Heparin chromatography as an in vitro predictor for antibody clearance rate through pinocytosis

Rat as a Predictive Model for Human Clearance and Bioavailability of Monoclonal Antibodies

BACKGROUND

The prediction of human clearance (CL) and subcutaneous (SC) bioavailability is a critical aspect of monoclonal antibody (mAb) selection for clinical development. While monkeys are a well-accepted model for predicting human CL, other preclinical species have been less-thoroughly explored. Unlike CL, predicting the bioavailability of SC administered mAbs in humans remains challenging as contributing factors are not well understood, and preclinical models have not been systematically evaluated.

METHODS

Non-clinical and clinical pharmacokinetic (PK) parameters were mined from public and internal sources for rats, cynomolgus monkeys, and humans. Intravenous (IV) and SC PK was determined in Sprague Dawley rats for fourteen mAbs without existing PK data. Together, we obtained cross-species data for 25 mAbs to evaluate CL and SC bioavailability relationships among rats, monkeys, and humans.

RESULTS

Rat and monkey CL significantly correlated with human CL and supported the use of species-specific exponents for body-weight-based allometric scaling. Notably, rat SC bioavailability significantly correlated with human SC bioavailability, while monkey SC bioavailability did not. Bioavailability also correlated with clearance.

CONCLUSIONS

The rat model enables an early assessment of mAb PK properties, allowing discrimination among molecules in the discovery pipeline and prediction of human PK. Importantly, rat SC bioavailability significantly correlated with human SC bioavailability, which has not been observed with other species. Rats are cost-effective and efficient relative to monkeys and provide a valuable tool for pharmacokinetic predictions in therapeutic antibody discovery.

A minimal physiologically based pharmacokinetic model to study the combined effect of antibody size, charge, and binding affinity to FcRn/antigen on antibody pharmacokinetics

Protein therapeutics have revolutionized the treatment of a wide range of diseases. While they have distinct physicochemical characteristics that influence their absorption, distribution, metabolism, and excretion (ADME) properties, the relationship between the physicochemical properties and PK is still largely unknown. In this work we present a minimal physiologically-based pharmacokinetic (mPBPK) model that incorporates a multivariate quantitative relation between a therapeutic's physicochemical parameters and its corresponding ADME properties. The model's compound-specific input includes molecular weight, molecular size (Stoke's radius), molecular charge, binding affinity to FcRn, and specific antigen affinity. Through derived and fitted empirical relationships, the model demonstrates the effect of these compound-specific properties on antibody disposition in both plasma and peripheral tissues using observed PK data in mice and humans. The mPBPK model applies the two-pore hypothesis to predict size-based clearance and exposure of full-length antibodies (150 kDa) and antibody fragments (50-100 kDa) within a onefold error. We quantitatively relate antibody charge and PK parameters like uptake rate, non-specific binding affinity, and volume of distribution to capture the relatively faster clearance of positively charged mAb as compared to negatively charged mAb. The model predicts the terminal plasma clearance of slightly positively and negatively charged antibody in humans within a onefold error. The mPBPK model presented in this work can be used to predict the target-mediated disposition of a drug when compound-specific and target-specific properties are known. To our knowledge, a combined effect of antibody weight, size, charge, FcRn, and antigen has not been incorporated and studied in a single mPBPK model previously. By conclusively incorporating and relating a multitude of protein's physicochemical properties to observed PK, our mPBPK model aims to contribute as a platform approach in the early stages of drug development where many of these properties can be optimized to improve a molecule's PK and ultimately its efficacy.

Utility of Cellular Measurements of Non-Specific Endocytosis to Assess the Target-Independent Clearance of Monoclonal Antibodies

Past studies have demonstrated higher clearance for monoclonal antibodies possessing increased rates of non-specific endocytosis. However, this metric is oftentimes evaluated indirectly using biophysical techniques or cell surface binding studies that may not provide insight into the specific rates of cellular turnover. Furthermore, few examples evaluating non-specific endocytosis have been reported for a therapeutic antibody that reached clinical assessment. In the current report, we evaluated a therapeutic human immunoglobulin G2 monoclonal antibody targeted against the interleukin-4 receptor alpha chain (IL-4Rα) that exhibited elevated target independent clearance in previous Phase 1 and 2 studies. We confirmed high non-specific clearance of the anti-IL-4Rα antibody as compared to a reference antibody during pharmacokinetic assessments in wild type mice where target-mediated disposition was absent. We then developed a cell-based method capable of measuring cellular protein endocytosis and demonstrated the anti-IL-4Rα antibody exhibited marked non-specific uptake relative to the reference compound. Antibody homology modeling identified the anti-IL-4Rα antibody possessed positive charge patches whose removal via targeted mutations substantially reduced its non-specific endocytosis. We then expanded the scope of the study by evaluating panels of both preclinical and clinically relevant monoclonal antibodies and demonstrate those with the highest rates of non-specific uptake in vitro exhibited elevated target independent clearance, low subcutaneous bioavailability, or both. Our results support the observation that high non-specific endocytosis is a negative attribute in monoclonal antibody development and demonstrate the utility of a generic cell-based screen as a quantitative tool to measure non-specific endocytosis of protein therapeutics at the single-cell level.

DOTAD: A Database of Therapeutic Antibody Developability

The development of therapeutic antibodies is an important aspect of new drug discovery pipelines. The assessment of an antibody's developability-its suitability for large-scale production and therapeutic use-is a particularly important step in this process. Given that experimental assays to assess antibody developability in large scale are expensive and time-consuming, computational methods have been a more efficient alternative. However, the antibody research community faces significant challenges due to the scarcity of readily accessible data on antibody developability, which is essential for training and validating computational models. To address this gap, DOTAD (Database Of Therapeutic Antibody Developability) has been built as the first database dedicated exclusively to the curation of therapeutic antibody developability information. DOTAD aggregates all available therapeutic antibody sequence data along with various developability metrics from the scientific literature, offering researchers a robust platform for data storage, retrieval, exploration, and downloading. In addition to serving as a comprehensive repository, DOTAD enhances its utility by integrating a web-based interface that features state-of-the-art tools for the assessment of antibody developability. This ensures that users not only have access to critical data but also have the convenience of analyzing and interpreting this information. The DOTAD database represents a valuable resource for the scientific community, facilitating the advancement of therapeutic antibody research. It is freely accessible at http://i.uestc.edu.cn/DOTAD/ , providing an open data platform that supports the continuous growth and evolution of computational methods in the field of antibody development.

