This Article: ]
115.  Kaneko E, Niwa R. Optimizing therapeutic antibody function: progress with Fc domain engineering. BioDrugs. 2011;25:1-11.  [PubMed]  [DOI]  [Cited in This Article: ]
116.  Shinkawa T, Nakamura K, Yamane N, Shoji-Hosaka E, Kanda Y, Sakurada M, Uchida K, Anazawa H, Satoh M, Yamasaki M. The absence of fucose but not the presence of galactose or bisecting N-acetylglucosamine of human IgG1 complex-type oligosaccharides shows the critical role of enhancing antibody-dependent cellular cytotoxicity. J Biol Chem. 2003;278:3466-3473.  [PubMed]  [DOI]  [Cited in This Article: ]
117.  Hodoniczky J, Zheng YZ, James DC. Control of recombinant monoclonal antibody effector functions by Fc N-glycan remodeling in vitro. Biotechnol Prog. 2005;21:1644-1652.  [PubMed]  [DOI]  [Cited in This Article: ]
118.  Tao MH, Morrison SL. Studies of aglycosylated chimeric mouse-human IgG. Role of carbohydrate in the structure and effector functions mediated by the human IgG constant region. J Immunol. 1989;143:2595-2601.  [PubMed]  [DOI]  [Cited in This Article: ]
119.  Goetze AM, Liu YD, Zhang Z, Shah B, Lee E, Bondarenko PV, Flynn GC. High-mannose glycans on the Fc region of therapeutic IgG antibodies increase serum clearance in humans. Glycobiology. 2011;21:949-959.  [PubMed]  [DOI]  [Cited in This Article: ]
120.  Junttila TT, Parsons K, Olsson C, Lu Y, Xin Y, Theriault J, Crocker L, Pabonan O, Baginski T, Meng G. Superior in vivo efficacy of afucosylated trastuzumab in the treatment of HER2-amplified breast cancer. Cancer Res. 2010;70:4481-4489.  [PubMed]  [DOI]  [Cited in This Article: ]
121.  Liu L, Stadheim A, Hamuro L, Pittman T, Wang W, Zha D, Hochman J, Prueksaritanont T. Pharmacokinetics of IgG1 monoclonal antibodies produced in humanized Pichia pastoris with specific glycoforms: a comparative study with CHO produced materials. Biologicals. 2011;39:205-210.  [PubMed]  [DOI]  [Cited in This Article: ]
122.  Harris RJ. Heterogeneity of recombinant antibodies: linking structure to function. Dev Biol (. Basel). 2005;122:117-127.  [PubMed]  [DOI]  [Cited in This Article: ]
123.  Millward TA, Heitzmann M, Bill K, Längle U, Schumacher P, Forrer K. Effect of constant and variable domain glycosylation on pharmacokinetics of therapeutic antibodies in mice. Biologicals. 2008;36:41-47.  [PubMed]  [DOI]  [Cited in This Article: ]
124.  Kabat EA, Wu TT, Perry HM, Gottesman KS, Foeller C.  Sequences of proteins of immunological interest. 5th ed. Bethesda, MD: US Department of Health and Human Services, Public Health Service, National Institutes of Health 1991; .  [PubMed]  [DOI]  [Cited in This Article: ]
125.  Wright A, Tao MH, Kabat EA, Morrison SL. Antibody variable region glycosylation: position effects on antigen binding and carbohydrate structure. EMBO J. 1991;10:2717-2723.  [PubMed]  [DOI]  [Cited in This Article: ]
126.  Stefanich EG, Ren S, Danilenko DM, Lim A, Song A, Iyer S, Fielder PJ. Evidence for an asialoglycoprotein receptor on nonparenchymal cells for O-linked glycoproteins. J Pharmacol Exp Ther. 2008;327:308-315.  [PubMed]  [DOI]  [Cited in This Article: ]
127.  Briggs DW, Fisher JW, George WJ. Hepatic clearance of intact and desialylated erythropoietin. Am J Physiol. 1974;227:1385-1388.  [PubMed]  [DOI]  [Cited in This Article: ]
128.  Morell AG, Gregoriadis G, Scheinberg IH, Hickman J, Ashwell G. The role of sialic acid in determining the survival of glycoproteins in the circulation. J Biol Chem. 1971;246:1461-1467.  [PubMed]  [DOI]  [Cited in This Article: ]
129.  Gregoriadis G, Fernandes A, Mital M, McCormack B. Polysialic acids: potential in improving the stability and pharmacokinetics of proteins and other therapeutics. Cell Mol Life Sci. 2000;57:1964-1969.  [PubMed]  [DOI]  [Cited in This Article: ]
130.  Bailon P, Won CY. PEG-modified biopharmaceuticals. Expert Opin Drug Deliv. 2009;6:1-16.  [PubMed]  [DOI]  [Cited in This Article: ]
131.  Rojas JR, Taylor RP, Cunningham MR, Rutkoski TJ, Vennarini J, Jang H, Graham MA, Geboes K, Rousselle SD, Wagner CL. Formation, distribution, and elimination of infliximab and anti-infliximab immune complexes in cynomolgus monkeys. J Pharmacol Exp Ther. 2005;313:578-585.  [PubMed]  [DOI]  [Cited in This Article: ]
132.  Sharkey RM, Blumenthal RD, Goldenberg DM. Anti-antibody enhancement of tumor imaging. Cancer Treat Res. 1990;51:433-455.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 7]  [Article Influence: 0.2]  [Reference Citation Analysis (0)]
