Balancing charge in the complementarity-determining regions of humanized mAbs without affecting pI reduces non-specific binding and improves the pharmacokinetics

Isoelectric point, net charge and amino acid analysis of experimentally validated therapeutic antibodies

The isoelectric point (pI) of an antibody is known to affect its non-specific interactions and repulsive self-interactions. However, analytical outcomes for the pI of a large number of therapeutic antibodies remain unexplored. In this study, we explored the pI and net charge of variable heavy (VH), variable light (VL), CDR (complementarity determining regions) and whole IgG on a large number of therapeutic antibodies, additionally amino acids distribution in the CDR regions were also analyzed. A total of 708 experimentally validated antibodies from the Thera-SAbDab database were analyzed in this study. Analysis of the antibody dataset showed that the pI of the whole IgG sequence is between 5 and 9, while the majority was in the intermediate range between 7 and 9 (86.7%). The charge had a wide range from - 10 to 12, with the majority falling between the charges 2-6 (53.4%). However, the combined pI score of the CDRs of light chains (60%) as well as for the heavy chains (67%) was observed in the range of 4-6. The amino acid composition analysis of CDR regions revealed that most of the amino acids in the light chain are uncharged-polar (46.3%) followed by hydrophobic-aliphatic (28.4%), while in the heavy chain; it is hydrophobic-aliphatic (35.2%) followed by uncharged-polar (24.6%). In conclusion, the pI and net charge analysis of therapeutic antibodies are crucial for understanding pharmacokinetic properties. Moreover, amino acid composition of the light and heavy chain CDR regions has a significant impact on the pI and charge of the entire IgG antibody.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-025-00356-y.

A non-classical view of antibody properties: Allosteric effect between variable and constant regions

Historically, antibodies have been divided into two functionally independent domains, the variable (V) region for antigen binding and the constant (C) region for mediating effector functions. However, this classical view of antibody function has been severely challenged by a large and growing number of studies, which reveal long-range conformational interactions and allosteric links between the V and C regions. This review comprehensively summarizes the existing studies on antibody allostery, including allosteric conformational changes induced by covalent modifications or noncovalent ligand binding. In addition, we discuss how intramolecular allosteric signals are transmitted from the V to C regions and vice versa. This review argues that there is sufficient evidence to revisit the structure-function relationship of antibodies. These advances in antibody allostery will provide a blueprint for regulating antibody functions in a simple and highly predictable manner. More focus on antibody allostery will definitely benefit antibody engineering and vaccine design in the field of biotechnology.

Steered molecular dynamics simulation as a post-process to optimize the iBRAB-designed Fab model

Therapeutic monoclonal antibodies are an effective method of treating acute infectious diseases. However, knowing which of the produced antibodies in the vast number of human antibodies can cure the disease requires a long time and advanced technology. The previously introduced iBRAB method relies on studied antibodies to design a broad-spectrum antibody capable of neutralizing antigens of many different Influenza A viral strains. To evaluate the antigen-binding fragment as an applicable drug, the therapeutic antibody profiles providing guidelines collected from clinically staged therapeutic antibodies were used to access different measurements. Although the evaluated values were within an accepted range, the modification in the amino acid sequence is required for better properties. Thus, using the steered molecular dynamics (SMD) simulation to determine the binding capacity of amino acids in the functional region, the profile of interacted amino acids of Fab with the antigen was established for modified reference. As a result, the model was modified with amino acids elimination at positions 96-97 in the heavy chain and 26-27, 91, 96-97, and 102-103 in the light chain, which has better Therapeutic Antibody Profiler evaluations than the original designation. Thus again, SMD simulation is a promising computational approach for post-modification in rational drug design.

