Monoclonal Antibodies: From Structure to Therapeutic Application

Monoclonal Antibodies for Cancer Immunotherapy

Keywords

Introduction

The exciting field of therapeutic monoclonal antibodies (MABs) had its origins when Köhler and Milstein presented their murine hybridoma technology in 1975 (Kohler and Milstein 1975). This technology provides a reproducible method for producing MABs with unique target selectivity in almost unlimited quantities. In 1984, both scientists received the Nobel Prize for their scientific breakthrough, and their work is viewed as a key milestone in the history of MABs as therapeutic modalities and their other applications. Although it took some time until the first therapeutic MAB received FDA approval in 1986 (Orthoclone OKT3, Chap. 25), MABs are now the standard of care in several disease areas. In particular, in oncology (Chap. 23), transplantation (Chap. 25), and inflammatory diseases (Chap. 26), patients now have novel life-changing treatment alternatives for diseases that had very limited or nonexistent medical treatment options before the emergence of MABs. Today, more than 75 MABs and MAB derivatives, including fusion proteins and MAB fragments, are available for a variety of indications (Table 8.1). The majority of approved biologic therapies are MABs, antibody-drug conjugates (ADCs), antibody fragments, and Fc fusion proteins. Technological evolutions have subsequently allowed much wider application of MABs thanks to the ability to generate mouse/human chimeric, humanized, and fully human MABs from antibodies (Abs) of pure murine origin. In particular, the reduction of the xenogenic portion of the MAB structure decreased the immunogenic potential of murine MABs, allowing their wider application. MABs are generally well-tolerated drugs because of their target selectivity, thus avoiding unnecessary exposure to, and consequently activity in, nontarget organs. This is particularly apparent in the field of oncology where MABs such as rituximab, trastuzumab, bevacizumab, cetuximab and immune-oncology MABs such as atezolizumab, pembrolizumab and nivolumab can offer a more favorable risk-benefit profile compared to common chemotherapeutic treatment regimens for some hematologic cancers and solid tumors.

Table 8.1 Therapeutic biologics (monoclonal antibodies, antibody fragments, fusion proteins and antibody-drug conjugates)^a

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The advent of MABs not only resulted in new drugs, but also triggered the development of an entirely new business model for drug research and development and the founding of hundreds of biotech companies focused on MAB development. Furthermore, the ability to selectively target disease-related molecules with MABs helped to launch a new era of targeted medicine and set new standards for successful drug research and development. The term translational medicine was coined to describe the use of biochemical, biological, and (patho)physiological understanding to find novel interventions to treat disease. During this process, biomarkers (e.g., genetic expression levels of marker genes, protein expression of target proteins, or molecular imaging) can be used to gain deeper understanding of the biological activities of drugs in a qualitative and, most importantly, quantitative sense, essentially encompassing the entire field of pharmacokinetics and pharmacodynamics (PK/PD) . The application of these scientific methods, together with the principle of molecular-targeted medicine and the favorable PK and safety of MABs, may at least partly explain the higher success rates of biotechnologically derived products in reaching the market compared to chemically derived small molecule drugs.

This chapter addresses the following topics: Antibody structure and classes, currently approved MAB based therapeutics, mechanisms of action, clinical development and drug properties. In this sense, this chapter provides a general introduction to Chaps. 23, 25, and 26, where the currently marketed MABs and MAB derivatives including antibody fragments, fusion proteins and ADCs are discussed in the context of their therapeutic applications. Efalizumab (anti-CD11a), a MAB marketed as an anti-psoriasis drug in the US and EU, was chosen to illustrate the application of PK/PD principles in the drug development process.

Antibody Structure and Classes

Antibodies , or immunoglobulins (Igs) , are roughly Y-shaped molecules or combinations of such molecules. There are five major classes of Ig: IgG , IgA , IgD , IgE , and IgM . Table 8.2 summarizes the characteristics of these molecules, particularly their structure (monomer, dimer, hexamer, or pentamer), molecular weight (ranging from ~150 to ~1150 kDa), and functions (e.g., activate complement, FcγR binding). Among these classes, IgGs and their derivatives form the framework for the development of therapeutic antibodies. Figure 8.1 depicts the general structural components of IgG and a conformational structure of efalizumab. An IgG molecule has four peptide chains, including two identical heavy (H) chains (50–55 kDa) and two identical light (L) chains (25 kDa), which are linked via disulfide (S–S) bonds at the hinge region. The first ~110 amino acids of both chains form the variable regions (V _H and V _L) and are also the antigen-binding regions. Each V domain contains three short stretches of peptide with hypervariable sequences (HV1, HV2, and HV3), known as complementarity determining regions (CDRs) , i.e., the region that binds antigen. The remaining sequences of each light chain consist of a single constant domain (C _L). The remainder of each heavy chain contains three constant regions (C_H1, C_H2, and C_H3). Constant regions are responsible for effector recognition and binding. IgGs can be further divided into four subclasses (IgG1, IgG2, IgG3, and IgG4). The differences among these subclasses are also summarized in Table 8.2.

Table 8.2 Important properties of endogenous immunoglobulin subclass (Goldsby et al. 1999; Kolar and Capra 2003)

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■ Murine, Chimeric, Humanized, and Fully Human MABs

The first therapeutic MABs were murine MABs produced via hybridomas; however, these murine MABs easily elicited formation of neutralizing human anti-mouse antibodies (HAMA) (Kuus-Reichel et al. 1994). With the advancement of technology, murine MABs have been engineered further to chimeric (mouse CDR, human Fc), humanized, and fully human MABs (Fig. 8.2). Murine MABs, chimeric MABs , humanized MABs , and fully human MABs have 0%, ~60–70%, ~90–95%, and ~100% sequence similarity to human MABs, respectively. Decreasing the xenogenic portion of the MAB potentially reduces the immunogenic risks of generating anti-drug antibodies (ADAs) . Muromonab-CD3 (Orthoclone OKT3), a first-generation MAB of murine origin, has shown efficacy in the treatment of acute transplant rejection and was the first MAB licensed for use in humans. It is reported that 50% of the patients who received OKT3 produced HAMA after the first dose. HAMA interfered with OKT3’s binding to T cells, thus decreasing the therapeutic efficacy of the MAB (Norman et al. 1993). Later, molecular cloning and the expression of the variable region genes of IgGs facilitated the generation of engineered antibodies. A second generation of MABs, chimeric MABs, consists of human constant regions and mouse variable regions. The antigen specificity of a chimeric MAB is the same as the parental mouse antibody; however, the human Fc region renders a longer in vivo half-life than the parent murine MAB, and similar effector functions as a human antibody. Currently, there are 9 chimeric MABs, fragments and ADCs on the market (abciximab, basiliximab, cetuximab, dinutuximab, infliximab, obiltoxaximab, rituximab, siltuximab, and brentuximab vedotin). These MABs can still induce human anti-chimeric antibodies (HACA). For example, about 61% of patients who received infliximab had a HACA response associated with shorter duration of therapeutic efficacy and increased risk of infusion reactions (Baert et al. 2003). The development of ADAs appears to be different across indications. For example, 6 of 17 patients with systemic lupus erythematosus receiving rituximab developed high-titer HACA (Looney et al. 2004), whereas only 1 of 166 B cell depleted lymphoma patients developed HACA (McLaughlin et al. 1998). Humanized MABs contain significant portions of human sequence except the CDR which is still of murine origin. There are more than 25 humanized MABs (including ADCs) on the market (see Table 8.1). The incidence of ADAs (in this case, human anti-human antibodies or HAHAs), was greatly decreased for these humanized MABs. Trastuzumab has a reported a HAHA incidence of ~0.1% (1 of 903 cases) (Herceptin (Trastuzumab) Prescribing Information 2006), but daclizumab had HAHA rate as high as 34% (Zenapax (Daclizumab) Prescribing Information 2005). Another way to achieve full biocompatibility of MABs is to develop fully human antibodies, which can be produced by two approaches: through phage-display library or by using transgenic animals, such as the XenoMouse^® or Trianni Mouse™ (Weiner 2006; Trianni.com 2018). Adalimumab is the first licensed fully human MAB generated using a phage-display library. Adalimumab was approved in 2002 and 2007 for the treatment of rheumatoid arthritis (RA) and Crohn’s diseases, respectively (Humira (Adalimumab) Prescribing Information 2007). However, despite its fully human antibody structure, the incidence of HAHA was about 5% (58 of 1062 patients) in three randomized clinical trials with adalimumab (Cohenuram and Saif 2007; Humira (Adalimumab) Prescribing Information 2007). Panitumumab is the first approved fully human MAB generated using transgenic mouse technology. HAHA responses have been reported as less than 1% by an acid dissociation bridging enzyme-linked immunosorbent assay (ELISA) in clinical trial after chronic dosing with panitumumab to date (Vectibix (Panitumumab) Prescribing Information 2015; Cohenuram and Saif 2007). Of note, typically ADAs are measured using ELISA, and the reported incidence rates of ADAs for a given MAB can be influenced by the sensitivity and specificity of the assay. Additionally, the observed incidence of ADA positivity in an assay may also be influenced by several other factors, including sample handling, timing of sample collection, concomitant medications, and underlying disease. For these reasons, comparison of the incidence of ADAs to a specific MAB with the incidence of ADAs to another product may be misleading.

■ Key Structural Components of MABs

Proteolytic digestion of antibodies releases different fragments termed Fv (fragment variable ), Fab (fragment antigen binding ), and Fc (fragment crystallization ) [reviewed by Wang et al. (2007)]. These fragments can also be generated by recombinant engineering. Treatment with papain generates two identical Fab’s and one Fc. Pepsin treatment generates a F(ab’)2 and several smaller fragments. Reduction of F(ab’)2 will produce two Fab fragments. The Fv consists of the heavy chain variable domain (V _H) and the light chain variable domain (V _L) held together by strong noncovalent interaction. Stabilization of the Fv by a peptide linker generates a single chain Fv (scFv) .