Cellular Neonatal Fc Receptor Recycling Efficiencies can Differentiate Target-Independent Clearance Mechanisms of Monoclonal Antibodies

In vivo clearance mechanisms of therapeutic monoclonal antibodies (mAbs) encompass both target-mediated and target-independent processes. Two distinct determinants of overall mAb clearance largely separate of target-mediated influences are non-specific cellular endocytosis and subsequent pH-dependent mAb recycling mediated by the neonatal Fc receptor (FcRn), where inter-mAb variability in the efficiency of both processes is observed. Here, we implemented a functional cell-based FcRn recycling assay via Madin-Darby canine kidney type II cells stably co-transfected with human FcRn and its light chain β2-microglobulin. Next, a series of pH-dependent internalization studies using a model antibody demonstrated proper function of the human FcRn complex. We then applied our cellular assays to assess the contribution of both FcRn and non-specific interactions in the cellular turnover for a panel of 8 clinically relevant mAbs exhibiting variable human pharmacokinetic behavior. Our results demonstrate that the interplay of non-specific endocytosis rates, pH-dependent non-specific interactions, and engagement with FcRn all contribute to the overall recycling efficiency of therapeutic monoclonal antibodies. The predictive capacity of our assay approach was highlighted by successful identification of all mAbs within our panel possessing clearance in humans greater than 5 mL/day/kg. These results demonstrate that a combination of cell-based in vitro assays can properly resolve individual mechanisms underlying the overall in vivo recycling efficiency and non-target mediated clearance of therapeutic mAbs.

Internalization of therapeutic antibodies into dendritic cells as a risk factor for immunogenicity

Introduction

Immunogenicity, the unwanted immune response triggered by therapeutic antibodies, poses significant challenges in biotherapeutic development. This response can lead to the production of anti-drug antibodies, potentially compromising the efficacy and safety of treatments. The internalization of therapeutic antibodies into dendritic cells (DCs) is a critical factor influencing immunogenicity. Using monoclonal antibodies, with differences in non-specific cellular uptake, as tools to explore the impact on the overall risk of immunogenicity, this study explores how internalization influences peptide presentation and subsequently T cell activation.

Materials and methods

To investigate the impact of antibody internalization on immunogenicity, untargeted toolantibodies with engineered positive or negative charge patches were utilized. Immature monocyte-derived DCs (moDCs), known for their physiologically relevant high endocytic activity, were employed for internalization assays, while mature moDCs were used for MHC-II associated peptide proteomics (MAPPs) assays. In addition to the lysosomal accumulation and peptide presentation, subsequent CD4+ T cell activation has been assessed. Consequently, a known CD4+ T cell epitope from ovalbumin was inserted into the tool antibodies to evaluate T cell activation on a single, shared epitope.

Results

Antibodies with positive charge patches exhibited higher rates of lysosomal accumulation and epitope presentation compared to those with negative charge patches or neutral surface charge. Furthermore, a direct correlation between internalization rate and presentation on MHC-II molecules could be established. To explore the link between internalization, peptide presentation and CD4+ T cell activation, tool antibodies containing the same OVA epitope were used. Previous observations were not altered by the insertion of the OVA epitope and ultimately, an enhanced CD4+ T cell response correlated with increased internalization in DCs and peptide presentation.

Discussion

These findings demonstrate that the biophysical properties of therapeutic antibodies, particularly surface charge, play a crucial role in their internalization into DCs. Antibodies internalized faster and processed by DCs, are also more prone to be presented on their surface leading to a higher risk of triggering an immune response. These insights underscore the importance of considering antibody surface charge and other properties that enhance cellular accumulation during the preclinical development of biotherapeutics to mitigate immunogenicity risks.

A Physiologically Based Pharmacokinetic Model Relates the Subcutaneous Bioavailability of Monoclonal Antibodies to the Saturation of FcRn-Mediated Recycling in Injection-Site-Draining Lymph Nodes

The bioavailability of a monoclonal antibody (mAb) or another therapeutic protein after subcutaneous (SC) dosing is challenging to predict from first principles, even if the impact of injection site physiology and drug properties on mAb bioavailability is generally understood. We used a physiologically based pharmacokinetic model to predict pre-systemic clearance after SC administration mechanistically by incorporating the FcRn salvage pathway in antigen-presenting cells (APCs) in peripheral lymph nodes, draining the injection site. Clinically observed data of the removal rate of IgG from the arm as well as its plasma concentration after SC dosing were mostly predicted within the 95% confidence interval. The bioavailability of IgG was predicted to be 70%, which mechanistically relates to macropinocytosis in the draining lymph nodes and transient local dose-dependent partial saturation of the FcRn receptor in the APCs, resulting in higher catabolism and consequently less drug reaching the systemic circulation. The predicted free FcRn concentration was reduced to 40-45%, reaching the minimum 1-2 days after the SC administration of IgG, and returned to baseline after 8-12 days, depending on the site of injection. The model predicted the uptake into APCs, the binding affinity to FcRn, and the dose to be important factors impacting the bioavailability of a mAb.

Long-Acting Strategies for Antibody Drugs: Structural Modification, Controlling Release, and Changing the Administration Route

Because of their high specificity, high affinity, and targeting, antibody drugs have been widely used in the treatment of many diseases and have become the most favored new drugs for research in the world. However, some antibody drugs (such as small-molecule antibody fragments) have a short half-life and need to be administered frequently, and are often associated with injection-site reactions and local toxicities during use. Increasing attention has been paid to the development of antibody drugs that are long-acting and have fewer side effects. This paper reviews existing strategies to achieve long-acting antibody drugs, including modification of the drug structure, the application of drug delivery systems, and changing their administration route. Among these, microspheres have been studied extensively regarding their excellent tolerance at the injection site, controllable loading and release of drugs, and good material safety. Subcutaneous injection is favored by most patients because it can be quickly self-administered. Subcutaneous injection of microspheres is expected to become the focus of developing long-lasting antibody drug strategies in the near future.

Characterization of antibody surface properties and selection of a diverse subset for development of a generic size-exclusion chromatography method

Aggregates are an important quality attribute for biotherapeutics because they can affect the safety and efficacy of the drug and they are therefore routinely monitored, mainly with size-exclusion chromatography (SEC). However, there is often a need to tailor a SEC method to a specific molecule. This study describes the development of a generic SEC method tested on 138 antibodies with the variable domains taken from clinical stage antibodies. We report on the discovery of a subset of 12 antibodies that represents the full range of physiochemical properties found in the 138 antibodies. This subset is shown to be an efficient and reliable test set when developing chromatographic methods for antibodies. An understanding of the nature of the analyte-stationary phase interactions was gained when using this set with its wide range of physiochemical properties. Highly hydrophobic antibodies interact strongly with some modern silica hybrid materials causing the elution time to increase significantly, while a hydrophilically modified hybrid surface showed highly reduced interactions for the hydrophobic antibodies. Highly hydrophilic antibodies, on the other hand, exhibited asymmetric peaks to a certain extent on all stationary phases, while the elution time was not affected. The developed SEC method was shown to have satisfactory performance in terms of linearity, repeatability, range, and accuracy and exhibit very narrow distributions of elution time and peak symmetry when testing the 138 antibodies indicating its generic performance.