Human antibody polyreactivity is governed primarily by the heavy-chain complementarity-determining regions

Although antibody variable regions mediate antigen-specific binding, they can also mediate non-specific interactions with non-cognate antigens, impacting diverse immunological processes and the efficacy, safety, and half-life of antibody therapeutics. To understand the molecular basis of antibody non-specificity, we sorted two dissimilar human naïve antibody libraries against multiple reagents to enrich for variants with different levels of polyreactivity. Sequence analysis of >300,000 paired antibody variable regions revealed that the heavy chain primarily mediates human antibody polyreactivity, and this is due to the high positive charge, high hydrophobicity, and combinations thereof in the corresponding complementarity-determining regions, which can be predicted using a machine learning model developed in this work. Notably, a subset of the most important features governing antibody non-specific interactions, namely those that contain tyrosine, also govern specific antigen recognition. Our findings are broadly relevant for understanding fundamental aspects of antibody molecular recognition and the applied aspects of antibody-drug design.

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.

Engineering of pH-dependent antigen binding properties for toxin-targeting IgG1 antibodies using light-chain shuffling

Immunoglobulin G (IgG) antibodies that bind their cognate antigen in a pH-dependent manner (acid-switched antibodies) can release their bound antigen for degradation in the acidic environment of endosomes, while the IgGs are rescued by the neonatal Fc receptor (FcRn). Thus, such IgGs can neutralize multiple antigens over time and therefore be used at lower doses than their non-pH-responsive counterparts. Here, we show that light-chain shuffling combined with phage display technology can be used to discover IgG1 antibodies with increased pH-dependent antigen binding properties, using the snake venom toxins, myotoxin II and α-cobratoxin, as examples. We reveal differences in how the selected IgG1s engage their antigens and human FcRn and show how these differences translate into distinct cellular handling properties related to their pH-dependent antigen binding phenotypes and Fc-engineering for improved FcRn binding. Our study showcases the complexity of engineering pH-dependent antigen binding IgG1s and demonstrates the effects on cellular antibody-antigen recycling.

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.

Protein language models enable prediction of polyreactivity of monospecific, bispecific, and heavy-chain-only antibodies

Background

Early assessment of antibody off-target binding is essential for mitigating developability risks such as fast clearance, reduced efficacy, toxicity, and immunogenicity. The baculovirus particle (BVP) binding assay has been widely utilized to evaluate polyreactivity of antibodies. As a complementary approach, computational prediction of polyreactivity is desirable for counter-screening antibodies from in silico discovery campaigns. However, there is a lack of such models.

Methods

Herein, we present the development of an ensemble of three deep learning models based on two pan-protein foundational protein language models (ESM2 and ProtT5) and an antibody-specific protein language model (PLM) (Antiberty). These models were trained in a transfer learning network to predict the outcomes in the BVP assay and the bovine serum albumin binding assay, which was developed as a complement to the BVP assay. The training was conducted on a large dataset of antibody sequences augmented with experimental conditions, which were collected through a highly efficient application system.

Results

The resulting models demonstrated robust performance on canonical mAbs (monospecific with heavy and light chain), bispecific Abs, and single-domain Fc (VHH-Fc). PLMs outperformed a model built using molecular descriptors calculated from AlphaFold 2 predicted structures. Embeddings from the antibody-specific and foundational PLMs resulted in similar performance.

Conclusion

To our knowledge, this represents the first application of PLMs to predict assay data on bispecifics and VHH-Fcs.

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.

Antibody Drug Clearance: An Underexplored Marker of Outcomes with Checkpoint Inhibitors