■ Modifying Fc Structures

The Fc regions of MABs play a critical role not only in their function but also in their disposition in the body. MABs elicit effector functions, including antibody-dependent cellular cytotoxicity (ADCC) , antibody-dependent cellular phagocytosis (ADCP) and complement-dependent cytotoxicity (CDC) , following interaction between their Fc regions and different Fcγ receptors and complement fixation (C1q, C3b). The CH2 domain and the hinge region joining CH1 and CH2 have been identified as the crucial regions for binding to FcγR (Presta 2002; Presta et al. 2002). Engineered MABs with enhanced or decreased ADCC, ADCP and CDC activity have been produced by manipulation of the critical Fc regions. Umana et al. (1999) engineered an anti-neuroblastoma IgG1 with enhanced ADCC activity compared with wild type (WT). Shields et al. (2001) demonstrated that selected IgG1 variants with improved binding to FcγRIIIA showed enhanced ADCC by peripheral blood monocyte cells and natural killer cells. These findings indicate that Fc-engineered antibodies may have important applications for improving therapeutic efficacy. It was found that the FcγRIIIA gene dimorphism generates two allotypes, FcγRIIIa-158V and FcγRIIIa-158F, and the polymorphism in FcγRIIIA is associated with favorable clinical response following rituximab administration in non-Hodgkin’s lymphoma patients (Cartron et al. 2004; Dall’Ozzo et al. 2004). Recently, obinutuzumab, an anti-CD20 MAB with enhanced effector functions as compared to rituximab, was approved for the treatment of patients with previously untreated chronic lymphocytic leukemia (CLL) and patients with follicular lymphoma (FL) who relapsed after, or are refractory to, a rituximab-containing regimen. The efficacy of antibody-interleukin 2 fusion protein (Ab-IL2) was improved by reducing its interaction with Fc receptors (Gillies et al. 1999). In addition, the Fc portion of MABs also binds to FcRn (named based on its discovery in neonatal rats), an Fc receptor belonging to the major histocompatibility complex structure, which is involved in IgG transport and clearance (CL) (Junghans 1997). Engineered MABs with a decreased or increased FcRn binding affinity have been investigated for its potential to modify the pharmacokinetic behavior of MABs (see the section on Clearance for details).

■ Antibody Derivatives: F(ab’)2, Fab, Antibody-Drug Conjugates and Fusion Proteins

The fragments of antibodies [Fab, F(ab’)2, and scFv] have a shorter half-life compared with the corresponding full-sized antibodies. scFv can be further engineered into a dimer (diabody, ~60 kDa), or trimer (triabody, ~90 kDa). Two diabodies can be further linked together to generate a bispecific tandem diabody (tandab). A single Fab can be fused to a complete Fc engineered to form a single arm MAB, which is monovalent. Figure 8.3 illustrates the structure of different antibody fragments. Of note, abciximab, idarucizumab and ranibizumab are three Fabs approved by FDA. Abciximab is a chimeric Fab used for keeping blood from clotting that has a 20–30 min half-life in serum and 4-h half-life in platelets (Schror and Weber 2003). Ranibizumab, administrated via intravitreal injection, was approved for the treatment of macular degeneration in 2006 and exhibits a vitreous elimination half-life of 9 days (Albrecht and DeNardo 2006).

The half-life of Fc fragments is more similar to that of full-sized IgGs (Lobo et al. 2004). Therefore, Fc portions of IgGs have been used to form fusions with molecules such as cytokines, growth factor enzymes, or the ligand-binding region of receptor or adhesion molecules to improve their half-life and stability. There are ten Fc fusion proteins currently on the market [abatacept, aflibercept, alefacept, alprolix, antihemophilic factor (recombinant) Fc fusion protein, belatacept, dulaglutide, etanercept, rilonacept and ziv-aflibercept]. Etanercept, a dimeric fusion molecule consisting of the TNF-α receptor fused to the Fc region of human IgG1, has a half-life of approximately 70–100 h (Zhou 2005), which is much longer than that of the TNF-α receptor itself (30 min to ~2 h) (Watanabe et al. 1988).

Antibodies and antibody fragments can also be linked covalently with cytotoxic radionuclides or drugs to form radioimmunotherapeutic (RIT) agents or ADCs (Fig. 8.4), respectively. In each case, the antibody is used as a delivery mechanism to selectively target the cytotoxic moiety to tumors (Prabhu et al. 2011; Girish and Li 2015). For both ADCs and RIT agents, the therapeutic strategy involves selective delivery of a cytotoxin (drug or radionuclide) to tumors via the antibody. As targeted approaches, both technologies exploit the overexpression of target on the surface of the cancer cells and thereby minimize damage to normal tissues. Such approaches are anticipated to minimize the significant side effects encountered when cytotoxic small molecule drugs or radionuclides are administered as single agents, thus leading to enhanced therapeutic windows. However, important distinctions exist between these two therapeutic modalities. For example, ADCs usually require internalization into the endosomes and/or lysosomes for efficacy, while RIT agents are often able to emit beta or gamma radiation, even from the cell surface, to achieve cell killing following direct binding to membrane antigens. Furthermore, RIT can deliver high levels of radiation even with very low doses of radioimmunoconjugate. Importantly, most clinically successful ADC and RIT agents to date have been against hematologic tumors (Boswell and Brechbiel 2007). Trastuzumab emtansine is the only ADC approved in a solid tumor indication (LoRusso et al. 2011). Various impediments to the delivery of antibodies and other macromolecules to solid tumors have been widely discussed and studied, especially in the context of microspatial distribution (Thurber et al. 2008).

Currently, there are four ADCs on the market. Gemtuzumab ozogamicin (Dowell et al. 2001), an anti-CD33 MAB linked to the cytotoxic antitumor antibiotic drug calicheamicin, became the first approved ADC in 2000 when it was granted accelerated approval for the treatment of acute myelogenous leukemia. Calicheamicin binds to the minor groove of DNA, causing double-strand DNA breaks and resulting in inhibition of DNA synthesis. However, gemtuzumab ozogamicin was removed from the US market in June 2010 after subsequent confirmatory trials failed to verify clinical benefit and demonstrated safety concerns, including deaths. In September 2017, the FDA re-approved gemtuzumab ozogamicin with a lower recommended dose and a different schedule in combination with chemotherapy or on its own. Gemtuzumab ozogamicin’s history underscores the importance of examining alternative dosing, scheduling, and administration of therapies for patients with cancer, especially in those who may be most vulnerable to the side effects of treatment. In August 2011, the FDA approved a second ADC, brentuximab vedotin, a CD30-directed MAB linked to the cytotoxic microtubule-disrupting agent MMAE, for treatment of Hodgkin’s lymphoma and systemic anaplastic large-cell lymphoma. In February 2013, the FDA approved ado-trastuzumab emtansine, a human epidermal growth factor receptor (HER2)-targeted ADC for treatment of HER2-positive breast cancer (LoRusso et al. 2011). In August 2017, inotuzumab ozogamicin, a CD22-directed MAB linked to calicheamicin, was approved by FDA for the treatment of adults with relapsed or refractory B-cell precursor acute lymphoblastic leukemia.

The only current radioimmunotherapeutic agents licensed by the FDA are ibritumomab tiuxetan and tositumomab plus ¹³¹I-tositumomab, both for non-Hodgkin’s lymphoma. Both of the above intact murine MABs bind CD20 and carry a potent beta particle-emitting radioisotope (⁹⁰Y for ibritumomab/tiuxetan and ¹³¹I for tositumomab). In the case of ibritumomab, the bifunctional chelating agent, tiuxetan, is used to covalently link the radionuclide to the MAB ibritumomab. However, another approved anti-CD20 MAB, rituximab, is included in the dosing regimen as a nonradioactive pre-dose to improve the biodistribution of the radiolabeled MAB. Despite impressive clinical results, radioimmunotherapeutic MABs have not generated considerable commercial success; various financial, regulatory, and commercial barriers have been cited as contributing factors to this trend (Boswell and Brechbiel 2007).

MAB Therapeutic Mechanisms of Action (MOAS)

The pharmacological effects of antibodies are first initiated by the specific interaction between antibody and antigen. MABs generally exhibit exquisite specificity for the target antigen. The binding site on the antigen, called the epitope, can be linear or conformational and may comprise continuous or discontinuous amino acid sequences. The epitope is the primary determinant of the antibody’s modulatory functions, and depending on the epitope, the antibody may exert antagonist or agonist effects, or it may be nonmodulatory. The epitope may also influence the antibody’s ability to induce ADCC and CDC. MABs exert their pharmacological effects via multiple mechanisms that include direct modulation of the target antigen, CDC and ADCC, ADCP, apoptosis, delivery of a radionuclide or immunotoxin to target cells and T cell activation using bispecific constructs.

■ Direct Modulation of Target Antigen

Examples of direct modulation of the target antigen include anti-TNFα, anti-IgE, and anti-CD11a therapies that are involved in blocking and removal of the target antigen. Most MABs act through multiple mechanisms and may exhibit cooperativity with concurrent therapies.

■ Complement-Dependent Cytotoxicity (CDC)

The complement system is an important part of the innate (i.e., nonadaptive) immune system. It consists of many enzymes that form a cascade with each enzyme acting as a catalyst for the next. CDC results from interaction of cell-bound MABs with proteins of the complement system. CDC is initiated by binding of the complement protein, C1q, to the Fc domain. The IgG1 and IgG3 isotypes have the highest CDC activity, while the IgG4 isotype lacks C1q binding and complement activation (Presta 2002). Upon binding to immune complexes, C1q undergoes a conformational change, and the resulting activated complex initiates an enzymatic cascade involving complement proteins C2 to C9 and several other factors. This cascade spreads rapidly and ends in the formation of the membrane attack complex (MAC), which inserts into the membrane of the target cell and causes osmotic disruption and lysis of the target. Figure 8.5 illustrates the mechanism for CDC with rituximab (a chimeric MAB that targets the CD20 antigen) as an example.

■ Antibody-Dependent Cellular Cytotoxicity (ADCC)

ADCC is a mechanism of cell-mediated immunity whereby an effector cell of the immune system actively lyses a target cell that has been bound by specific antibodies. It is one of the mechanisms through which antibodies, as part of the humoral immune response, can act to limit and contain infection. Classical ADCC is mediated by natural killer (NK) cells, monocytes, or macrophages, but an alternate ADCC is used by eosinophils to kill certain parasitic worms known as helminths. ADCC is part of the adaptive immune response due to its dependence on a prior antibody response. The typical ADCC involves activation of NK cells, monocytes, or macrophages and is dependent on the recognition of antibody-coated infected cells by Fc receptors on the surface of these cells. The Fc receptors recognize the Fc portion of antibodies such as IgG, which bind to the surface of a pathogen-infected target cell. The Fc receptor that exists on the surface of NK cell is called CD16 or FcγRIII. Once bound to the Fc receptor of IgG, the NK cell releases cytokines such as IFN-γ and cytotoxic granules like perforin and granzyme that enter the target cell and promote cell death by triggering apoptosis. This is similar to, but independent of, responses by cytotoxic T cells. Figure 8.6 illustrates the mechanism for ADCC with rituximab as an example.

■ Antibody-Dependent Cellular Phagocytosis (ADCP)

ADCP is an immune effector function in which cells or particles opsonized with antibodies are engulfed by phagocytic effector cells, such as macrophages, following interactions between the Fc region of antibodies and Fcγ receptors on effector cells. In vivo, ADCP can be mediated by monocytes, macrophages, neutrophils and dendritic cells via all three types of activating Fcγ receptors: FcγRI, FcγRIIa, and FcγRIIIa. Studies have shown that MABs against tumor antigens induce phagocytosis of cancer cells in vitro, promote macrophage infiltration into tumors, and elicit macrophage-mediated destruction of tumors in mice (Weiskopf and Weissman 2015). ADCP is an important MOA of several antibody therapies for cancer, such as rituximab, obinutuzumab, and ocrelizumab. Engagement of Fcγ receptors expressed on phagocytic effector cells with antibodies bound to target cells triggers a signaling cascade leading to the engulfment of the antibody-opsonized tumor cells. Upon full engulfment, a phagosome is formed, which fuses with lysosomes, leading to acidification and digestion of the tumor cells. Figure 8.6 illustrates the mechanism for ADCP with rituximab as an example.