133.  Eastwood D, Findlay L, Poole S, Bird C, Wadhwa M, Moore M, Burns C, Thorpe R, Stebbings R. Monoclonal antibody TGN1412 trial failure explained by species differences in CD28 expression on CD4+ effector memory T-cells. Br J Pharmacol. 2010;161:512-526.  [PubMed]  [DOI]  [Cited in This Article: ]
134.  Pallardy M, Hünig T. Primate testing of TGN1412: right target, wrong cell. Br J Pharmacol. 2010;161:509-511.  [PubMed]  [DOI]  [Cited in This Article: ]
135.  Bussiere JL, Martin P, Horner M, Couch J, Flaherty M, Andrews L, Beyer J, Horvath C. Alternative strategies for toxicity testing of species-specific biopharmaceuticals. Int J Toxicol. 2009;28:230-253.  [PubMed]  [DOI]  [Cited in This Article: ]
136.  Bugelski PJ, Treacy G. Predictive power of preclinical studies in animals for the immunogenicity of recombinant therapeutic proteins in humans. Curr Opin Mol Ther. 2004;6:10-16.  [PubMed]  [DOI]  [Cited in This Article: ]
137.  Alpers CE. The Kidney. Pathologic Basis of Disease, Professional Edition. 8th ed. Philadelphia, PA: Saunders Elsevier 2009; .  [PubMed]  [DOI]  [Cited in This Article: ]
138.  Hebert LA, Birmingham DJ, Shen XP, Cosio FG, Fryczkowski A. Rate of antigen entry into the circulation in experimental versus naturally occurring immune complex glomerulonephritis. J Am Soc Nephrol. 1994;5:S70-S75.  [PubMed]  [DOI]  [Cited in This Article: ]
139.  Hebert LA, Cosio FG, Birmingham DJ, Mahan JD, Sharma HM, Smead WL, Goel R. Experimental immune complex-mediated glomerulonephritis in the nonhuman primate. Kidney Int. 1991;39:44-56.  [PubMed]  [DOI]  [Cited in This Article: ]
140.  Nangaku M, Couser WG. Mechanisms of immune-deposit formation and the mediation of immune renal injury. Clin Exp Nephrol. 2005;9:183-191.  [PubMed]  [DOI]  [Cited in This Article: ]
141.  Hutto DL. Opportunistic infections in non-human primates exposed to immunomodulatory biotherapeutics: considerations and case examples. J Immunotoxicol. 2010;7:120-127.  [PubMed]  [DOI]  [Cited in This Article: ]
142.  Sasseville VG, Diters RW. Impact of infections and normal flora in nonhuman primates on drug development. ILAR J. 2008;49:179-190.  [PubMed]  [DOI]  [Cited in This Article: ]
143.  Sasseville VG, Mansfield KG. Overview of known non-human primate pathogens with potential to affect colonies used for toxicity testing. J Immunotoxicol. 2010;7:79-92.  [PubMed]  [DOI]  [Cited in This Article: ]
144.  International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) M3(R2) Guidance on nonclinical safety studies for the conduct of human clinical trials and marketing authorization for pharmaceuticals. 2009; Available from: http//  [PubMed]  [DOI]  [Cited in This Article: ]
145.  Cappon GD, Bailey GP, Buschmann J, Feuston MH, Fisher JE, Hew KW, Hoberman AM, Ooshima Y, Stump DG, Hurtt ME. Juvenile animal toxicity study designs to support pediatric drug development. Birth Defects Res B Dev Reprod Toxicol. 2009;86:463-469.  [PubMed]  [DOI]  [Cited in This Article: ]
146.  Chellman GJ, Bussiere JL, Makori N, Martin PL, Ooshima Y, Weinbauer GF. Developmental and reproductive toxicology studies in nonhuman primates. Birth Defects Res B Dev Reprod Toxicol. 2009;86:446-462.  [PubMed]  [DOI]  [Cited in This Article: ]
147.  Dranitsaris G, Amir E, Dorward K. Biosimilars of biological drug therapies: regulatory, clinical and commercial considerations. Drugs. 2011;71:1527-1536.  [PubMed]  [DOI]  [Cited in This Article: ]
148.  Ledford H. 'Biosimilar' drugs poised to penetrate market. Nature. 2010;468:18-19.  [PubMed]  [DOI]  [Cited in This Article: ]
149.  European Medicines Agency (EMA) Guideline on similar biological medicinal products. 2005; Available from: http//  [PubMed]  [DOI]  [Cited in This Article: ]
150.  European Medicines Agency (EMA) Guideline on similar biological medicinal products containing monoclonal antibodies (Draft). 2010; Available from: http//  [PubMed]  [DOI]  [Cited in This Article: ]
151.  World Health Organizaion (WHO) Guidelines on evaluation of similar Biotherapeutic Products (SBPs). 2005; Available from: http//  [PubMed]  [DOI]  [Cited in This Article: ]
152.  Kozlowski S, Woodcock J, Midthun K, Sherman RB. Developing the nation's biosimilars program. N Engl J Med. 2011;365:385-388.  [PubMed]  [DOI]  [Cited in This Article: ]