Immune-checkpoint inhibitor (ICI) therapy has dramatically changed the clinical landscape for several cancers, and ICI use continues to expand across many cancer types. Low baseline clearance (CL) and/or a large reduction of CL during treatment correlates with better clinical response and longer survival. Similar phenomena have also been reported with other monoclonal antibodies (mAb) in cancer and other diseases, highlighting a characteristic of mAb clinical pharmacology that is potentially shared among various mAbs and diseases. Though tempting to attribute poor outcomes to low drug exposure and arguably low target engagement due to high CL, such speculation is not supported by the relatively flat exposure-response relationship of most ICIs, where a higher dose or exposure is not likely to provide additional benefit. Instead, an elevated and/or increasing CL could be a surrogate marker of the inherent resistant phenotype that cannot be reversed by maximizing drug exposure. The mechanisms connecting ICI clearance, therapeutic efficacy, and resistance are unclear and likely to be multifactorial. Therefore, to explore the potential of ICI CL as an early marker for efficacy, this review highlights the similarities and differences of CL characteristics and CL-response relationships for all FDA-approved ICIs, and we compare and contrast these to selected non-ICI mAbs. We also discuss underlying mechanisms that potentially link mAb CL with efficacy and highlight existing knowledge gaps and future directions where more clinical and preclinical investigations are warranted to clearly understand the value of baseline and/or time-varying CL in predicting response to ICI-based therapeutics.

Impact of structural modifications of IgG antibodies on effector functions

Immunoglobulin G (IgG) antibodies are a critical component of the adaptive immune system, binding to and neutralizing pathogens and other foreign substances. Recent advances in molecular antibody biology and structural protein engineering enabled the modification of IgG antibodies to enhance their therapeutic potential. This review summarizes recent progress in both natural and engineered structural modifications of IgG antibodies, including allotypic variation, glycosylation, Fc engineering, and Fc gamma receptor binding optimization. We discuss the functional consequences of these modifications to highlight their potential for therapeutical applications.

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.

Tau-targeting therapies for Alzheimer disease: current status and future directions

Alzheimer disease (AD) is the most common cause of dementia in older individuals. AD is characterized pathologically by amyloid-β (Aβ) plaques and tau neurofibrillary tangles in the brain, with associated loss of synapses and neurons, which eventually results in dementia. Many of the early attempts to develop treatments for AD focused on Aβ, but a lack of efficacy of these treatments in terms of slowing disease progression led to a change of strategy towards targeting of tau pathology. Given that tau shows a stronger correlation with symptom severity than does Aβ, targeting of tau is more likely to be efficacious once cognitive decline begins. Anti-tau therapies initially focused on post-translational modifications, inhibition of tau aggregation and stabilization of microtubules. However, trials of many potential drugs were discontinued because of toxicity and/or lack of efficacy. Currently, the majority of tau-targeting agents in clinical trials are immunotherapies. In this Review, we provide an update on the results from the initial immunotherapy trials and an overview of new therapeutic candidates that are in clinical development, as well as considering future directions for tau-targeting therapies.

Polyreactivity of antibodies from different B-cell subpopulations is determined by distinct sequence patterns of variable region

An antibody molecule that can bind to multiple distinct antigens is defined as polyreactive. In the present study, we performed statistical analyses to assess sequence correlates of polyreactivity of >600 antibodies cloned from different B-cell types of healthy humans. The data revealed several sequence patterns of variable regions of heavy and light immunoglobulin chains that determine polyreactivity. The most prominent identified patterns were increased number of basic amino acid residues, reduced frequency of acidic residues, increased number of aromatic and hydrophobic residues, and longer length of CDR L1. Importantly, our study revealed that antibodies isolated from different B-cell populations used distinct sequence patterns (or combinations of them) for polyreactive antigen binding. Furthermore, we combined the data from sequence analyses with molecular modeling of selected polyreactive antibodies and demonstrated that human antibodies can use multiple pathways for achieving antigen-binding promiscuity. These data reconcile some contradictions in the literature regarding the determinants of antibody polyreactivity. Moreover, our study demonstrates that the mechanism of polyreactivity of antibodies evolves during immune response and might be tailored to specific functional properties of different B-cell compartments. Finally, these data can be of use for efforts in the development and engineering of therapeutic antibodies.