■ Apoptosis

MABs achieve their therapeutic effect through various mechanisms. In addition to the abovementioned effector functions, they can have direct effects in producing apoptosis or programmed cell death, which is characterized by nuclear DNA degradation, nuclear degeneration and condensation, and the phagocytosis of cell remains.

■ Targeted Delivery of Cytotoxic Drugs via ADCs

ADCs achieve their therapeutic effect through selectively delivering a potent cytotoxic agent to tumor cells (Girish and Li 2015). The MAB component enables the ADC to specifically bind to targeted cell surface antigens overexpressed on the tumor cells. After binding to the cell surface antigen, the ADC is internalized by the tumor cell, where it undergoes lysosomal degradation, leading to the release of the cytotoxic agent. Targeted delivery of cytotoxic drugs to tumors enables ADCs to potentially harness and improve their antitumor effect while minimizing their impact on normal tissues, thereby enhancing the benefit-risk profile.

■ CD3⁺ T cell Activation Using Bispecific Constructs

CD3 bispecific constructs achieve their therapeutic effects through activating a patient’s own CD3⁺ T cells to attack target-positive tumor cells. CD3 bispecific constructs have one arm directed against the CD3 receptor on T cells and the other arm directed against a target cell surface antigen overexpressed by tumor cells (Mandikian et al. 2018). Simultaneous engagement of both arms results in formation of an immunologic synapse between a target tumor cell and a CD3⁺ T cell, which leads to killing of the target tumor cells, either through direct killing by granzyme- and perforin-induced cell lysis or through cytokine release caused by T-cell activation.

Translational Medicine/Development Process

The tight connection of basic to clinical sciences is an essential part of translational medicine, which aims to translate the knowledge of basic science into practical therapeutic applications for patients. This knowledge transfer is often referred to as the process of moving from-bench-to-bedside, emphasizing the transition of scientific advancements into clinical applications. This framework of translational medicine is applied during the discovery and drug development process of a specific MAB against a certain disease. It includes major steps such as identifying an important and viable pathophysiological target antigen to modify the disease in a beneficial way, producing MABs with structural elements providing optimal PK, preclinical safety and efficacy testing in relevant models, and finally clinical trials in patients. An overview of the development phases of the molecules comprising the preclinical activities is outlined in Fig. 8.7. Furthermore, the critical components of the entire MAB development process are explained in detail from a PK/PD perspective below.

■ Preclinical Safety Assessment of MABs

Preclinical safety assessment of MABs encounters unique challenges, as many of the classical evaluations employed for small molecules are not appropriate for protein therapeutics in general and MABs in particular. For example, in vitro genotoxicology tests such as the Ames and chromosome aberration assays are generally not conducted for MABs given their limited interaction with nuclear material and the lack of appropriate receptor/target expression in these systems. As MAB binding tends to be highly species specific, suitable animal models are often limited to nonhuman primates, and for this reason, many common in vivo models, such as rodent carcinogenesis bioassays and some safety pharmacology bioassays, are not viable for MAB therapeutic candidates. For general toxicology studies, cynomolgus and rhesus monkeys are most commonly employed and offer many advantages given their close phylogenetic relationship with humans; however, due to logistics, animal availability, and costs, group sizes tend to be much smaller than typically used for lower species, thus limiting statistical power. In some cases, alternative models are employed to enable studies in rodents. Rather than directly testing the therapeutic candidate, analogous MABs that can bind to target epitopes in lower species (e.g. mice) can be engineered and used as a surrogate MAB for safety evaluation (Clarke et al. 2004). Often the antibody framework amino acid sequence is modified to reduce antigenicity thus enabling longer-term studies (Albrecht and DeNardo 2006; Weiner 2006; Cohenuram and Saif 2007). Another approach is to use transgenic models that express the human receptor/target of interest (Bugelski et al. 2000), although results must be interpreted with caution as transgenic models often have altered physiology and typically lack historical background data for the model (Boswell et al. 2013). To address development issues that are specific to MABs and other protein therapeutics, the International Conference of Harmonization (ICH) has developed guidelines specific to the preclinical evaluation of biotechnology-derived pharmaceuticals (ICH 1997a, b).

For general safety studies, species selection is an important consideration given the exquisite species specificity often encountered with MABs. Model selection needs to be justified based on appropriate expression of the target epitope, appropriate binding affinity with the therapeutic candidate, and appropriate biologic activity in the test system. To aid in the interpretation of results, tissue cross-reactivity studies offer the ability to compare drug localization in both animal and human tissues. For MAB therapeutic candidates, a range of three or more dose levels are typically selected to attain pharmacologically relevant serum concentrations, to approximate levels anticipated in the clinic, and to provide information at doses higher than anticipated in the clinic. For most indications, it is important to include dose levels that allow identification of a no observable adverse effect level (NOAEL). If feasible, the highest dose should fall within the range where toxicity is anticipated; although, in practice, many MABs do not exhibit toxicity, and other factors limit the maximum dose. To best reflect human exposures, doses are often normalized and selected to match and exceed anticipated human therapeutic exposure in plasma, serum, or blood based upon the exposure parameters, area under the concentration-time curve (AUC), maximum concentration (C _max), or concentration immediately prior to next treatment (C _trough). The route of administration , dosing regimen , and dosing duration should be selected to best model the anticipated use in clinical trials (ICH 1997a, b).

To adequately interpret nonclinical study results, it is important to characterize ADA responses. For human MABs, ADA responses are particularly prominent in lower species but also evident in nonhuman primates albeit to a lesser degree, making these species more viable for chronic toxicity studies. ADAs can impact drug activity in a variety of ways. Neutralizing ADAs are those that bind to the therapeutic in a manner that prevents activity, often by inhibiting direct binding to the target epitope. Non-neutralizing antibodies may also indirectly impact drug activity, for example, rapid clearance of drug–ADA complexes can effectively reduce serum drug concentrations. In situations where prominent ADA responses are expected, administration of high-dose multiples of the anticipated clinical dose may overcome these issues by maintaining sufficient circulating concentrations of active drug when supported with sufficient safety margin. To properly interpret study results, it is important to characterize ADA incidence and magnitude, as the occurrence of ADA responses could mask toxicities. Alternatively, robust ADA responses may induce significant signs of toxicity, such as infusion-related anaphylaxis, that may not be predictive of human outcome where ADA formation is likely to be less of an issue. If ADA formation is clearly impacting circulating drug levels, ADA-positive individual animals are often removed from consideration when evaluating pharmacokinetic parameters to better reflect the anticipated PK in human populations.

■ Pharmacokinetics

A thorough and rigorous PK program in the early learning phase of preclinical drug development can provide a linkage between drug discovery and preclinical development. PK information can be linked to PD by mathematical modeling, which allows characterizing the time course of the effect intensity resulting from a certain dosing regimen. Antibodies often exhibit PK properties that are complex and different than those typically associated with small molecule drugs (Meibohm and Derendorf 2002). The PK of ADCs is more complex due to the presence of both an antibody component as well as a small molecule component. In the following sections, the basic characteristics of MAB and ADC PK are summarized in contrast to small molecule drugs.

The PK of antibodies and ADCs are very different from that of small molecules, as summarized in Table 8.3. Precise, sensitive, and accurate bioanalytical methods are essential for PK interpretation. However, for MABs, the immunoassays and bioassay methodologies are often less specific than assays used for small molecule drugs (e.g., LC/MS/MS). MABs are handled by the body very differently than are small molecules. In contrast to small molecule drugs, the typical metabolic enzymes and transporter proteins, such as cytochrome P450 and multidrug resistance (MDR) efflux pumps, are not involved in the disposition of MABs. Consequently, drug–drug interactions (DDI) at the level of these drug-metabolizing enzymes and transporters are not complicating factors in the drug development process of MABs and in general do not need to be addressed by in vitro and in vivo studies. Because of their large molecular weight, intact MABs are not usually cleared by the kidneys; however, renal clearance processes may play an important role in the elimination of molecules of smaller molecular weight such as Fab’s and chemically derived small molecule drugs. The different ADME (Absorption, Distribution, Metabolism, and Elimination) processes comprising the PK of MABs are discussed separately to address their individual specifics.

Table 8.3 Comparison of the pharmacokinetics between small molecule drugs, monoclonal antibodies and antibody-drug conjugates (Mould et al. 1999; Lobo et al. 2004; Roskos et al. 2004; Mould and Sweeney 2007; Kamath 2016)

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Absorption

Most MABs are not administrated orally because of their limited gastrointestinal stability, lipophilicity, and size, all of which result in insufficient resistance against the hostile proteolytic gastrointestinal milieu and very limited permeation through the lipophilic intestinal wall. Therefore, intravenous (IV) administration is still the most frequently used route, which allows for immediate systemic delivery of a large volume of drug product and provides complete systemic availability. Subcutaneous (SC) administration, however, may offer a number of benefits over IV administration. Being less invasive and with a much shorter injection duration (2–7 min versus 30–90 min for IV infusion), and commonly with a fixed dose, SC dosing is expected to offer more convenience to patients compared to IV infusion. Additionally, IV infusion is typically administered in a hospital or physician’s office; SC administration may allow self or healthcare professional-assisted home administration. Of note, 22 of the 75 FDA-approved MAB or MAB-derived therapies listed in Table 8.1 are administered by an extravascular route, either SC or IM. Aflibercept and ranibizumab are administered via intravitreal injection.

The absorption mechanisms of SC or IM administration are poorly understood. However, it is believed that the absorption of MABs after IM or SC injection is likely via lymphatic drainage due to its large molecular weight, leading to a slow absorption rate (see Chaps. 5 and 6). The bioavailability of MABs after SC or IM administration has been reported to be around 50–100% with maximal plasma concentrations observed 1–8 days following administration (Lobo et al. 2004). For example, following an IM injection, the bioavailability of alefacept was ~60% in healthy male volunteers; its C _max was threefold lower (0.96 versus 3.1 μg/mL), and its T _max was 30 times longer (86 versus 2.8 h) than a 30-min IV infusion (Vaishnaw and TenHoor 2002). Interestingly, differences in PK have also been observed between different sites of IM dosing. PAmAb, a fully humanized MAB against Bacillus anthracis protective antigen, has significantly different pharmacokinetics between IM-GM (gluteus maximus site) and IM-VL (vastus lateralis site) injection in healthy volunteers (Subramanian et al. 2005). The bioavailability of PAmAb is 50–54% for IM-GM injection and 71–85% for IM-VL injection (Subramanian et al. 2005). Of note, MABs appear to have greater bioavailability after SC administration in monkeys than in humans (Oitate et al. 2011). The mean bioavailability of adalimumab is 52–82% after a single 40 mg SC administration in healthy adult subjects, whereas it was observed to be 94–100% in monkeys. Similarly, the mean bioavailability of omalizumab is 66–71% after a single SC dose in patients with asthma versus 88–100% in monkeys (Oitate et al. 2011).