Molecular surface descriptors to predict antibody developability: sensitivity to parameters, structure models, and conformational sampling

In silico assessment of antibody developability during early lead candidate selection and optimization is of paramount importance, offering a rapid and material-free screening approach. However, the predictive power and reproducibility of such methods depend heavily on the selection of molecular descriptors, model parameters, accuracy of predicted structure models, and conformational sampling techniques. Here, we present a set of molecular surface descriptors specifically designed for predicting antibody developability. We assess the performance of these descriptors by benchmarking their correlations with an extensive array of experimentally determined biophysical properties, including viscosity, aggregation, hydrophobic interaction chromatography, human pharmacokinetic clearance, heparin retention time, and polyspecificity. Further, we investigate the sensitivity of these surface descriptors to methodological nuances, such as the choice of interior dielectric constant, hydrophobicity scales, structure prediction methods, and the impact of conformational sampling. Notably, we observe systematic shifts in the distribution of surface descriptors depending on the structure prediction method used, driving weak correlations of surface descriptors across structure models. Averaging the descriptor values over conformational distributions from molecular dynamics mitigates the systematic shifts and improves the consistency across different structure prediction methods, albeit with inconsistent improvements in correlations with biophysical data. Based on our benchmarking analysis, we propose six in silico developability risk flags and assess their effectiveness in predicting potential developability issues for a set of case study molecules.

Exploring molecular determinants and pharmacokinetic properties of IgG1-scFv bispecific antibodies

Bispecific antibodies (BsAbs) capable of recognizing two distinct epitopes or antigens offer promising therapeutic options for various diseases by targeting multiple pathways. The favorable pharmacokinetic (PK) properties of monoclonal antibodies (mAbs) are crucial, as they directly influence patient safety and therapeutic efficacy. For numerous mAb therapeutics, optimization of neonatal Fc receptor (FcRn) interactions and elimination of unfavorable molecular properties have led to improved PK properties. However, many BsAbs exhibit unfavorable PK, which has precluded their development as drugs. In this report, we present studies on the molecular determinants underlying the distinct PK profiles of three IgG1-scFv BsAbs. Our study indicated that high levels of nonspecific interactions, elevated isoelectric point (pI), and increased number of positively charged patches contributed to the fast clearance of IgG1-scFv. FcRn chromatography results revealed specific scFv-FcRn interactions that are unique to the IgG1-scFv, which was further supported by molecular dynamics (MD) simulation. These interactions likely stabilize the BsAb FcRn interaction at physiological pH, which in turn could disrupt FcRn-mediated BsAb recycling. In addition to the empirical observations, we also evaluated the impact of in silico properties, including pI differential between the Fab and scFv and the ratio of dipole moment to hydrophobic moment (RM) and their correlation with the observed clearance. These findings highlight that the PK properties of BsAbs may be governed by novel determinants, owing to their increased structural complexity compared to immunoglobulin G (IgG) 1 antibodies.

Assessment and incorporation of in vitro correlates to pharmacokinetic outcomes in antibody developability workflows

In vitro assessments for the prediction of pharmacokinetic (PK) behavior of biotherapeutics can help identify corresponding liabilities significantly earlier in the discovery timeline. This can minimize the need for extensive early in vivo PK characterization, thereby reducing animal usage and optimizing resources. In this study, we recommend bolstering classical developability workflows with in vitro measures correlated with PK. In agreement with current literature, in vitro measures assessing nonspecific interactions, self-interaction, and FcRn interaction are demonstrated to have the highest correlations to clearance in hFcRn Tg32 mice. Crucially, the dataset used in this study has broad sequence diversity and a range of physicochemical properties, adding robustness to our recommendations. Finally, we demonstrate a computational approach that combines multiple in vitro measurements with a multivariate regression model to improve the correlation to PK compared to any individual assessment. Our work demonstrates that a judicious choice of high throughput in vitro measurements and computational predictions enables the prioritization of candidate molecules with desired PK properties.

Nonspecificity fingerprints for clinical-stage antibodies in solution

Monoclonal antibodies (mAbs) have successfully been developed for the treatment of a wide range of diseases. The clinical success of mAbs does not solely rely on optimal potency and safety but also require good biophysical properties to ensure a high developability potential. In particular, nonspecific interactions are a key developability parameter to monitor during discovery and development. Despite an increased focus on the detection of nonspecific interactions, their underlying physicochemical origins remain poorly understood. Here, we employ solution-based microfluidic technologies to characterize a set of clinical-stage mAbs and their interactions with commonly used nonspecificity ligands to generate nonspecificity fingerprints, providing quantitative data on the underlying physical chemistry. Furthermore, the solution-based analysis enables us to measure binding affinities directly, and we evaluate the contribution of avidity in nonspecific binding by mAbs. We find that avidity can increase the apparent affinity by two orders of magnitude. Notably, we find that a subset of these highly developed mAbs show nonspecific electrostatic interactions, even at physiological pH and ionic strength, and that they can form microscale particles with charge-complementary polymers. The group of mAb constructs flagged here for nonspecificity are among the worst performers in independent reports of surface and column-based screens. The solution measurements improve on the state-of-the-art by providing a stand-alone result for individual mAbs without the need to benchmark against cohort data. Based on our findings, we propose a quantitative solution-based nonspecificity score, which can be integrated in the development workflow for biological therapeutics and more widely in protein engineering.

PEP-Patch: Electrostatics in Protein-Protein Recognition, Specificity, and Antibody Developability

The electrostatic properties of proteins arise from the number and distribution of polar and charged residues. Electrostatic interactions in proteins play a critical role in numerous processes such as molecular recognition, protein solubility, viscosity, and antibody developability. Thus, characterizing and quantifying electrostatic properties of a protein are prerequisites for understanding these processes. Here, we present PEP-Patch, a tool to visualize and quantify the electrostatic potential on the protein surface in terms of surface patches, denoting separated areas of the surface with a common physical property. We highlight its applicability to elucidate protease substrate specificity and antibody-antigen recognition and predict heparin column retention times of antibodies as an indicator of pharmacokinetics.

Physiologically Based Pharmacokinetic Modeling to Characterize the Effect of Molecular Charge on Whole-Body Disposition of Monoclonal Antibodies

Motivated by a series of work demonstrating the effect of molecular charge on antibody pharmacokinetics (PK), physiological-based pharmacokinetic (PBPK) models are emerging that relate in silico calculated charge or in vitro measures of polyspecificity to antibody PK parameters. However, only plasma data has been used for model development in these studies, leading to unvalidated assumptions. Here, we present an extended platform PBPK model for antibodies that incorporate charge-dependent endothelial cell pinocytosis rate and nonspecific off-target binding in the interstitial space and on circulating blood cells, to simultaneously characterize whole-body disposition of three antibody charge variants. Predictive potential of various charge metrics was also explored, and the difference between positive charge patches and negative charge patches (i.e., PPC-PNC) was used as the charge parameter to establish quantitative relationships with nonspecific binding affinities and endothelial cell uptake rate. Whole-body disposition of these charge variants was captured well by the model, with less than 2-fold predictive error in area under the curve of most plasma and tissue PK data. The model also predicted that with greater positive charge, nonspecific binding was more substantial, and pinocytosis rate increased especially in brain, heart, kidney, liver, lung, and spleen, but remained unchanged in adipose, bone, muscle, and skin. The presented PBPK model contributes to our understanding of the mechanisms governing the disposition of charged antibodies and can be used as a platform to guide charge engineering based on desired plasma and tissue exposures.