Defining and Studying B Cell Receptor and TCR Interactions

BCRs (Abs) and TCRs (or adaptive immune receptors [AIRs]) are the means by which the adaptive immune system recognizes foreign and self-antigens, playing an integral part in host defense, as well as the emergence of autoimmunity. Importantly, the interaction between AIRs and their cognate Ags defies a simple key-in-lock paradigm and is instead a complex many-to-many mapping between an individual's massively diverse AIR repertoire, and a similarly diverse antigenic space. Understanding how adaptive immunity balances specificity with epitopic coverage is a key challenge for the field, and terms such as broad specificity, cross-reactivity, and polyreactivity remain ill-defined and are used inconsistently. In this Immunology Notes and Resources article, a group of experimental, structural, and computational immunologists define commonly used terms associated with AIR binding, describe methodologies to study these binding modes, as well as highlight the implications of these different binding modes for therapeutic design.

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.

Intravital Microscopy Reveals Unforeseen Biodistribution Within the Liver and Kidney Mechanistically Connected to the Clearance of a Bifunctional Antibody

Bifunctional antibody (BfAb) therapeutics offer the potential for novel functionalities beyond those of the individual monospecific entities. However, combining these entities into a single molecule can have unpredictable effects, including changes in pharmacokinetics that limit the compound's therapeutic profile. A better understanding of how molecular modifications affect in vivo tissue interactions could help inform BfAb design. The present studies were predicated on the observation that a BfAb designed to have minimal off-target interactions cleared from the circulation twice as fast as the monoclonal antibody (mAb) from which it was derived. The present study leverages the spatial and temporal resolution of intravital microscopy (IVM) to identify cellular interactions that may explain the different pharmacokinetics of the two compounds. Disposition studies of mice demonstrated that radiolabeled compounds distributed similarly over the first 24 hours, except that BfAb accumulated approximately two- to -three times more than mAb in the liver. IVM studies of mice demonstrated that both distributed to endosomes of liver endothelia but with different kinetics. Whereas mAb accumulated rapidly within the first hour of administration, BfAb accumulated only modestly during the first hour but continued to accumulate over 24 hours, ultimately reaching levels similar to those of the mAb. Although neither compound was freely filtered by the mouse or rat kidney, BfAb, but not mAb, was found to accumulate over 24 hours in endosomes of proximal tubule cells. These studies demonstrate how IVM can be used as a tool in drug design, revealing unpredicted cellular interactions that are undetectable by conventional analyses. SIGNIFICANCE STATEMENT: Bifunctional antibodies offer novel therapeutic functionalities beyond those of the individual monospecific entities. However, combining these entities into a single molecule can have unpredictable effects, including undesirable changes in pharmacokinetics. Studies of the dynamic distribution of a bifunctional antibody and its parent monoclonal antibody presented here demonstrate how intravital microscopy can expand our understanding of the in vivo disposition of therapeutics, detecting off-target interactions that could not be detected by conventional pharmacokinetics approaches or predicted by conventional physicochemical analyses.

Trastuzumab Charge Variants: a Study on Physicochemical and Pharmacokinetic Properties

Background

Post-translational modifications in bioprocessing and storage of recombinant mAbs are the main sources of charge variants. While the profile of these kinds of variants is considered an important attribute for the therapeutic mAbs, there is controversy about their direct role in safety and efficacy. In this study, the physicochemical and pharmacokinetic (PK) properties of the separated charge variants belonging to a trastuzumab potential biosimilar, were examined.

Methods

The acidic peaks, basic peaks, and main variants of trastuzumab were separated and enriched by semi-preparative weak cation exchange. A panel of analytical techniques was utilized to characterize the physicochemical properties of these variants. The binding affinity to HER2 and FcγRs and the PK parameters were evaluated for each variant.

Results

Based on the results, the charge variants of the proposed biosimilar had no significant influence on the examined efficacy and PK parameters.

Conclusion

During the development and production of biosimilar monoclonal antibodies, evaluating the effect of their charge variants on efficacy and PK parameters is needed.