Although SC administration of MABs initially used low-volume injections (1–2 mL), in recent years, larger-volume injections (>2 mL) have been used, with and without permeation enhancers . SC injections of a viscous (5 cP) placebo buffer, characteristic of a high-concentration MAB formulation, at volumes of up to 3.5 mL had acceptable tolerability in healthy adult subjects at injection rates up to 3.5 mL/min (Dias et al. 2015a, b). Due to relatively large therapeutic doses (several hundred milligram), dosing volumes of high-concentration MABs may still be too large to facilitate a painless SC injection. Without co-injection of a permeation enhancer, large volume injections may produce swelling at the injection site, particularly in the thigh and arm. A permeation enhancer, such as recombinant human hyaluronidase (rHuPH20), reduces this swelling. Hyaluronidase is a 61-kD naturally-occurring enzyme that temporarily degrades hyaluronan in the skin and increases dispersion of the MAB over a greater area. Co-formulation of rHuPH20 with therapeutic proteins allows SC administration of larger injection volumes and potentially enhances absorption of the therapeutic protein into the systemic circulation (Frost 2007). Trastuzumab and rituximab have both been co-formulated with rHuPH20 to facilitate large-volume SC injections (Bittner et al. 2012). Trastuzumab is available as a 5-mL SC injection to be administered over 2–5 min, while rituximab is available at 11.7 or 13.4 mL injection volumes to be administered over 5 or 7 min, respectively.

Distribution

After reaching the bloodstream , MABs undergo biphasic elimination from serum, beginning with a rapid distribution phase. The volume of distribution of the rapid-distribution compartment is relatively small, approximating plasma volume. It is reported that the volume of the central compartment (Vc) is about 2–3 L, and the steady-state volume of distribution (Vss) is around 3.5–7 L for MABs in humans (Lobo et al. 2004; Roskos et al. 2004). The small Vc and Vss for MABs indicate that the distribution of MABs is restricted to the blood and extracellular spaces, which is in agreement with their hydrophilic nature and their large molecular weight, limiting access to the intracellular compartment surrounded by a lipid bilayer. Small volumes of distributions are consistent with relatively small tissue: blood ratios for most antibodies typically ranging from 0.1 to 0.5 (Baxter et al. 1995; Baxter et al. 1994; Berger et al. 2005). For example, the tissue-to-blood concentration ratios for a murine IgG1 MAB against the human ovarian cancer antigen CA125 in mice at 24 h after injection are 0.44, 0.39, 0.48, 0.34, 0.10, and 0.13 for the spleen, liver, lung, kidney, stomach, and muscle, respectively. Brain and cerebrospinal fluid are anatomically protected by blood–brain barriers. Although the blood-brain barrier was believed to be impaired in certain neurodegenerative disease states, recent work has brought this into question (Bien-Ly et al. 2015). Therefore, both compartments are very limited distribution compartments for MABs. For example, endogenous IgG levels in CSF were shown to be in the range of only 0.1–1% of their respective serum levels (Wurster and Haas 1994; Yadav et al. 2017; Yu et al. 2014).

It has been repeatedly noted that the reported Vss obtained by traditional non-compartmental or compartmental analysis may not be correct for MABs that primarily undergo catabolism within tissue (Lobo et al. 2004; Straughn et al. 2006; Tang et al. 2004). The rate and extent of MAB distribution will be dependent on the kinetics of MAB extravasation within tissue, distribution within tissue, and elimination from tissue. Convection, diffusion, transcytosis, binding, and catabolism are important determining factors for antibody distribution (Lobo et al. 2004). Therefore, Vss might be substantially greater than the plasma volume in particular for those MABs demonstrating high binding affinity in the tissue. Different research groups have reported effects of the presence of specific receptors (i.e., antigen sink) on the distribution of MABs (Danilov et al. 2001; Kairemo et al. 2001; Bumbaca et al. 2012). Danilov et al. (2001) found in rats that an anti-PECAM-1 (anti-CD31) MAB showed tissue-to-blood concentration ratios of 13.1, 10.9, and 5.96 for the lung, liver, and spleen, respectively, 2 h after injection. Therefore, the true Vss of the anti-PECAM-1 is likely to be 15-fold greater than plasma volume.

Another complexity to consider is that tissue distribution via interaction with target proteins (e.g., cell surface proteins) and subsequent internalization of the antigen-MAB complex may be dose dependent. For the murine analog MAB of efalizumab, M17, a pronounced dose-dependent distribution was demonstrated by comparing tissue-to-blood concentration ratios for liver, spleen, bone marrow, and lymph node after a tracer dose of radiolabeled M17 and a high-dose treatment (Coffey et al. 2005). The tracer dose of M17 resulted in substantially higher tissue-to-blood concentration ratios of 6.4, 2.8, 1.6, and 1.3 for the lung, spleen, bone marrow, and lymph node, respectively, in mice at 72 h after injection. In contrast, the saturation of the target antigen at the high-dose level reduced the tissue distribution to the target independent distribution and resulted consequently in substantially lower tissue-to-blood concentration ratios (less than 1).

FcRn may play an important role in the transport of IgGs from plasma to the interstitial fluid of tissue. Recently, the data from Yip et al. increased understanding of FcRn’s role in antibody PK and catabolism at the tissue level (Yip et al. 2014). They reported that distribution of the wild-type IgG and the variant with enhanced binding for FcRn were largely similar to each other in mice, but vastly different for the low-FcRn-binding variant due to its very low systemic exposure and widespread catabolism, particularly in liver and spleen. Ferl et al. (2005) reported that a physiologically based pharmacokinetic (PBPK) model, including the kinetic interaction between the MAB and the FcRn receptor within intracellular compartments, could describe the biodistribution of an anti-CEA MAB in a variety of tissue compartments such as plasma, lung, spleen, tumor, skin, muscle, kidney, heart, bone, and liver. FcRn was also reported to mediate the crossing of placental barriers by IgG (Junghans 1997) and the vectorial transport of IgG into the lumen of intestine (Dickinson et al. 1999) and lung (Spiekermann et al. 2002).

Clearance

Antibodies are mainly cleared by catabolism and broken down into peptide fragments and amino acids, which can be recycled—to be used as energy supply or for new protein synthesis. Due to the small molecular weight of antibodies fragments (e.g., Fab and Fv), elimination of these fragments is faster than for intact IgGs, and they can be filtered through the glomerulus and reabsorbed and/or metabolized by proximal tubular cells of the nephron (Lobo et al. 2004). Murine monoclonal anti-digoxin Fab, F(ab’)2, and IgG1 have half-lives of 0.41, 0.70, and 8.10 h in rats, respectively (Bazin-Redureau et al. 1997). Several studies reported that the kidney is the major route for the catabolism of Fab and elimination of unchanged Fab (Druet et al. 1978; McClurkan et al. 1993).

Typically, IgGs have serum half-lives of approximately 21 days, resulting from CL values of about 3–5 mL/day/kg, and Vss’s of 50–100 mL/kg. The exception is IgG3, which has a half-life of only 7 days. The half-life of IgG is much longer than that of other Igs (IgA, 6 days; IgE, 2.5 days; IgM, 5 days; IgD, 3 days). The FcRn receptor has been demonstrated to be a primary determinant of the disposition of IgG antibodies (Ghetie et al. 1996; Junghans 1997; Junghans and Anderson 1996). FcRn, which protects IgG from catabolism and contributes to the long plasma half-life of IgG, was first postulated by Brambell in 1964 (Brambell et al. 1964) and cloned in the late 1980s (Simister and Mostov 1989a, b). FcRn is a heterodimer comprising of a β₂m light chain and a MHC class I-like heavy chain. The receptor is ubiquitously expressed in cells and tissues. Several studies have shown that IgG CL in β₂m knockout mice (Ghetie et al. 1996; Junghans and Anderson 1996) and FcRn heavy chain knockout mice (Roopenian et al. 2003) is increased 10 to 15-fold, with no changes in the elimination of other Igs. Figure 8.8 illustrates how the FcRn receptor protects IgG from catabolism and contributes to its long half-life. The FcRn receptor binds to IgG in a pH-dependent manner: binding to IgG at the acidic pH (6.0) of the endosome and releasing IgG at physiological pH (7.4). The unbound IgG proceeds to the lysosome and undergoes proteolysis.

It has been demonstrated that IgG half-life is dependent on its affinity to FcRn receptors. The shorter half-life of IgG3 was attributed to its low binding affinity to the FcRn receptor (Junghans 1997; Medesan et al. 1997). Murine MABs have serum half-lives of 1–2 days in human. The shorter half-life of murine antibodies in human is due to their low binding affinity to the human FcRn receptor. It is reported that human FcRn binds to human, rabbit, and guinea pig IgG, but not to rat, mouse, sheep, and bovine IgG; however, mouse FcRn binds to IgG from all of these species (Ober et al. 2001). Interestingly, human IgG1 has greater affinity to murine FcRn (Petkova et al. 2006), which indicates potential limitations of using mice as preclinical models for human IgG1 pharmacokinetic evaluations. Ward’s group confirmed that an engineered human IgG1 had disparate properties in murine and human systems (Vaccaro et al. 2006). Engineered IgGs with higher affinity to FcRn receptor have a two to three-fold longer half-life compared with WT in mice and monkeys (Hinton et al. 2006; Petkova et al. 2006). Two engineered human IgG1 mutants with enhanced binding affinity to human FcRn show a considerably extended half-life compared with WT in hFcRn transgenic mice (4.35 ± 0.53, 3.85 ± 0.55 days versus 1.72 ± 0.08 days) (Hinton et al. 2006; Petkova et al. 2006) found that the half-life of IgG1 FcRn mutants with increasing binding affinity to human FcRn at pH 6.0 is about 2.5-fold longer than the WT antibody in monkey (838 ± 187 h versus 336 ± 34 h).

Dose-proportional, linear CL has been observed for MAB against soluble antigens with low endogenous levels (such as TNF-α, IFN-α, VEGF, and IL-5). For example, linear PK has been observed for a humanized MAB directed to human interleukin-5 following IV administration over a 6000-fold dose range (0.05–300 mg/kg) in monkeys (Zia-Amirhosseini et al. 1999). The CL of rhuMAB against VEGF after IV dosing (2–50 mg/kg) ranged from 4.81 to 5.59 mL/day/kg and did not depend on dose (Lin et al. 1999). The mean total serum CL and the estimated mean terminal half-life of adalimumab were reported to range from 0.012 to 0.017 L/h and 10.0 to 13.6 days, respectively, for a 5-cohort clinical trial (0.5–10 mg/kg), with an overall mean half-life of 12 days (den Broeder et al. 2002). However, MABs against soluble antigens with high endogenous levels (such as IgE) exhibit nonlinear PK. The PK of omalizumab, an MAB against IgE, is linear only at doses greater than 0.5 mg/kg (Petkova et al. 2006; Xolair (Omalizumab) Prescribing Information 2006).