Surface patches induce nonspecific binding and phase separation of antibodies

Nonspecific interactions are a key challenge in the successful development of therapeutic antibodies. The tendency for nonspecific binding of antibodies is often difficult to reduce by rational design, and instead, it is necessary to rely on comprehensive screening campaigns. To address this issue, we performed a systematic analysis of the impact of surface patch properties on antibody nonspecificity using a designer antibody library as a model system and single-stranded DNA as a nonspecificity ligand. Using an in-solution microfluidic approach, we find that the antibodies tested bind to single-stranded DNA with affinities as high as KD = 1 µM. We show that DNA binding is driven primarily by a hydrophobic patch in the complementarity-determining regions. By quantifying the surface patches across the library, the nonspecific binding affinity is shown to correlate with a trade-off between the hydrophobic and total charged patch areas. Moreover, we show that a change in formulation conditions at low ionic strengths leads to DNA-induced antibody phase separation as a manifestation of nonspecific binding at low micromolar antibody concentrations. We highlight that phase separation is driven by a cooperative electrostatic network assembly mechanism of antibodies with DNA, which correlates with a balance between positive and negative charged patches. Importantly, our study demonstrates that both nonspecific binding and phase separation are controlled by the size of the surface patches. Taken together, these findings highlight the importance of surface patches and their role in conferring antibody nonspecificity and its macroscopic manifestation in phase separation.

Identifying developability risks for clinical progression of antibodies using high-throughput in vitro and in silico approaches

With the growing significance of antibodies as a therapeutic class, identifying developability risks early during development is of paramount importance. Several high-throughput in vitro assays and in silico approaches have been proposed to de-risk antibodies during early stages of the discovery process. In this review, we have compiled and collectively analyzed published experimental assessments and computational metrics for clinical antibodies. We show that flags assigned based on in vitro measurements of polyspecificity and hydrophobicity are more predictive of clinical progression than their in silico counterparts. Additionally, we assessed the performance of published models for developability predictions on molecules not used during model training. We find that generalization to data outside of those used for training remains a challenge for models. Finally, we highlight the challenges of reproducibility in computed metrics arising from differences in homology modeling, in vitro assessments relying on complex reagents, as well as curation of experimental data often used to assess the utility of high-throughput approaches. We end with a recommendation to enable assay reproducibility by inclusion of controls with disclosed sequences, as well as sharing of structural models to enable the critical assessment and improvement of in silico predictions.

SUMO: In Silico Sequence Assessment Using Multiple Optimization Parameters

To select the most promising screening hits from antibody and VHH display campaigns for subsequent in-depth profiling and optimization, it is highly desirable to assess and select sequences on properties beyond only their binding signals from the sorting process. In addition, developability risk criteria, sequence diversity, and the anticipated complexity for sequence optimization are relevant attributes for hit selection and optimization. Here, we describe an approach for the in silico developability assessment of antibody and VHH sequences. This method not only allows for ranking and filtering multiple sequences with regard to their predicted developability properties and diversity, but also visualizes relevant sequence and structural features of potentially problematic regions and thereby provides rationales and starting points for multi-parameter sequence optimization.

Assessing developability early in the discovery process for novel biologics

Beyond potency, a good developability profile is a key attribute of a biological drug. Selecting and screening for such attributes early in the drug development process can save resources and avoid costly late-stage failures. Here, we review some of the most important developability properties that can be assessed early on for biologics. These include the influence of the source of the biologic, its biophysical and pharmacokinetic properties, and how well it can be expressed recombinantly. We furthermore present in silico, in vitro, and in vivo methods and techniques that can be exploited at different stages of the discovery process to identify molecules with liabilities and thereby facilitate the selection of the most optimal drug leads. Finally, we reflect on the most relevant developability parameters for injectable versus orally delivered biologics and provide an outlook toward what general trends are expected to rise in the development of biologics.

Structure-Based Optimization of Antibody-Based Biotherapeutics for Improved Developability: A Practical Guide for Molecular Modelers

A great effort to avoid known developability risks is now more often being made earlier during the lead candidate discovery and optimization phase of biotherapeutic drug development. Predictive computational strategies, used in the early stages of antibody discovery and development, to mitigate the risk of late-stage failure of antibody candidates, are highly valuable. Various structure-based methods exist for accurately predicting properties critical to developability, and, in this chapter, we discuss the history of their development and demonstrate how they can be used to filter large sets of candidates arising from target affinity screening and to optimize lead candidates for developability. Methods for modeling antibody structures from sequence and detecting post-translational modifications and chemical degradation liabilities are also discussed.

Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies

Biologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration-time curve (AUC0-672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL.

Utility of physiologically based pharmacokinetic modeling to predict inter-antibody variability in monoclonal antibody pharmacokinetics in mice

In this investigation, we tested the hypothesis that a physiologically based pharmacokinetic (PBPK) model incorporating measured in vitro metrics of off-target binding can largely explain the inter-antibody variability in monoclonal antibody (mAb) pharmacokinetics (PK). A diverse panel of 83 mAbs was evaluated for PK in wild-type mice and subjected to 10 in vitro assays to measure major physiochemical attributes. After excluding for target-mediated elimination and immunogenicity, 56 of the remaining mAbs with an eight-fold variability in the area under the curve (A U C 0 - 672 h : 1.74 × 106 -1.38 × 107 ng∙h/mL) and 10-fold difference in clearance (2.55-26.4 mL/day/kg) formed the training set for this investigation. Using a PBPK framework, mAb-dependent coefficients F1 and F2 modulating pinocytosis rate and convective transport, respectively, were estimated for each mAb with mostly good precision (coefficient of variation (CV%) <30%). F1 was estimated to be the mean and standard deviation of 0.961 ± 0.593, and F2 was estimated to be 2.13 ± 2.62. Using principal component analysis to correlate the regressed values of F1/F2 versus the multidimensional dataset composed of our panel of in vitro assays, we found that heparin chromatography retention time emerged as the predictive covariate to the mAb-specific F1, whereas F2 variability cannot be well explained by these assays. A sigmoidal relationship between F1 and the identified covariate was incorporated within the PBPK framework. A sensitivity analysis suggested plasma concentrations to be most sensitive to F1 when F1 > 1. The predictive utility of the developed PBPK model was evaluated against a separate panel of 14 mAbs biased toward high clearance, among which area under the curve of PK data of 12 mAbs was predicted within 2.5-fold error, and the positive and negative predictive values for clearance prediction were 85% and 100%, respectively. MAb heparin chromatography assay output allowed a priori identification of mAb candidates with unfavorable PK.