Embedding Dynamics in Intrinsic Physicochemical Profiles of Market-Stage Antibody-Based Biotherapeutics

Adequate stability, manufacturability, and safety are crucial to bringing an antibody-based biotherapeutic to the market. Following the concept of holistic in silico developability, we introduce a physicochemical description of 91 market-stage antibody-based biotherapeutics based on orthogonal molecular properties of variable regions (Fvs) embedded in different simulation environments, mimicking conditions experienced by antibodies during manufacturing, formulation, and in vivo. In this work, the evaluation of molecular properties includes conformational flexibility of the Fvs using molecular dynamics (MD) simulations. The comparison between static homology models and simulations shows that MD significantly affects certain molecular descriptors like surface molecular patches. Moreover, the structural stability of a subset of Fv regions is linked to changes in their specific molecular interactions with ions in different experimental conditions. This is supported by the observation of differences in protein melting temperatures upon addition of NaCl. A DEvelopability Navigator In Silico (DENIS) is proposed to compare mAb candidates for their similarity with market-stage biotherapeutics in terms of physicochemical properties and conformational stability. Expanding on our previous developability guidelines (Ahmed et al. Proc. Natl. Acad. Sci. 2021, 118 (37), e2020577118), the hydrodynamic radius and the protein strand ratio are introduced as two additional descriptors that enable a more comprehensive in silico characterization of biotherapeutic drug candidates. Test cases show how this approach can facilitate identification and optimization of intrinsically developable lead candidates. DENIS represents an advanced computational tool to progress biotherapeutic drug candidates from discovery into early development by predicting drug properties in different aqueous environments.

IgG Fab Glycans Hinder FcRn-Mediated Placental Transport

Abs can be glycosylated in both their Fc and Fab regions with marked effects on Ab function and binding. High levels of IgG Fab glycosylation are associated with malignant and autoimmune conditions, exemplified by rheumatoid arthritis and highly Fab-glycosylated (∼90%) anti-citrullinated protein Abs (ACPAs). Important properties of IgG, such as long half-life and placental transport, are facilitated by the human neonatal Fc receptor (hFcRn). Although it is known that glycosylation of Abs can affect binding to Fc receptors, little is known on the impact of IgG Fab glycosylation on hFcRn binding and transplacental transport. Therefore, we analyzed the interaction between hFcRn and IgG with and without Fab glycans in vitro with various methods as well as in vivo by studying placental transfer of Fab-glycosylated Abs from mothers to newborns. No effect of Fab glycosylation on IgG binding to hFcRn was found by surface plasmon resonance and hFcRn affinity chromatography. In contrast, studies in a cell membrane context revealed that Fab glycans negatively impacted IgG-hFcRn interaction. In line with this, we found that Fab-glycosylated IgGs were transported ∼20% less efficiently across the placenta. This appeared to be a general phenomenon, observed for ACPAs, non-ACPAs, as well as total IgG in rheumatoid arthritis patients and healthy controls. Our results suggest that, in a cellular context, Fab glycans inhibit IgG-hFcRn interaction and thus negatively affect the transplacental transfer of IgG. As Fab-glycosylated Abs are frequently associated with autoimmune and malignant disorders and may be potentially harmful, this might encompass a regulatory mechanism, limiting the half-life and transport of such Abs.

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.

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.

Developability profiling of a panel of Fc engineered SARS-CoV-2 neutralizing antibodies

To combat the COVID-19 pandemic, potential therapies have been developed and moved into clinical trials at an unprecedented pace. Some of the most promising therapies are neutralizing antibodies against SARS-CoV-2. In order to maximize the therapeutic effectiveness of such neutralizing antibodies, Fc engineering to modulate effector functions and to extend half-life is desirable. However, it is critical that Fc engineering does not negatively impact the developability properties of the antibodies, as these properties play a key role in ensuring rapid development, successful manufacturing, and improved overall chances of clinical success. In this study, we describe the biophysical characterization of a panel of Fc engineered ("TM-YTE") SARS-CoV-2 neutralizing antibodies, the same Fc modifications as those found in AstraZeneca's Evusheld (AZD7442; tixagevimab and cilgavimab), in which the TM modification (L234F/L235E/P331S) reduce binding to FcγR and C1q and the YTE modification (M252Y/S254T/T256E) extends serum half-life. We have previously shown that combining both the TM and YTE Fc modifications can reduce the thermal stability of the CH2 domain and possibly lead to developability challenges. Here we show, using a diverse panel of TM-YTE SARS-CoV-2 neutralizing antibodies, that despite lowering the thermal stability of the Fc CH2 domain, the TM-YTE platform does not have any inherent developability liabilities and shows an in vivo pharmacokinetic profile in human FcRn transgenic mice similar to the well-characterized YTE platform. The TM-YTE is therefore a developable, effector function reduced, half-life extended antibody platform.