Elimination of MABs may also be impacted by interaction with the targeted cell-bound antigen, and this phenomenon was demonstrated by dose-dependent clearance and half-life. At low dose, MABs show a shorter half-life and a faster clearance due to receptor-mediated elimination. With increasing doses, receptors become saturated, the half-life gradually increases to a constant, and the CL gradually decreases to a constant. The binding affinity (K _d), antigen density, and antigen turnover rate may influence the receptor-mediated elimination. Koon et al. found a strong inverse correlation between CD25 cell expression and the apparent half-life of daclizumab (a MAB specifically binding to CD25) (Koon et al. 2006). It has been shown that the PK of murine antihuman CD3 antibodies may be determined by the disappearance of target antigen (Meijer et al. 2002). In monkeys and mice, clearance of SGN-40, a humanized anti-CD40 MAB, was much faster at low dose, suggesting nonlinear PK (Kelley et al. 2006). In addition, Ng et al. demonstrated that an anti-CD4 MAB (TRX-1) had ~fivefold faster CL at 1 mg/kg dose compared with 10 mg/kg dose (37.4 ± 2.4 versus 7.8 ± 0.6 mL/day/kg) in healthy volunteers (Ng et al. 2006). They also found that receptor-mediated CL via endocytosis became saturated at higher doses; nonspecific clearance of TRX-1 contributed 8.6, 27.1, and 41.7% of total CL when dose was 1, 5, and 10 mg/kg, respectively.

In addition to FcRn and antigen–antibody interaction, other factors may also contribute to MAB elimination (Roskos et al. 2004; Tabrizi et al. 2006; Lobo et al. 2004):

1.
Immunogenicity: The elimination of MABs in humans may increase with increasing level of immunogenicity (Tabrizi et al. 2006; Ternant and Paintaud 2005).
2.
Degree and the nature of glycosylation : The impact of glycosylation on the pharmacokinetics and effector functions of therapeutic IgG1 monoclonal antibodies has been previously reviewed (Putnam et al. 2010).
3.
Susceptibility to proteolysis : Gillies and coworkers improved the circulating half-life of antibody-interleukin 2 immunocytokine by two-fold compared with wild type (1.0 h versus 0.54 h) by increasing the resistance to intracellular degradation (Gillies et al. 2002).
4.
Charge: Deliberate modification of the isoelectric point (pI) of an antibody by approximately one pI unit or more can lead to noticeable differences in the PK of an intact antibody (Igawa et al. 2010; Li et al. 2014; Bumbaca Yadav et al. 2015). Using a humanized anti-IL-6 receptor IgG1 as an example, Igawa et al. showed that lowering the pI point from 9.2 to 7.2 by engineering the V region reduced the IgG elimination in cynomolgus monkeys (Igawa et al. 2010). In contrast, minor changes in the nature of ionic charge resulting in pI differences of less than approximately one pI unit are not expected to affect the biological function of MABs, including tissue retention and whole blood clearance (Boswell et al. 2010b; Khawli et al. 2010).
5.
Effector function : Effector functions, such as interactions with FcγR, can also regulate elimination and PK of MABs (Mahmood and Green 2005). Mutation of the binding site of FcγR, for example, had dramatic effects on the clearance of an Ab-IL-2 fusion protein (Gillies et al. 1999).
6.
Concomitant medications: Methotrexate reduced adalimumab apparent CL after single dose and multiple dosing by 29 and 44%, respectively, in patients with RA (Humira (Adalimumab) Prescribing Information 2007). In addition, azathioprine and mycophenolate mofetil were reported to reduce CL of basiliximab by approximately 22 and 51%, respectively (Simulect (Basiliximab) Prescribing Information 2005). The effects of small molecule drugs on the expression of Fcγ receptors could explain this finding. It has also been shown that methotrexate affects expression of FcγRI on monocytes significantly in RA patients (Bunescu et al. 2004).
7.
Off-target binding: Although specificity to their targets is a major characteristic of MABs, they may have off-target binding that may result in atypical PK, such as faster CL and larger volume distribution. An anti-respiratory syncytial virus MAB, A4b4, developed by affinity maturation of palivizumab, had poor PK in rats and cynomolgus monkeys due to broad nonspecific tissue binding and sequestration (Wu et al. 2007). The rapid elimination of a humanized anti-human amyloid beta peptide MAB, anti-Aβ Ab2, in cynomolgus monkeys was linked to off-target binding to cynomolgus monkey fibrinogen (Vugmeyster et al. 2011). In addition, a humanized anti-fibroblast growth factor receptor 4 MAB had rapid CL in mice that was attributable to binding to mouse complement component 3 (Bumbaca et al. 2011). Other examples of MABs with off-target effects include MABs targeting Factor IXa/X (Sampei et al. 2013), interleukin-21 receptor (Vugmeyster et al. 2010). It is important to eliminate MABs with higher risk of failure at the discovery stage, to increase the success rate. As PK of these therapeutic proteins might be influenced by a large number of both specific and nonspecific factors, Dostalek et al. have proposed multiple pharmacokinetic de-risking tools for selection of MAB lead candidates (Dostalek et al. 2017).
8.
Body weight, age, disease state, and other demographic factors: Individual characteristics can also change MAB PK (Mould and Sweeney 2007; Ryman and Meibohm 2017) (see Population Pharmacokinetics section).
9.
Albumin: Albumin is often an indicator of disease status and a significant covariate affecting clearance for several MABs, including infliximab, pertuzumab, trastuzumab emtansine (Lu et al. 2014), and bevacizumab (Dirks and Meibohm 2010). It is believed that albumin, which binds to FcRn at different sites than IgG, is an indicator of increased number of FcRn (Dirks and Meibohm 2010; Fasanmade et al. 2010). Nevertheless, the correlation between the levels of albumin and the CL of pertuzumab and bevacizumab was moderate and dose modification was not recommended (Dirks and Meibohm 2010). Regardless, it has been suggested that serum albumin levels are a predictive factor for PK of infliximab and clinical response to the drug in patients with ulcerative colitis (Fasanmade et al. 2010).
10.
Disease state: It has been reported that disease state can impact MAB PK. Lower exposure and faster CL for trastuzumab (Yang et al. 2013; Han et al. 2014), bevacizumab (Han et al. 2014), pertuzumab (Kang et al. 2013), and trastuzumab emtansine (Chen et al. 2017) in patients with gastric cancer (GC) versus breast cancer (BC) have been reported. Steady-state trastuzumab trough concentration (C_trough) in patients with metastatic GC is 24–63% lower than in BC (Yang et al. 2013). The underlying mechanism for faster CL of MABs in GC is unknown and warrants further research. Population PK analyses of ofatumumab were performed for various diseases with varying CD20 B-cell counts and indicated that target-mediated CL in CLL is greater than that in RA and FL, which is consistent with the higher B-cell count seen in CLL (Struemper et al. 2014). Diabetic comorbidity resulted in 28.7% higher CL/F for ustekinumab (Zhu et al. 2009). Infliximab CL is 40–50% higher in inflammatory bowel disease patients, which is likely due to protein losing enteropathy (Fasanmade et al. 2009). Recently, it has been observed that MABs in immune-oncology, such as pembrolizumab (Li et al. 2017) and nivolumab (Bajaj et al. 2017), have time-dependent CL. Sicker patients tend to have faster CL.

In summary, the association between baseline disease factors and PK complicates the interpretation of the exposure-efficacy analyses for MABs and ADCs in cancer patients, as only one-dose level is usually tested in the pivotal study. Although correction methods can be applied, the effect of disease severity on treatment exposure may result in an over-estimation of exposure–response relationships, i.e. visually a steep trend is seen when the true relationship is flat (Liu et al. 2015; Wang 2016).

Therapeutic MAB–Drug Interactions

MABs and other therapeutic proteins are increasingly combined with small molecule drugs to treat various diseases. Assessment of the potential for PK- and/or PD-based MAB–drug interactions is frequently incorporated into the drug development process (Girish et al. 2011). The exposure and response of concomitantly administered drugs can be altered by MABs (MAB as perpetrator), and other drugs can effect the PK and PD of therapeutic MABs (MAB as victim).

Several different mechanisms have been proposed for MAB–drug interactions. Various cytokines and cytokine modulators can influence the expression and activity of cytochrome P450 (CYP) enzymes and drug transporters (Lee et al. 2010). Therefore, if a therapeutic MAB is a cytokine or cytokine modulator, it can potentially alter the systemic exposure and/or clinical response of concomitantly administered drugs that are substrates of CYPs or transporters (Huang et al. 2010), particularly those with narrow therapeutic windows. For example, an increase in cyclosporin A (CsA) trough level was observed when given in combination with muromonab (Vasquez and Pollak 1997). Similarly, basiliximab has been shown to increase CsA and tacrolimus level when used in combination (Sifontis et al. 2002). In diseases states such as infection or inflammation, cytokines or cytokine modulators can also normalize previously changed activity of CYPs or transporters, thereby altering the exposure of co-administered drugs. Examples include tocilizumab coadministered with omeprazole and tocilizumab coadministered with simvastatin. At present, in vitro and preclinical systems have shown limited value in predicting a clinically relevant effect of cytokine-mediated therapeutic protein (TP)-DDI, and clinical evidence is preferred for informing the evolving risk assessment for TP-DDI (Huang et al. 2010; Slatter et al. 2013). To determine the necessity for a dedicated clinical DDI study, a four-step approach was proposed by the IQ Consortium/FDA TP-DDI workshop (San Diego 2012) in assessing TP-DDI risk for cytokines or cytokine modulators on CYP enzymes . This includes stepwise investigations of: (1) the disease effect on cytokine levels and CYP expression; (2) TP mechanism and its impact on cytokine-mediated DDI; (3) DDI liability of the concurrently used small molecule drugs; and (4) the above overall driving force in determining appropriate clinical TP-DDI strategies (Kenny et al. 2013). To date, a few dedicated clinical DDI studies have been performed for MABs that specifically target cytokines or cytokine receptors, e.g., tocilizumab (Schmitt et al. 2011), sirukumab (Zhuang et al. 2015), daclizumab HYP (Tran et al. 2016), and dupilumab (Davis et al. 2018). However, the overall impact of these cytokine-blocking MABs on PK of the CYP substrates (MAB as a perpetrator) were minimal (no effect, e.g., daclizumab HYP, ustekinumab, and dupilumab) or moderate (18–57% reduction in AUC for CYP 2C19 or 3A4 substrates, e.g., tocilizumab and sirukumab) and have not been implicated in dose justification for the relevant concurrent medicines.