Structure-based engineering of a novel CD3ε-targeting antibody for reduced polyreactivity

Bispecific antibodies continue to represent a growth area for antibody therapeutics, with roughly a third of molecules in clinical development being T-cell engagers that use an anti-CD3 binding arm. CD3 antibodies possessing cross-reactivity with cynomolgus monkey typically recognize a highly electronegative linear epitope at the extreme N-terminus of CD3 epsilon (CD3ε). Such antibodies have high isoelectric points and display problematic polyreactivity (correlated with poor pharmacokinetics for monospecific antibodies). Using insights from the crystal structure of anti-Hu/Cy CD3 antibody ADI-26906 in complex with CD3ε and antibody engineering using a yeast-based platform, we have derived high-affinity CD3 antibody variants with very low polyreactivity and significantly improved biophysical developability. Comparison of these variants with CD3 antibodies in the clinic (as part of bi- or multi-specifics) shows that affinity for CD3 is correlated with polyreactivity. Our engineered CD3 antibodies break this correlation, forming a broad affinity range with no to low polyreactivity. Such antibodies will enable bispecifics with improved pharmacokinetic and safety profiles and suggest engineering solutions that will benefit the large and growing sector of T-cell engagers.

Blueprint for antibody biologics developability

Large-molecule antibody biologics have revolutionized medicine owing to their superior target specificity, pharmacokinetic and pharmacodynamic properties, safety and toxicity profiles, and amenability to versatile engineering. In this review, we focus on preclinical antibody developability, including its definition, scope, and key activities from hit to lead optimization and selection. This includes generation, computational and in silico approaches, molecular engineering, production, analytical and biophysical characterization, stability and forced degradation studies, and process and formulation assessments. More recently, it is apparent these activities not only affect lead selection and manufacturability, but ultimately correlate with clinical progression and success. Emerging developability workflows and strategies are explored as part of a blueprint for developability success that includes an overview of the four major molecular properties that affect all developability outcomes: 1) conformational, 2) chemical, 3) colloidal, and 4) other interactions. We also examine risk assessment and mitigation strategies that increase the likelihood of success for moving the right candidate into the clinic.

Non-specificity as the sticky problem in therapeutic antibody development

Antibodies are highly potent therapeutic scaffolds with more than a hundred different products approved on the market. Successful development of antibody-based drugs requires a trade-off between high target specificity and target binding affinity. In order to better understand this problem, we here review non-specific interactions and explore their fundamental physicochemical origins. We discuss the role of surface patches - clusters of surface-exposed amino acid residues with similar physicochemical properties - as inducers of non-specific interactions. These patches collectively drive interactions including dipole-dipole, π-stacking and hydrophobic interactions to complementary moieties. We elucidate links between these supramolecular assembly processes and macroscopic development issues, such as decreased physical stability and poor in vivo half-life. Finally, we highlight challenges and opportunities for optimizing protein binding specificity and minimizing non-specificity for future generations of therapeutics.

Radiolabelling small and biomolecules for tracking and monitoring

Radiolabelling small molecules with beta-emitters has been intensively explored in the last decades and novel concepts for the introduction of radionuclides continue to be reported regularly. New catalysts that induce carbon/hydrogen activation are able to incorporate isotopes such as deuterium or tritium into small molecules. However, these established labelling approaches have limited applicability for nucleic acid-based drugs, therapeutic antibodies, or peptides, which are typical of the molecules now being investigated as novel therapeutic modalities. These target molecules are usually larger (significantly >1 kDa), mostly multiply charged, and often poorly soluble in organic solvents. However, in preclinical research they often require radiolabelling in order to track and monitor drug candidates in metabolism, biotransformation, or pharmacokinetic studies. Currently, the most established approach to introduce a tritium atom into an oligonucleotide is based on a multistep synthesis, which leads to a low specific activity with a high level of waste and high costs. The most common way of tritiating peptides is using appropriate precursors. The conjugation of a radiolabelled prosthetic compound to a functional group within a protein sequence is a commonly applied way to introduce a radionuclide or a fluorescent tag into large molecules. This review highlights the state-of-the-art in different radiolabelling approaches for oligonucleotides, peptides, and proteins, as well as a critical assessment of the impact of the label on the properties of the modified molecules. Furthermore, applications of radiolabelled antibodies in biodistribution studies of immune complexes and imaging of brain targets are reported.

Minimal Physiologically-based Pharmacokinetic Model to Investigate the Effect of Charge on the Pharmacokinetics of Humanized anti-HCV-E2 IgG Antibodies in Sprague-Dawley Rats

PURPOSE

To develop a minimal physiologically-based pharmacokinetic (mPBPK) model in quantifying the relationships between the charge and pharmacokinetics (PK) of therapeutic monoclonal IgG antibody (TMAb).

METHODS

PK data used in this study were native IgG and five humanized anti-HCVE2-IgG antibodies in rats. Different models that related the effect of charge on interstitial distribution, transcapillary transport, and cellular uptake for FcRn-mediated metabolism were tested. External validation was conducted to assess if the charge-parameter relationships derived from rats could be used to predict the PK of TMAbs in mice. The final mPBPK model was used to construct the relationships between the FcRn binding and charge on the PK of TMAbs.

RESULTS

Increasing the isoelectric point (pI) of IgG was associated with higher interstitial space distribution and cellular uptake. The transcapillary transport of IgG from plasma to interstitial space remains constant with pI values below 7.96 and then increased linearly with pI. The model-based simulation results suggested that improving the FcRn binding affinity can overcome the problems of low plasma/interstitial space exposures associated with TMAbs with higher pI values by reducing the FcRn-mediated metabolism and hence increasing drug exposure in the interstitial space that has close contact with many solid tumors.

CONCLUSIONS

The final mPBPK model was developed and used to construct complex quantitative relationships between the pI/FcRn binding affinity and PK of TMAbs and such relationships are useful to select the discovery of a "sweet spot" of designing future generation of TMAbs with optimal PK properties to achieve desirable plasma and tissue drug exposures.

Impact of charge patches on tumor disposition and biodistribution of therapeutic antibodies

This study explores the impact of antibody surface charge on tissue distribution into various tissues including tumor. Tumor-bearing mice were dosed intravenously with a mixture comprising three antibodies engineered to carry negative charge patches, a balanced charge distribution, or positive patches, respectively (cassette dosing). Tissue levels were analyzed with a specific LC-MS/MS method. In addition, the antibody mix was administered to non-tumor bearing mice. Muscle and skin interstitial fluid were obtained by centrifugation and analyzed by LC-MS/MS. An in vitro endothelium model was explored for its feasibility to mimic the observed distribution differences.

A balanced charge distribution was optimal in terms of total tumor exposure, while in other tissues, negatively charged and balanced charged antibodies gave similar results. In contrast, positive charge patches generally resulted in increased serum clearance but markedly enhanced tumor and organ uptake, leading to higher tissue-to-serum ratios. The uptake and availability in the interstitial space were confirmed by specific assessment of antibody levels in the interstitial fluid of the muscle and skin, with similar charge impact as in total tissue. The in vitro model was able to differentiate the transport propensity of this series of antibody variants. In summary, our results show the differential effects of charge patches on an antibody surface on biodistribution and tumor uptake. These insights may help in the design of molecules with biodistribution properties tailored to their purpose, and an optimized safety profile.