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.

Monoclonal Antibody Pharmacokinetics in Cynomolgus Monkeys Following Subcutaneous Administration: Physiologically Based Model Predictions from Physiochemical Properties

An integrated physiologically based modeling framework is presented for predicting pharmacokinetics and bioavailability of subcutaneously administered monoclonal antibodies in cynomolgus monkeys, based on in silico structure-derived metrics characterizing antibody size, overall charge, local charge, and hydrophobicity. The model accounts for antibody-specific differences in pinocytosis, transcapillary transport, local lymphatic uptake, and pre-systemic degradation at the subcutaneous injection site and reliably predicts the pharmacokinetics of five different wild-type mAbs and their Fc variants following intravenous and subcutaneous administration. Significant associations were found between subcutaneous injection site degradation rate and the antibody's local positive charge of its complementarity-determining region (R = 0.56, p = 0.0012), antibody pinocytosis rate and its overall positive charge (R = 0.59, p = 0.00063), and antibody paracellular transport and its overall charge together with hydrophobicity (R = 0.63, p = 0.00096). Based on these results, population simulations were performed to predict the relationship between bioavailability and antibody local positive charge. In addition, model simulations were conducted to calculate the relative contribution of absorption pathways (lymphatic and blood), pre-systemic degradation pathways (interstitial and lysosomal), and the influence of injection site lymph flow on antibody bioavailability and pharmacokinetics. The proposed physiologically based modeling framework integrates fundamental mechanisms governing antibody subcutaneous absorption and disposition, with structured-based physiochemical properties, to predict antibody bioavailability and pharmacokinetics in vivo.

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.

The Fab region of IgG impairs the internalization pathway of FcRn upon Fc engagement

Binding to the neonatal Fc receptor (FcRn) extends serum half-life of IgG, and antagonizing this interaction is a promising therapeutic approach in IgG-mediated autoimmune diseases. Fc-MST-HN, designed for enhanced FcRn binding capacity, has not been evaluated in the context of a full-length antibody, and the structural properties of the attached Fab regions might affect the FcRn-mediated intracellular trafficking pathway. Here we present a comprehensive comparative analysis of the IgG salvage pathway between two full-size IgG1 variants, containing wild type and MST-HN Fc fragments, and their Fc-only counterparts. We find no evidence of Fab-regions affecting FcRn binding in cell-free assays, however, cellular assays show impaired binding of full-size IgG to FcRn, which translates into improved intracellular FcRn occupancy and intracellular accumulation of Fc-MST-HN compared to full size IgG1-MST-HN. The crystal structure of Fc-MST-HN in complex with FcRn provides a plausible explanation why the Fab disrupts the interaction only in the context of membrane-associated FcRn. Importantly, we find that Fc-MST-HN outperforms full-size IgG1-MST-HN in reducing IgG levels in cynomolgus monkeys. Collectively, our findings identify the cellular membrane context as a critical factor in FcRn biology and therapeutic targeting.