MAB–drug interactions can also occur when a therapeutic MAB is administered with a concomitant drug that can alter the formation of ADAs. This may in turn alter MAB clearance from the systemic circulation. For example, methotrexate (MTX) reduced the apparent CL of adalimumab by 29 and 44% after single and repeated dosing (Humira (Adalimumab) Prescribing Information 2007). MTX also had similar effect on infliximab (Maini et al. 1998). PD-based interactions can result from alteration of target biology, such as the site of expression, relative abundance of expression, and the pharmacology of the target (Girish et al. 2011). Examples include efalizumab in combination with triple immune-suppressant therapy (Vincenti et al. 2007) and anakinra in combination with etanercept (Genovese et al. 2004).

To date, evidence of therapeutic MAB–drug interactions via nonspecific clearance appears to be limited, although down-regulation of Fcγ receptors by MTX is observed in patients with RA. It is possible that changes in Fcγ receptors can affect MAB clearance in the presence of MTX (Girish et al. 2011).

ADCs can also interact with drugs or MABs via the mechanisms described above. However, evidence of ADC–drug or ADC–MAB interaction appears to be absent. Lu et al. reported lack of interaction between trastuzumab emtansine (T-DM1) and pertuzumab in patients with HER2-positive metastatic breast cancer (Lu et al. 2012). Similarly, no interaction was observed between T-DM1 and paclitaxel or T-DM1 and docetaxel (Lu et al. 2012). With the theoretical potential for, and current experiences with, MAB–drug interactions, a question and risk-based integrated approach depending on the mechanism of the MABs and patient population have been progressively adopted during drug development to address important questions regarding the safety and efficacy of MAB and drug combinations (Girish et al. 2011). Various in vitro test systems have been used to provide some insight into the MAB–drug interactions, such as isolated hepatocytes and liver microsomes. However, the interpretation of these in vitro data is difficult. More importantly, prospective predictions of drug interactions based on in vitro findings have not been feasible for MABs. Therefore, clinical methods are primarily used to assess MAB–drug interactions. Three common methods used are population PK, clinical cocktail studies, and less frequently, dedicated drug interaction studies. Details of various strategies used in pharmaceutical industry were reviewed in a 2011 AAPS white paper (Girish et al. 2011). Recently, PBPK modeling has been used as a tool to predict drug interactions for antibody-drug conjugates (Chen et al. 2015).

Prediction of Human PK/PD Based on Preclinical Information

Prior to a first-in-human (FIH) clinical study, a number of preclinical in vivo and in vitro experiments are conducted to evaluate the PK/PD, safety, and efficacy of a new drug candidate. However, the ultimate goal is at all times to predict how these preclinical results on PK, safety, and efficacy data translate into a given patient population. Therefore, the objective of translational research is to predict PK/PD/safety outcomes in a target patient population, acknowledging the similarities and differences between preclinical and clinical settings.

Over the years, many theories and approaches have been proposed and used for scaling preclinical PK data to humans (Fig. 8.9). Allometric scaling , based on a power–law relationship between size of the body and physiological and anatomical parameters, is the simplest and most widely used approach (Dedrick 1973; Mahmood 2005, 2009). More recently, experimental efforts have been dedicated to accurate measurement of physiological parameters that are required for calculating drug concentrations at site of action and for physiologically based models (Boswell et al. 2010a, 2012, 2014). Physiologically based PK modeling (Shah and Betts 2012), species-invariant time method (Dedrick approach) (Oitate et al. 2011), and nonlinear mixed effect modeling based on allometry (Jolling et al. 2005; Martin-Jimenez and Riviere 2002) have also been used for interspecies scaling of PK. While no single scaling method has been shown to definitively predict human PK in all cases, especially for small molecule drugs (Tang and Mayersohn 2005), the PK for MABs can be predicted reasonably well, especially for MAB at doses where the dominant clearance route is likely to be independent of concentration. Most therapeutic MABs bind to nonhuman primate antigens more often than to rodent antigens, due to the greater sequence homology observed between nonhuman primates and humans. The binding epitope, in vitro binding affinity to antigen, binding affinity to FcRn, tissue cross-reactivity profiles, and disposition and elimination pathways of MABs are often comparable in nonhuman primates and humans. It has recently been demonstrated that clearance and distribution volume of MABs with linear PK in humans can be reasonably projected based on data from nonhuman primates alone, with a fixed scaling exponent ranging from 0.75 to 0.9 for CL and a fixed scaling exponent 1 for volume of distribution (Oitate et al. 2011; Ling et al. 2009; Wang and Prueksaritanont 2010; Deng et al. 2011; Dong et al. 2011). For MABs that exhibited nonlinear PK, the best predictive performance was obtained above doses that saturated the target of the MAB (Dong et al. 2011). Pharmacokinetic prediction for low doses of a MAB with nonlinear elimination remains challenging and will likely require further exploration of species difference in target expression level, target antibody binding and target kinetics, as well as strategic in vivo animal PK studies, designed with relevant dose ranges. Immunogenicity is an additional challenge for the prediction of MAB PK. Alterations in the PK profile due to immune-mediated clearance mechanisms in preclinical species cannot be scaled up to humans, since animal models are not predictive of human immune response to human MABs. Thus, either excluding ADA-positive animals from PK scaling analysis or using only the early time points prior to ADAs observation in ADA-positive animals has been a standard practice in the industry.

Due to its complexity, any extrapolation of PD to humans requires more thorough consideration than for PK. Little is known about allometric relationships in PD parameters. It is expected that the physiological turnover rate constants of most general structures and functions among species should obey allometric principles, whereas capacity and sensitivity tend to be similar across species (Mager et al. 2009). Through integration of PK/PD modeling and interspecies scaling, PD effects in humans may be predicted if the PK/PD relationship is assumed to be similar between animal models and humans (Duconge et al. 2004; Kagan et al. 2010). For example, a PK/PD model was first developed to optimize the dosing regimen of a MAB against EGF/r3 using tumor-bearing nude mice as an animal model of human disease (Duconge et al. 2004). This PK/PD model was subsequently integrated with allometric scaling to calculate the dosing schedule required in a potential clinical trial to achieve a specific effect (Duconge et al. 2004).

In summary, species differences in antigen expression level, antigen–antibody binding and antigen kinetics, differences in FcRn binding between species, the immunogenicity, and other factors must be considered during PK/PD scaling of a MAB from animals to humans.

Role of PK/PD in Clinical Development of Antibody Therapeutics

Drug development has traditionally been performed in sequential phases, divided into preclinical as well as clinical phases I–IV . During the development phases of the molecules, the safety and PK/PD characteristics are established in order to select a compound for development and define a dosing regimen. This information-gathering process has been characterized as two successive learning–confirming cycles (Sheiner and Wakefield 1999; Sheiner 1997).

The first cycle (phases I and IIa) comprises learning about the dose regimen that is tolerated in healthy subjects and confirming that this dose regimen has shown drug-target engagement, acceptable tolerability and measurable clinical benefits in the targeted patients. An affirmative answer at this first cycle provides the justification for a larger and more costly second learn–confirm cycle (phases IIb and III), where the learning step is focused on defining the drug benefit/risk profile, whereas the confirm step is aimed at demonstrating acceptable benefit/risk in a large patient population (Meibohm and Derendorf 2002).

The drug development process at the clinical stage provides several opportunities for integration of PK/PD concepts. Clinical phase I dose escalation studies provide, from a PK/PD standpoint, the unique opportunity to evaluate the dose–concentration–effect relationship for therapeutic and toxic effects over a wide range of doses up to or even beyond the maximum tolerated dose under controlled conditions (Meredith et al. 1991). PK/PD evaluations at this stage of drug development can provide crucial information regarding the potency and tolerability of the drug in vivo and the verification and suitability of the PK/PD relationship established during preclinical studies.

Collecting robust data on the PK of the drug and PD or disease biomarkers that are indicative of drug pharmacology and disease progression/improvement is key to informing dose selection. Tocilizumab, omalizumab, and evolocumab are examples of MABs that utilized PK/PD or disease biomarker data to facilitate dose selection for pivotal trials, final doses and/or label revisions. In general, the strategy includes (1) understanding the PK profile and selecting clinical doses in the linear range, if possible; (2) identifying biomarkers having profiles correlated to clinically meaningful endpoints for PK/PD or exposure-response analyses, and (3) leveraging modeling and simulation approaches to predict the clinical outcome under different regimen scenarios, which is essential to determine the dose regimen for a pivotal trial or the final dose regimen on the label.

In the case of omalizumab, a dosing table for asthma patients was developed to select the dose based on an individual’s pre-treatment serum IgE level and body weight. The dosing table was designed to achieve a serum-free IgE level associated with clinical improvement (Hochhaus et al. 2003). PK/PD modeling and simulation approaches were subsequently used to revise and expand the dosing table (Lowe et al. 2015; Honma et al. 2016). In the case of evolocumab, a high-level summary of the development program and dosing strategy follows.

Evolocumab is a recombinant, human IgG2 MAB that specifically binds to human proprotein convertase subtilisin/kexin type 9 (PCSK9). It prevents PCSK9 from interacting with the low density lipoprotein receptor (LDLR), thus upregulating LDLR, increasing uptake of circulating LDL-cholesterol (LDL-C) and reducing LDL-C concentration in plasma (Page and Watts 2015). Evolocumab is used as an adjunct to diet and maximally tolerated statin therapy for the treatment of adults with heterozygous familial hypercholesterolemia or clinical atherosclerotic cardiovascular disease. Its use is also indicated as an adjunct to diet and other LDL-lowering therapies for the treatment of patients with homozygous familial hypercholesterolemia.

The PK of evolocumab following multiple SC doses was evaluated in a Phase 1 study in subjects on a stable dose of statin over a dose range of 14–420 mg of evolocumab weekly, every 2 weeks, or every 4 weeks. Multiple doses of evolocumab resulted in nonlinear PK for the lower doses (up to 140 mg SC). Dose regimens of 140 mg and greater led to linear PK and concentrations associated with near complete suppression of PCSK9 (CDER 2014). Dose-dependent decreases in LDL-C levels were seen following treatment with evolocumab (CDER 2014) and this PD readout is also indicative of a meaningful clinical readout. There was a clear exposure-response relationship between evolocumab trough concentrations and LDL-C response (CDER 2014). These PK/PD data and the exposure-response relationship were used to support the final approved dose and dosing regimen.

■ Efalizumab Case Study (Raptiva^®)

In the following sections, the recombinant humanized IgG1 MAB efalizumab is provided as a more detailed case study to understand the various steps during the development of therapeutic antibodies for various indications. Raptiva^® received approval for the treatment of patients with psoriasis in more than 30 countries, including the United States and the European Union (Raptiva (Efalizumab) [Prescribing Information] 2004). However, it was withdrawn from the market when the use of efalizumab was found to be associated with an increased risk of progressive multifocal leukoencephalopathy (PML) .

A summary of the preclinical program, the overall PK/PD data from multiple clinical studies, and the selection of the subcutaneous doses of efalizumab for the treatment of psoriasis will be discussed. Psoriasis is a chronic skin disease characterized by abnormal keratinocyte differentiation and hyperproliferation and by an aberrant inflammatory process in the dermis and epidermis. T cell infiltration and activation in the skin and subsequent T cell-mediated processes have been implicated in the pathogenesis of psoriasis (Krueger 2002). Efalizumab is a targeted inhibitor of T cell interactions (Werther et al. 1996). An extensive preclinical research program was conducted to study the safety and MOA of efalizumab. Multiple clinical studies were also conducted to investigate the efficacy, safety, PK, PD, and MOA of efalizumab in patients with psoriasis.