Human Antibodies for Viral Infections

Antibodies have been used to prevent or treat viral infections since the nineteenth century, but the full potential to use passive immunization for infectious diseases has yet to be realized. The advent of efficient methods for isolating broad and potently neutralizing human monoclonal antibodies is enabling us to develop antibodies with unprecedented activities. The discovery of IgG Fc region modifications that extend antibody half-life in humans to three months or more suggests that antibodies could become the principal tool with which we manage future viral epidemics. Antibodies for members of most virus families that cause severe disease in humans have been isolated, and many of them are in clinical development, an area that has accelerated during the effort to prevent or treat COVID-19 (coronavirus disease 2019). Broad and potently neutralizing antibodies are also important research reagents for identification of protective epitopes that can be engineered into active vaccines through structure-based reverse vaccinology. Expected final online publication date for the Annual Review of Immunology, Volume 40 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Physiologically Based Modeling to Predict Monoclonal Antibody Pharmacokinetics in Humans from in vitro Physiochemical Properties

A model-based framework is presented to predict monoclonal antibody (mAb) pharmacokinetics (PK) in humans based on in vitro measures of antibody physiochemical properties. A physiologically based pharmacokinetic (PBPK) model is used to explore the predictive potential of 14 in vitro assays designed to measure various antibody physiochemical properties, including nonspecific cell-surface interactions, FcRn binding, thermal stability, hydrophobicity, and self-association. Based on the mean plasma PK time course data of 22 mAbs from humans reported in the literature, we found a significant positive correlation (R = 0.64, p = .0013) between the model parameter representing antibody-specific vascular to endothelial clearance and heparin relative retention time, an in vitro measure of nonspecific binding. We also found that antibody-specific differences in paracellular transport due to convection and diffusion could be partially explained by antibody heparin relative retention time (R = 0.52, p = .012). Other physiochemical properties, including antibody thermal stability, hydrophobicity, cross-interaction and self-association, in and of themselves were not predictive of model-based transport parameters. In contrast to other studies that have reported empirically derived expressions relating in vitro measures of antibody physiochemical properties directly to antibody clearance, the proposed PBPK model-based approach for predicting mAb PK incorporates fundamental mechanisms governing antibody transport and processing, informed by in vitro measures of antibody physiochemical properties, and can be expanded to include more descriptive representations of each of the antibody processing subsystems, as well as other antibody-specific information.

Non-human primates in the PKPD evaluation of biologics: Needs and options to reduce, refine, and replace. A BioSafe White Paper

Monoclonal antibodies (mAbs) deliver great benefits to patients with chronic and/or severe diseases thanks to their strong specificity to the therapeutic target. As a result of this specificity, non-human primates (NHP) are often the only preclinical species in which therapeutic antibodies cross-react with the target. Here, we highlight the value and limitations that NHP studies bring to the design of safe and efficient early clinical trials. Indeed, data generated in NHPs are integrated with in vitro information to predict the concentration/effect relationship in human, and therefore the doses to be tested in first-in-human trials. The similarities and differences in the systems defining the pharmacokinetics and pharmacodynamics (PKPD) of mAbs in NHP and human define the nature and the potential of the preclinical investigations performed in NHPs. Examples have been collated where the use of NHP was either pivotal to the design of the first-in-human trial or, inversely, led to the termination of a project prior to clinical development. The potential impact of immunogenicity on the results generated in NHPs is discussed. Strategies to optimize the use of NHPs for PKPD purposes include the addition of PD endpoints in safety assessment studies and the potential re-use of NHPs after non-terminal studies or cassette dosing several therapeutic agents of interest. Efforts are also made to reduce the use of NHPs in the industry through the use of in vitro systems, alternative in vivo models, and in silico approaches. In the case of prediction of ocular PK, the body of evidence gathered over the last two decades renders the use of NHPs obsolete. Expert perspectives, advantages, and pitfalls with these alternative approaches are shared in this review.

Novel In Vivo and In Vitro Pharmacokinetic/Pharmacodynamic-Based Human Starting Dose Selection for Glofitamab

We present a novel approach for first-in-human (FIH) dose selection of the CD20xCD3 bispecific antibody, glofitamab, based on pharmacokinetic/pharmacodynamic (PKPD) assessment in cynomolgus monkeys to select a high, safe starting dose, with cytokine release (CR) as the PD endpoint. Glofitamab pharmacokinetics were studied in mice and cynomolgus monkeys; PKPD of IL-6, TNF-α and interferon-γ release following glofitamab, with/without obinutuzumab pretreatment (Gpt) was studied in cynomolgus monkeys. Potency differences for CR between cynomolgus monkeys and humans were determined by glofitamab incubation in whole blood of both species. The PKPD model for CR was translated to humans to project a starting dose that did not induce CR exceeding a clinically-predefined threshold. In cynomolgus monkeys, glofitamab showed a species-specific atypical high clearance, with and without B-cell debulking by Gpt. CR was related to glofitamab serum levels and B-cell counts. B-cell reduction by Gpt led to a marked decrease in CR. FIH starting dose (5 µg) was selected based on IL-6 release considering the markedly higher glofitamab in vitro potency in human vs monkey blood. This is a novel PKPD-based approach for selection of FIH starting dose for a CD20xCD3 bispecific antibody in B-cell lymphoma, evidenced in the glofitamab study, NP30179 (NCT03075696).

Pharmacokinetic Engineering of OX40-Blocking Anticalin Proteins Using Monomeric Plasma Half-Life Extension Domains

Anticalin^® proteins have been proven as versatile clinical stage biotherapeutics. Due to their small size (∼20 kDa), they harbor a short intrinsic plasma half-life which can be extended, e.g., by fusion with IgG or Fc. However, for antagonism of co-immunostimulatory Tumor Necrosis Factor Receptor Superfamily (TNFRSF) members in therapy of autoimmune and inflammatory diseases, a monovalent, pharmacokinetically optimized Anticalin protein format that avoids receptor clustering and therefore potential activation is favored. We investigated the suitability of an affinity-improved streptococcal Albumin-Binding Domain (ABD) and the engineered Fab-selective Immunoglobulin-Binding Domain (IgBD) SpGC3Fab for plasma Half-Life Extension (HLE) of an OX40-specific Anticalin and bispecific Duocalin proteins, neutralizing OX40 and a second co-immunostimulatory TNFRSF member. The higher affinity of ABD fusion proteins to human serum albumin (HSA) and Mouse Serum Albumin (MSA), with a 4 to 5-order of magnitude lower K_D compared with the binding affinity of IgBD fusions to human/mouse IgG, translated into longer terminal plasma half-lives (t_1/2). Hence, the anti-OX40 Anticalin-ABD protein reached t_1/2 values of ∼40 h in wild-type mice and 110 h in hSA/hFcRn double humanized mice, in contrast to ∼7 h observed for anti-OX40 Anticalin-IgBD in wild-type mice. The pharmacokinetics of an anti-OX40 Anticalin-Fc fusion protein was the longest in both models (t_1/2 of 130 h and 146 h, respectively). Protein formats composed of two ABDs or IgBDs instead of one single HLE domain clearly showed longer presence in the circulation. Importantly, Anticalin-ABD and -IgBD fusions showed OX40 receptor binding and functional competition with OX40L-induced cellular reactivity in the presence of albumin or IgG, respectively. Our results suggest that fusion to ABD or IgBD can be a versatile platform to tune the plasma half-life of Anticalin proteins in response to therapeutic needs.