Monoclonal Antibody Engineering and Design to Modulate FcRn Activities: A Comprehensive Review

Understanding the biological mechanisms underlying the pH-dependent nature of FcRn binding, as well as the various factors influencing the affinity to FcRn, was concurrent with the arrival of the first recombinant IgG monoclonal antibodies (mAbs) and IgG Fc-fusion proteins in clinical practice. IgG Fc–FcRn became a central subject of interest for the development of these drugs for the comfort of patients and good clinical responses. In this review, we describe (i) mAb mutations close to and outside the FcRn binding site, increasing the affinity for FcRn at acidic pH and leading to enhanced mAb half-life and biodistribution, and (ii) mAb mutations increasing the affinity for FcRn at acidic and neutral pH, blocking FcRn binding and resulting, in vivo, in endogenous IgG degradation. Mutations modifying FcRn binding are discussed in association with pH-dependent modulation of antigen binding and (iii) anti-FcRn mAbs, two of the latest innovations in anti-FcRn mAbs leading to endogenous IgG depletion. We discuss the pharmacological effects, the biological consequences, and advantages of targeting IgG–FcRn interactions and their application in human therapeutics.

Biophysical differences in IgG1 Fc-based therapeutics relate to their cellular handling, interaction with FcRn and plasma half-life

Antibody-based therapeutics (ABTs) are used to treat a range of diseases. Most ABTs are either full-length IgG1 antibodies or fusions between for instance antigen (Ag)-binding receptor domains and the IgG1 Fc fragment. Interestingly, their plasma half-life varies considerably, which may relate to how they engage the neonatal Fc receptor (FcRn). As such, there is a need for an in-depth understanding of how different features of ABTs affect FcRn-binding and transport behavior. Here, we report on how FcRn-engagement of the IgG1 Fc fragment compare to clinically relevant IgGs and receptor domain Fc fusions, binding to VEGF or TNF-α. The results reveal FcRn-dependent intracellular accumulation of the Fc, which is in line with shorter plasma half-life than that of full-length IgG1 in human FcRn-expressing mice. Receptor domain fusion to the Fc increases its half-life, but not to the extent of IgG1. This is mirrored by a reduced cellular recycling capacity of the Fc-fusions. In addition, binding of cognate Ag to ABTs show that complexes of similar size undergo cellular transport at different rates, which could be explained by the biophysical properties of each ABT. Thus, the study provides knowledge that should guide tailoring of ABTs regarding optimal cellular sorting and plasma half-life.

Analysis of clinically approved antibody-based therapeutics reveals different structural designs, such as full-length IgG1 or Fc-fusions, entail distinct biophysical properties that affect FcRn binding, intracellular transport and plasma half-life.

Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space

Therapeutic antibody development requires selection and engineering of molecules with high affinity and other drug-like biophysical properties. Co-optimization of multiple antibody properties remains a difficult and time-consuming process that impedes drug development. Here we evaluate the use of machine learning to simplify antibody co-optimization for a clinical-stage antibody (emibetuzumab) that displays high levels of both on-target (antigen) and off-target (non-specific) binding. We mutate sites in the antibody complementarity-determining regions, sort the antibody libraries for high and low levels of affinity and non-specific binding, and deep sequence the enriched libraries. Interestingly, machine learning models trained on datasets with binary labels enable predictions of continuous metrics that are strongly correlated with antibody affinity and non-specific binding. These models illustrate strong tradeoffs between these two properties, as increases in affinity along the co-optimal (Pareto) frontier require progressive reductions in specificity. Notably, models trained with deep learning features enable prediction of novel antibody mutations that co-optimize affinity and specificity beyond what is possible for the original antibody library. These findings demonstrate the power of machine learning models to greatly expand the exploration of novel antibody sequence space and accelerate the development of highly potent, drug-like antibodies.