Preclinical Program of Efalizumab

A thorough and rigorous preclinical program provides a linkage between drug discovery and clinical development. At the preclinical stage, activities may include the evaluation of in vivo potency and intrinsic activity, the identification of bio-/surrogate markers, understanding of MOA, and characterization of nonclinical PK/PD, as well as dosage form/regimen selection and optimization. The role of surrogate molecules in assessing ADME of therapeutic antibodies is important as the antigen specificity of humanized MABs limits their utility in studies with rodents. Surrogate rodent MABs (mouse/rat) provide a means of gaining knowledge of PK and PD in a preclinical rodent model, facilitating dose optimization in the clinic.

In the case of efalizumab, to complete a more comprehensive safety assessment, a chimeric rat anti-mouse CD11a antibody, muM17, was developed and evaluated as a species-specific surrogate molecule for efalizumab. muM17 binds mouse CD11a with specificity and affinity similar to that of efalizumab to its human target antigen. In addition, pharmacological activities of muM17 in mice were demonstrated to be similar to those of efalizumab in humans (Clarke et al. 2004; Nakakura et al. 1993).

The preclinical ADME program for efalizumab consisted of PK, PD (CD11a down-modulation and saturation), and toxicokinetic data from PK, PD, and toxicology studies with efalizumab in chimpanzees and with muM17 in mice. The use of efalizumab in the chimpanzee and muM17 in mice for PK and PD and safety studies was supported by in vitro activity assessments. The preclinical data were used for PK and PD characterization, PD-based dose selection, and toxicokinetic support for confirming exposure in toxicology studies. Together, these data supported both the design of the preclinical program and its relevance to the clinical program.

The observed PD as well as the MOA of efalizumab and muM17 is attributed to binding CD11a present on cells and tissues. The binding affinities of efalizumab to human and chimpanzee CD11a on CD3 lymphocytes are comparable, supporting the use of chimpanzees as a preclinical model for human responses. CD11a expression has been observed to be greatly reduced on T lymphocytes in chimpanzees and mice treated with efalizumab and muM17, respectively. Expression of CD11a is restored as efalizumab and muM17 are eliminated from the plasma.

The disposition of efalizumab and of the mouse surrogate muM17 is mainly determined by the combination of both specific interactions with the ligand CD11a and by their IgG1 framework. The disposition is governed by the species specificity of the antibody for its ligand CD11a, the amount of CD11a in the system, and the administered dose. Binding to CD11a serves as a major pathway for clearance of these molecules, which leads to nonlinear PK depending on the relative amounts of CD11a and efalizumab or muM17 (Coffey et al. 2005).

Based on the safety studies, efalizumab was considered to be generally well tolerated in chimpanzees at doses up to 40 mg/kg/week IV for 6 months, providing an exposure ratio of 339-fold based on cumulative dose and 174-fold based on the cumulative AUC, compared with a clinical dose of 1 mg/kg/week. The surrogate antibody muM17 was also well tolerated in mice at doses up to 30 mg/kg/week SC. Overall, efalizumab was considered to have an excellent nonclinical safety profile, thereby supporting the use in adult patients. There was no signal for PML in the nonclinical studies, which subsequently led to withdrawal of efalizumab from the market.

Clinical Program of Efalizumab: PK/PD Studies, Assessment of Dose, Route, and Regimen

Efalizumab PK and PD data were available from ten studies in which more than 1700 patients with psoriasis received IV or SC efalizumab. In the phase I studies, PK and PD parameters were characterized by extensive sampling during treatment; in the phase III trials, steady-state trough levels were measured once or twice during the first 12-week treatment period for all the studies and during extended treatment periods for some studies. Several early phase I and II trials examined IV injection of efalizumab, and dose-ranging findings from these trials served as the basis for SC dosing levels used in several subsequent phase I and all phase III trials.

IV Administration of Efalizumab

The PK of MABs varies greatly, depending primarily on their affinity for and the distribution of their target antigen (Lobo et al. 2004). Efalizumab exhibited concentration-dependent nonlinear PK after administration of single IV doses of 0.03, 0.1, 0.3, 0.6, 1.0, 2.0, 3.0, and 10.0 mg/kg in a phase I study. This nonlinearity is directly related to specific and saturable binding of efalizumab to its cell surface receptor, CD11a, and has been described by a PK/PD model developed by Bauer et al. (1999), which was expanded to a PK/PD/efficacy model by Ng et al. (2005). The PK profiles of efalizumab following single IV doses with observed data and model predicted fit are presented in Fig. 8.10. Mean CL decreased from 380 to 6.6 mL/kg/day for doses of 0.03 mg/kg to 10 mg/kg, respectively. The volume of distribution of the central compartment (Vc) of efalizumab was 110 mL/kg at 0.03 mg/kg (approximately twice the plasma volume) and decreased to 58 mL/kg at 10 mg/kg (approximately equal to plasma volume), consistent with saturable binding of efalizumab to CD11a in the vascular compartment. Because of efalizumab’s nonlinear PK, its half-life (t _1/2) is dose dependent.

In a phase II study of efalizumab, it was shown that at a weekly dosage of 0.1 mg/kg IV, patients did not maintain maximal down-modulation of CD11a expression and did not maintain maximal saturation. Also, at the end of 8 weeks of efalizumab treatment, 0.1 mg/kg/week IV, patients did not have statistically significant histological improvement and did not achieve a full clinical response. The minimum weekly IV dosage of efalizumab tested that produced histological improvements in skin biopsies was 0.3 mg/kg/week. This dosage resulted in submaximal saturation of CD11a binding sites but maximal down-modulation of CD11a expression. Improvements in patients’ psoriasis were also observed, as determined by histology and by the Psoriasis Area and Severity Index (PASI) (Papp et al. 2001).

Determination of SC Doses

Although efficacy was observed in phase I and II studies with 0.3 mg/kg/week IV efalizumab, dosages of 0.6 mg/kg/week and greater (given for 7–12 weeks) provided more consistent T lymphocyte CD11a saturation and maximal PD effect. At dosages ≤0.3 mg/kg/week, large between-subject variability was observed, whereas at dosages of 0.6 or 1.0 mg/kg/week, patients experienced better improvement in PASI scores, with lower between-patient variability in CD11a saturation and down-modulation. Therefore, since the desired route of administration was SC, this IV dosage was used to estimate an appropriate minimum SC dose of 1 mg/kg/week (based on a 50% bioavailability) that would induce similar changes in PASI, PD measures, and histology. The safety, PK, and PD of a range of SC efalizumab doses (0.5–4.0 mg/kg/week administered for 8–12 weeks) were evaluated initially in two phase I studies (Gottlieb et al. 2003). To establish whether a higher SC dosage might produce better results, several phase III clinical trials assessed a 2.0 mg/kg/week SC dosage in addition to the 1.0 mg/kg/week dosage. A dose of 1.0 mg/kg/week SC efalizumab was selected as it produced sufficient trough levels in patients to maintain the maximal down-modulation of CD11a expression and binding-site saturation between weekly doses (Joshi et al. 2006). Figure 8.11 depicts the serum efalizumab levels, CD11a expression, and available CD11a binding sites on T lymphocytes (mean ± SD) after SC administration of 1 mg/kg efalizumab.

SC Administration of Efalizumab

The PK of SC efalizumab was well characterized following multiple SC doses of 1.0 and 2.0 mg/kg/week (Joshi et al. 2006; Mortensen et al. 2005). A phase I study that collected steady-state PK and PD data for 12 weekly SC doses of 1.0 and 2.0 mg/kg in psoriasis patients provided most of the pharmacologic data relevant to the product that was on the market prior to its withdrawal. Although peak serum concentration after the last dose (C _max) was observed to be higher for the 2.0 mg/kg/week (30.9 μg/mL) than for the 1.0 mg/kg/week dosage (12.4 μg/mL), no additional changes in PD effects were observed at the higher dosages (Mortensen et al. 2005). Following a dose of 1.0 mg/kg/week, serum efalizumab concentrations were adequate to induce maximal down-modulation of CD11a expression and a reduction in free CD11a binding sites on T lymphocytes (Fig. 8.12). Steady-state serum efalizumab levels were reached more quickly with the 1.0 mg/kg/week dosage at 4 weeks compared with the 2.0 mg/kg/week dosage at 8 weeks (Mortensen et al. 2005), which is in agreement with the average effective t _1/2 of 5.5 days for SC efalizumab 1.0 mg/kg/week (Boxenbaum and Battle 1995). The bioavailability was estimated at approximately 50%. Population PK analyses indicated that body weight was the most significant covariate affecting efalizumab SC clearance, thus supporting body weight-based dosing for efalizumab (Sun et al. 2005).

Population Pharmacokinetics of Monoclonal Antibodies

Compared to many small molecule drugs , MABs typically exhibit less inter- and intra-subject variability of the standard PK parameters such as volume of distribution and clearance. However, it is possible that certain pathophysiological conditions may result into substantially increased intra- and inter-patient variability. In addition, patients are usually not very homogeneous; patients vary in sex, age, body weight; they may have concomitant disease and may be receiving multiple drug treatments. Even the diet, lifestyle, ethnicity, and geographic location can differ from a selected group of “normal” subjects. These covariates can have substantial influence on PK parameters. Therefore, good therapeutic practice should always be based on an understanding of both the influence of covariates on PK parameters as well as the PK variability in a given patient population. With this knowledge, dosage adjustments can be made to accommodate differences in PK due to genetic, environmental, physiological, or pathological factors, for instance, in case of compounds with a relatively small therapeutic index. The framework of application of population PK during drug development is summarized in the FDA guidance document entitled “Guidance for Industry—Population Pharmacokinetics” (FDA 1999).

For population PK data analysis, there are generally two reliable and practical approaches. One approach is the standard two-stage (STS) method, which estimates parameters from the plasma drug concentration data for an individual subject during the first stage. The estimates from all subjects are then combined to obtain a population mean and variability estimates for the parameters of interest. The method works well when sufficient drug concentration-time data are available for each individual patient; typically these data are gathered in phase 1 clinical trials. A second approach, nonlinear mixed effect modeling (NONMEM) , attempts to fit the data and partition the differences between theoretical and observed values into random error terms. The influence of fixed effect (i.e., age, sex, body weight) can be identified through a regression model building process.

The original scope for the NONMEM approach was its applicability even when the amount of time-concentration data obtained from each individual is sparse and conventional compartmental PK analyses are not feasible. This is usually the case during the routine visits in phase III or IV clinical studies. Nowadays the NONMEM approach is applied far beyond its original scope due to its flexibility and robustness. It has been used to describe data-rich phase I and phase IIa studies or even preclinical data to guide and expedite drug development from early preclinical to clinical studies (Aarons et al. 2001; Chien et al. 2005).