Viro-antibody therapy: engineering oncolytic viruses for genetic delivery of diverse antibody-based biotherapeutics

Cancer therapeutics approved for clinical application include oncolytic viruses and antibodies, which evolved by nature, but were improved by molecular engineering. Both facilitate outstanding tumor selectivity and pleiotropic activities, but also face challenges, such as tumor heterogeneity and limited tumor penetration. An innovative strategy to address these challenges combines both agents in a single, multitasking therapeutic, i.e., an oncolytic virus engineered to express therapeutic antibodies. Such viro-antibody therapies genetically deliver antibodies to tumors from amplified virus genomes, thereby complementing viral oncolysis with antibody-defined therapeutic action. Here, we review the strategies of viro-antibody therapy that have been pursued exploiting diverse virus platforms, antibody formats, and antibody-mediated modes of action. We provide a comprehensive overview of reported antibody-encoding oncolytic viruses and highlight the achievements of 13 years of viro-antibody research. It has been shown that functional therapeutic antibodies of different formats can be expressed in and released from cancer cells infected with different oncolytic viruses. Virus-encoded antibodies have implemented direct tumor cell killing, anti-angiogenesis, or activation of adaptive immune responses to kill tumor cells, tumor stroma cells or inhibitory immune cells. Importantly, numerous reports have shown therapeutic activity complementary to viral oncolysis for these modalities. Also, challenges for future research have been revealed. Established engineering technologies for both oncolytic viruses and antibodies will enable researchers to address these challenges, facilitating the development of effective viro-antibody therapeutics.

Effect of variable domain charge on in vitro and in vivo disposition of monoclonal antibodies

A growing body of evidence supports the important role of molecular charge on antibody pharmacokinetics (PK), yet a quantitative description of the effect of charge on systemic and tissue disposition of antibodies is still lacking. Consequently, we have systematically engineered complementarity-determining regions (CDRs) of trastuzumab to create a series of variants with an isoelectric point (pI) range of 6.3–8.9 and a variable region (Fv) charge range of −8.9 to +10.9 (at pH 5.5), and have investigated in vitro and in vivo disposition of these molecules. These monoclonal antibodies (mAbs) exhibited incrementally enhanced binding to cell surfaces and cellular uptake with increased positive charge in antigen-negative cells. After single intravenous dosing in mice, a bell-shaped relationship between systemic exposure and Fv charge was observed, with both extended negative and positive charge patches leading to more rapid nonspecific clearance. Whole-body PK experiments revealed that, although overall exposures of most variants in the tissues were very similar, positive charge of mAbs led to significantly enhanced tissue:plasma concentration ratios for most tissues. In well-perfused organs such as liver, spleen, and kidney, the positive charge variants show superior accumulation. In tissues with continuous capillaries such as fat, muscle, skin, and bone, plasma concentrations governed tissue exposures. The in vitro and in vivo disposition data presented here facilitate better understanding of the impact of charge modifications on antibody PK, and suggest that alteration in the charge may help to improve tissue:plasma concentration ratios for mAbs in certain tissues. The data presented here also paves the way for the development of physiologically based pharmacokinetic models of mAbs that incorporate charge variations.

Functional in vitro assessment of modified antibodies: Impact of label on protein properties

Labelling of therapeutic antibodies with radionuclides or fluorophores is routinely used to study their pharmacokinetic properties. A critical assumption in utilizing labelled therapeutic antibodies is that the label has no unfavourable effects on antibody charge, hydrophobicity, or receptor affinity. Ideally, the labelled protein should not have any significant deviations from the physiological properties of the original molecule. This article describes an established quality in vitro assessment workflow for labelled antibodies that ensures better prediction of changes in antibody pharmacokinetic (PK) properties after modifications. This analysis package considers degradation and aggregation analysis by size-exclusion chromatography, changes in neonatal-Fc-receptor (FcRn) affinity, and heparin interaction. FcRn binding is important for antibody recycling and half-life extension, whereas heparin affinity provides estimates on the rate of endocytosis through unspecific cell surface binding. Additionally, mass spectrometric analysis to determine the degree of labelling (DoL) completes the package and the combined analysis data allow to predict the label contribution to the PK properties of the modified antibody. This analytical strategy for labelling 11 IgGs has been investigated using 2 different IgG₁ constructs and applying 7 different types of labels. Each labelling resulted in a change in the physicochemical properties of the protein. Not only can the DoL of modified IgGs lead to a change in protein properties, but the type of label also can. Furthermore, it was demonstrated that the labelling process can also influence the behaviour of labelled mAbs. An identical label on different constructs of IgG₁ can cause different affinities for FcRn and heparin. Considering the assessment data, only 6 of the 11 modified antibodies from this study can be recommended for subsequent experiments. In conclusion, a suitability assessment of labelled antibodies prior to any pharmacokinetic studies is essential to reduce cost, allocate resources and reduce the number of animal experiments during pre-clinical drug development.

A cell-based FcRn-dependent recycling assay for predictive pharmacokinetic assessment of therapeutic antibodies

Aim: Evaluation of suitable pharmacokinetic properties is critical for successful development of IgG-based biotherapeutics. The prolonged half-lives of IgGs depend on the intracellular trafficking function of neonatal Fc receptor, which rescues internalized IgGs from lysosomal degradation and recycles them back to circulation. Results: Here, we developed a novel cell-based assay to quantify recycling of monoclonal antibodies in a transwell culture system that uses a cell line that stably expresses human neonatal Fc receptor. We tested seven therapeutic antibodies and showed that the recycling output of the assay strongly correlated with the clearance in humans. Conclusion: This recycling assay has potential application as a pharmacokinetic prescreening tool to facilitate development and selection of IgG-based candidate therapeutic monoclonal antibodies.

Interaction of clinical-stage antibodies with heme predicts their physiochemical and binding qualities

Immunoglobulin repertoires contain a fraction of antibodies that recognize low molecular weight compounds, including some enzymes' cofactors, such as heme. Here, by using a set of 113 samples with variable region sequences matching clinical-stage antibodies, we demonstrated that a considerable number of these antibodies interact with heme. Antibodies that interact with heme possess specific sequence traits of their antigen-binding regions. Moreover they manifest particular physicochemical and functional qualities i.e. increased hydrophobicity, higher propensity of self-binding, higher intrinsic polyreactivity and reduced expression yields. Thus, interaction with heme is a strong predictor of different molecular and functional qualities of antibodies. Notably, these qualities are of high importance for therapeutic antibodies, as their presence was associated with failure of drug candidates to reach clinic. Our study reveled an important facet of information about relationship sequence-function in antibodies. It also offers a convenient tool for detection of liabilities of therapeutic antibodies.

Predicting Method for the Human Plasma Concentration-Time Profile of a Monoclonal Antibody from the Half-life of Non-human Primates

Efficiency (speed and cost) and animal welfare are important factors in the development of new drugs. A novel method (the half-life method) was developed to predict the human plasma concentration-time profile of a monoclonal antibody (mAb) after intravenous (i.v.) administration using less data compared to the conventional approach; moreover, predicted results were comparable to conventional method. This new method use human geometric means of pharmacokinetics (PK) parameters and the non-human primates (NHP) half-life of each mAb. PK data on mAbs in humans and NHPs were collected from literature focusing on linear elimination, and the two-compartment model was used for analysis. The following features were revealed in humans: 1) the coefficient of variation in the distribution volume of the central compartment and at steady state of mAbs was small (22.6 and 23.8%, respectively) and 2) half-life at the elimination phase (t1/2_β) was the main contributor to plasma clearance. Moreover, distribution volume showed no significant correlation between humans and NHPs, and human t1/2_β showed a good correlation with allometrically scaled t1/2_β of NHP. Based on the features revealed in this study, we propose a new method for predicting the human plasma concentration-time profile of mAbs after i.v. dosing. When tested, this half-life method showed reasonable human prediction compared with a conventional empirical approach. The half-life method only requires t1/2_β to predict human PK, and is therefore able to improve animal welfare and potentially accelerate the drug development process.

Structure-based charge calculations for predicting isoelectric point, viscosity, clearance, and profiling antibody therapeutics

The effect of hydrophobicity on antibody aggregation is well understood, and it has been shown that charge calculations can be useful for high-concentration viscosity and pharmacokinetic (PK) clearance predictions. In this work, structure-based charge descriptors are evaluated for their predictive performance on recently published antibody pI, viscosity, and clearance data. From this, we devised four rules for therapeutic antibody profiling which address developability issues arising from hydrophobicity and charged-based solution behavior, PK, and the ability to enrich for those that are approved by the U.S. Food and Drug Administration. Differences in strategy for optimizing the solution behavior of human IgG1 antibodies versus the IgG2 and IgG4 isotypes and the impact of pH alterations in formulation are discussed.

Discovery-stage identification of drug-like antibodies using emerging experimental and computational methods

There is intense and widespread interest in developing monoclonal antibodies as therapeutic agents to treat diverse human disorders. During early-stage antibody discovery, hundreds to thousands of lead candidates are identified, and those that lack optimal physical and chemical properties must be deselected as early as possible to avoid problems later in drug development. It is particularly challenging to characterize such properties for large numbers of candidates with the low antibody quantities, concentrations, and purities that are available at the discovery stage, and to predict concentrated antibody properties (e.g., solubility, viscosity) required for efficient formulation, delivery, and efficacy. Here we review key recent advances in developing and implementing high-throughput methods for identifying antibodies with desirable in vitro and in vivo properties, including favorable antibody stability, specificity, solubility, pharmacokinetics, and immunogenicity profiles, that together encompass overall drug developability. In particular, we highlight impressive recent progress in developing computational methods for improving rational antibody design and prediction of drug-like behaviors that hold great promise for reducing the amount of required experimentation. We also discuss outstanding challenges that will need to be addressed in the future to fully realize the great potential of using such analysis for minimizing development times and improving the success rate of antibody candidates in the clinic.

Toward Drug-Like Multispecific Antibodies by Design

The success of antibody therapeutics is strongly influenced by their multifunctional nature that couples antigen recognition mediated by their variable regions with effector functions and half-life extension mediated by a subset of their constant regions. Nevertheless, the monospecific IgG format is not optimal for many therapeutic applications, and this has led to the design of a vast number of unique multispecific antibody formats that enable targeting of multiple antigens or multiple epitopes on the same antigen. Despite the diversity of these formats, a common challenge in generating multispecific antibodies is that they display suboptimal physical and chemical properties relative to conventional IgGs and are more difficult to develop into therapeutics. Here we review advances in the design and engineering of multispecific antibodies with drug-like properties, including favorable stability, solubility, viscosity, specificity and pharmacokinetic properties. We also highlight emerging experimental and computational methods for improving the next generation of multispecific antibodies, as well as their constituent antibody fragments, with natural IgG-like properties. Finally, we identify several outstanding challenges that need to be addressed to increase the success of multispecific antibodies in the clinic.

Pharmacokinetic prediction of an antibody in mice based on an in vitro cell-based approach using target receptor-expressing cells

In vivo pharmacokinetics (PK) studies using mice and monkeys are the main approaches for evaluating and predicting the PK of antibodies, and there is a strong demand for methods that do not require animal experiments. In this work, we focused on quantitatively predicting the nonlinear PK of an antibody based on cell-based assays. An anti-mouse Fc gamma receptor IIB antibody was used as a model antibody. To determine the PK parameters related to nonspecific elimination in vivo, the plasma concentration profile at 100 mg/kg, at which target-specific clearance is saturated, was analyzed by a 2-compartment model. To estimate the parameters related to target-specific elimination, the Michaelis–Menten constant (K_m) and the maximum elimination rate (V_max) were determined by an uptake assay using Chinese hamster ovary (CHO) cells expressing the target receptor. Finally, the integration of all of these parameters permitted the PK to be predicted at doses ranging from 1 to 100 mg/kg regardless of whether target-specific clearance was saturated or nonsaturated. The findings presented herein show that in vitro assays using target-expressing cells are useful tools for obtaining PK parameters and predicting PK profiles and, in some cases, eliminate the need for in vivo PK studies using experimental animals.

Assessing the binding properties of the anti-PD-1 antibody landscape using label-free biosensors

Here we describe an industry-wide collaboration aimed at assessing the binding properties of a comprehensive panel of monoclonal antibodies (mAbs) against programmed cell death protein 1 (PD-1), an important checkpoint protein in cancer immunotherapy and validated therapeutic target, with well over thirty unique mAbs either in clinical development or market-approved in the United States, the European Union or China. The binding kinetics of the PD-1/mAb interactions were measured by surface plasmon resonance (SPR) using a Carterra LSA instrument and the results were compared to data collected on a Biacore 8K. The effect of chip type on the SPR-derived binding rate constants and affinities were explored and the results compared with solution affinities from Meso Scale Discovery (MSD) and Kinetic Exclusion Assay (KinExA) experiments. When using flat chip types, the LSA and 8K platforms yielded near-identical kinetic rate and affinity constants that matched solution phase values more closely than those produced on 3D-hydrogels. Of the anti-PD-1 mAbs tested, which included a portion of those known to be in clinical development or approved, the affinities spanned from single digit picomolar to nearly 425 nM, challenging the dynamic range of our methods. The LSA instrument was also used to perform epitope binning and ligand competition studies which revealed over ten unique competitive binding profiles within this group of mAbs.