There has been increasing interest in the use of population PK and PD analyses for different antibody products (i.e. antibodies, antibody fragments, or antibody fusion proteins) over the past 15 years (Dirks and Meibohm 2010; Agoram et al. 2007; Gibiansky and Frey 2012; Gibiansky and Gibiansky 2009; Nestorov et al. 2004; Zheng et al. 2011; Zhou et al. 2004; Yim et al. 2005; Hayashi et al. 2007; Lee et al. 2003). One example involving analysis of population plasma concentration data involved a dimeric fusion protein, etanercept. A one-compartment first-order absorption and elimination population PK model with interindividual and inter-occasion variability on CL, volume of distribution, and absorption rate constant, with covariates of sex and race on apparent CL and body weight on CL and volume of distribution, was developed for etanercept in rheumatoid arthritis adult patients (Lee et al. 2003). The population PK model for etanercept was further applied to pediatric patients with juvenile RA and established the basis of the 0.8 mg/kg once weekly regimen in pediatric patients with juvenile RA (Yim et al. 2005). Unaltered etanercept PK with concurrent methotrexate in patients with RA has been demonstrated in a phase IIIb study using a population PK modeling approach (Zhou et al. 2004). Thus, no etanercept dose adjustment is needed for patients taking concurrent MTX. A simulation exercise of using the final population PK model of subcutaneously administered etanercept in patients with psoriasis indicated that the two different dosing regimens (50 mg QWk versus 25 mg BIWk) provide a similar steady-state exposure (Nestorov et al. 2004). Therefore, their respective efficacy and safety profiles are likely to be similar as well.

An added feature is the development of a population model involving both PK and PD. Population PK/PD modeling has been used to characterize drug PK and PD with models ranging from simple empirical PK/PD models to advanced mechanistic models by using drug–receptor binding principles or other physiologically based principles. A mechanism-based population PK and PD binding model was developed for a recombinant DNA-derived humanized IgG1 MAB, omalizumab (Hayashi et al. 2007). Clearance and volume of distribution for omalizumab varied with body weight, whereas CL and rate of production of IgE were predicted accurately by baseline IgE, and overall, these covariates explained much of the interindividual variability. Furthermore, this mechanism-based population PK/PD model enabled the estimation of not only omalizumab disposition but also the binding with its target, IgE, and the rate of production, distribution, and elimination of IgE.

Recently, a platform population PK approach has been used to characterize MAB PK to improve the efficiency of study design, such as optimal dose regimens and PK sampling times. Davda et al. (2014) determined typical population PK values for four MABs with linear elimination using model-based meta-analysis, which can be utilized to prospectively optimize FIH study designs. A platform model describing PK properties of vc-MMAE antibody-drug conjugates based on 8 ADCs is reported by Kagedal et al. (2017). The model could be applied to predict PK-profiles of future vc-MMAE ADCs, estimate individual exposure for the subsequent exposure-response analysis, and optimize study design.

Population PK/PD analysis can capture uncertainty and the expected variability in PK/PD data generated in preclinical studies or early phases of clinical development. Understanding the associated PK or PD variability and performing clinical trial simulation by incorporating the uncertainty from the existing PK/PD data allows projecting a plausible range of doses for future clinical studies and final practical uses.

Future Perspective

The success of MABs as new therapeutic agents in several disease areas such as oncology, inflammatory diseases, autoimmune diseases, and transplantation has triggered growing scientific, therapeutic, and business interest in the MAB technology. The market for therapeutic MABs is one of the most dynamic sectors within the pharmaceutical industry. Further growth is expected by developing MABs towards other surface protein targets, which are not covered yet by marketed MABs. Particularly, the technological advancement in the area of ADCs and MAB fragments may overcome some of the limitations of MABs by providing highly potent drugs selectively to target compartments and to extend the distribution of the active moiety, which are typically not reached by MABs. ADCs hold great promise for selective drug delivery of potent drugs with unfavorable own selectivity to target cells (e.g., highly potent cytotoxic drugs). Several of such ADCs are under development to target different tumor types and are expected to reach the market in the next several years. Modification of the MAB structure allows adjusting the properties according to therapeutic needs (e.g., adjusting half-life, increasing volume of distribution, changing clearance pathways). By using modified MAB derivatives, optimized therapeutic agents might become available. For example, this technology has been successfully used for two antibody fragments marketed in inflammatory disease and anti-angiogenesis (abciximab, ranibizumab).

Bispecific antibodies represent another promising new methodological approach to antibody therapy. Technological refinements in antibody engineering have allowed the production of bispecific antibodies that are simultaneously directed towards two distinct target antigens (Holmes 2011). For instance, the CDR consisting of the variable domains (V_L and V_H) at the tip of one arm of an IgG may be asymmetrically designed to bind to a different target than that of the other arm (Fig. 8.1). Symmetrical formats in which each arm can bind two targets are also possible.

MABs have become a key part of the pharmaceutical armamentarium, especially in the oncology and immunology settings and will continue to be a focus area for drug discovery and development. More specifically, the recent approvals of MABs like pembrolizumab, nivolumab and atezolizumab in cancer immunotherapy have revolutionized cancer treatment paradigm. These MABs, either as monotherapy or in combinations with other cancer immunotherapies, including cancer vaccines, bispecifics and other modalities, offer tremendous promise for personalized medicine.

Self-Assessment Questions

■ Questions

1.
What are the structural differences among the five immunoglobulin classes?
2.
What are key differences in PK/PD between MABs and small molecule drugs?
3.
Why do IgGs typically show nonlinear PK in the lower plasma (serum) concentration range?
4.
What is a surrogate MAB and how can it potentially be used in the drug development process of MABs?
5.
Which other modes of actions apart from ADCC—antibody dependent cellular cytotoxicity are known for MABs? What are the key steps of ADCC?
6.
Why do IgGs have a longer in vivo half-life compared with other Igs?
7.
What are the development phases for antibody therapeutics? What major activities are involved in each phase?

■ Answers

1.
The following structural properties distinguish MABs:

The molecular form varies across the five immunoglobulin classes: IgG, IgD, and IgE are monomers; IgM forms a pentamer or hexamer, and IgA exists either as a monomer or dimer. Consequently, the molecular weights of various Igs differ (IgG 150–169 kD, IgA 160–300 kD, IgD 175 kD, IgE 190, IgM 950 kD).
2.
Metabolism of MABs appears to be simpler than for small molecules. In contrast to small molecule drugs, the typical metabolic enzymes and transporter proteins, such as cytochrome P450, multidrug resistance (MDR) efflux pumps, are not involved in the disposition of MABs. Therefore, drug–drug interaction studies for those disposition processes are only part of the standard safety assessment for small molecules and not for MABs.

MABs, which have a protein structure, are metabolized by proteases. These enzymes are ubiquitously available in mammalian organisms. In contrast, small molecule drugs are primarily metabolized in the liver.

Because of their large molecular weight, intact MABs are typically not cleared via the renal elimination route. However, renal clearance processes can play a major role in the elimination of small molecule drugs.

PK of MABs usually is dependent on the binding to the pharmacological target protein and shows nonlinear behavior as consequence of its saturation kinetics.

In general, MABs have a longer half-life (on the order of days and weeks) than small molecule drugs (typically on the order of hours).

The distribution of MABs is very restricted (volume of distribution in the range of 0.1 L/kg). As a consequence, MABs do have limited access to tissue compartments (e.g., brain) as potential target sites via passive, energy-independent distribution processes only.
3.
At lower concentrations, MABs generally show nonlinear PK due to receptor-mediated clearance processes, which are characterized by small capacity of the clearance pathway and high affinity to the target protein. Consequently at these low concentrations, MABs exhibit typically shorter half-life. With increasing doses, these receptors become saturated, and the clearance as well as elimination half-life decreases until it becomes constant. The clearance in the higher concentration range, which is dominated by linear, non target-related clearance processes, is therefore also called nonspecific clearance in contrast to the target-related, specific clearance.
4.
A surrogate MAB has similar antigen specificity and affinity in experimental animals (e.g., mice and rats) compared to those of the corresponding human antibody in humans. It is quite common that the antigen specificity limits ADME studies of humanized MABs in rodents. Studies using surrogate antibodies might lead to important information regarding safety, MOA, disposition of the drug, tissue distribution, and receptor pharmacology in the respective animal species, which might be too cumbersome and expensive to be conducted in nonhuman primates. Surrogate MABs (from mouse or rat) provide a means to gain knowledge of ADME and PD in preclinical rodent models and might facilitate the dose selection for clinical studies.
5.
Apart from ADCC, MABs can exert pharmacological effects by multiple mechanisms that include direct modulation of the target antigen, complement-dependent cytotoxicity (CDC) and apoptosis. The key steps of ADCC are (1) opsonization of the targeted cells, (2) recognition of antibody-coated targeted cells by Fc receptors on the surface of monocytes, macrophages, natural killer cells, and other cells, and (3) destruction of the opsonized targets by phagocytosis of the opsonized targets and/or by toxic substances released after activation of monocytes, macrophages, natural killer cells, and other cells.
6.
IgG can bind to neonatal Fc receptor (FcRn) in the endosome, which protects IgG from catabolism via proteolytic degradation. This protection results into a slower clearance and thus longer plasma half-life of IgGs. Consequently, changing the FcRn affinity allows adjustment of the clearance of MABs (higher affinity—lower clearance), which can be employed to tailor the PK of these molecules.
7.
Pre-IND, phase I, II, III, and IV are the major development phases for antibody therapies. Safety pharmacology, toxicokinetics, toxicology, tissue cross-reactivity, local tolerance, PK support for candidate selection, assay support for PK/PD, and PK/PD support for dose/route/regimen are major activities in the pre-IND phase. General toxicity, reproductive toxicity, carcinogenicity, immunogenicity, characterization of dose–concentration–effect relationship, material comparability studies, mechanistic modeling approach, and population PK/predictions are major activities from phase I to phase III. Further studies might be performed as needed after the MAB got market authorization. These studies are called phase IV studies.

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Rong Deng, Wendy S. Putnam, Meina T. Tang, Amit Garg, Chunze Li & Sandhya Girish
Preclinical and Translational Pharmacokinetics, Genentech Inc., South San Francisco, CA, USA
C. Andrew Boswell
Bioanalytical Sciences, Genentech Inc., South San Francisco, CA, USA
Shan Chung

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Utrecht University, Utrecht, The Netherlands
Daan J. A. Crommelin
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Robert D. Sindelar
College of Pharmacy, University of Tennessee, Health Science Center, Memphis, TN, USA
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Deng, R. et al. (2019). Monoclonal Antibodies: From Structure to Therapeutic Application. In: Crommelin, D., Sindelar, R., Meibohm, B. (eds) Pharmaceutical Biotechnology. Springer, Cham. https://doi.org/10.1007/978-3-030-00710-2_8

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Monoclonal Antibodies: From Structure to Therapeutic Application

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