Absorption, Distribution, Metabolism, and Excretion of Therapeutic Proteins: Current Industry Practices and Future Perspectives

Therapeutic proteins (TPs) comprise a variety of modalities, including antibody-based drugs, coagulation factors, recombinant cytokines, enzymes, growth factors, and hormones. TPs usually cannot traverse cellular barriers and exert their pharmacological activity by interacting with targets on the exterior membrane of cells or with soluble ligands in the tissue interstitial fluid/blood. Due to their large size, lack of cellular permeability, variation in metabolic fate, and distinct physicochemical characteristics, TPs are subject to different absorption, distribution, metabolism, and excretion (ADME) processes as compared with small molecules. Limited regulatory guidance makes it challenging to determine the most relevant ADME data required for regulatory submissions. The TP ADME working group was sponsored by the Translational and ADME Sciences Leadership Group within the Innovation and Quality (IQ) consortium with objectives to: (1) better understand the current practices of ADME data generated for TPs across IQ member companies, (2) learn about their regulatory strategies and interaction experiences, and (3) provide recommendations on best practices for conducting ADME studies for TPs. To understand current ADME practices and regulatory strategies, an industry-wide survey was conducted within IQ member companies. In addition, ADME data submitted to the U.S. Food and Drug Administration was also collated by reviewing regulatory submission packages of TPs approved between 2011 and 2020. This article summarizes the key learnings from the survey and an overview of ADME data presented in biologics license applications along with future perspectives and recommendations for conducting ADME studies for internal decision-making as well as regulatory submissions for TPs. SIGNIFICANCE STATEMENT: This article provides comprehensive assessment of the current practices of absorption, distribution, metabolism, and excretion (ADME) data generated for therapeutic proteins (TPs) across the Innovation and Quality participating companies and the utility of the data in discovery, development, and regulatory submissions. The TP ADME working group also recommends the best practices for condu-cting ADME studies for internal decision-making and regulatory submissions.

Mathematical Models to Characterize the Absorption, Distribution, Metabolism, and Excretion of Protein Therapeutics

Therapeutic proteins (TPs) have ranked among the most important and fastest-growing classes of drugs in the clinic, yet the development of successful TPs is often limited by unsatisfactory efficacy. Understanding pharmacokinetic (PK) characteristics of TPs is key to achieving sufficient and prolonged exposure at the site of action, which is a prerequisite for eliciting desired pharmacological effects. PK modeling represents a powerful tool to investigate factors governing in vivo disposition of TPs. In this mini-review, we discuss many state-of-the-art models that recapitulate critical processes in each of the absorption, distribution, metabolism/catabolism, and excretion pathways of TPs, which can be integrated into the physiologically-based pharmacokinetic framework. Additionally, we provide our perspectives on current opportunities and challenges for evolving the PK models to accelerate the discovery and development of safe and efficacious TPs. SIGNIFICANCE STATEMENT: This minireview provides an overview of mechanistic pharmacokinetic (PK) models developed to characterize absorption, distribution, metabolism, and elimination (ADME) properties of therapeutic proteins (TPs), which can support model-informed discovery and development of TPs. As the next-generation of TPs with diverse physicochemical properties and mechanism-of-action are being developed rapidly, there is an urgent need to better understand the determinants for the ADME of TPs and evolve existing platform PK models to facilitate successful bench-to-bedside translation of these promising drug molecules.

Targeting tau only extracellularly is likely to be less efficacious than targeting it both intra- and extracellularly

Aggregation of the tau protein is thought to be responsible for the neurodegeneration and subsequent functional impairments in diseases that are collectively named tauopathies. Alzheimer's disease is the most common tauopathy, but the group consists of over 20 different diseases, many of which have tau pathology as their primary feature. The development of tau therapies has mainly focused on preventing the formation of and/or clearing these aggregates. Of these, immunotherapies that aim to either elicit endogenous tau antibodies or deliver exogenous ones are the most common approach in clinical trials. While their mechanism of action can involve several pathways, both extra- and intracellular, pharmaceutical companies have primarily focused on antibody-mediated clearance of extracellular tau. As we have pointed out over the years, this is rather surprising because it is well known that most of pathological tau protein is found intracellularly. It has been repeatedly shown by several groups over the past decades that antibodies can enter neurons and that their cellular uptake can be enhanced by various means, particularly by altering their charge. Here, we will briefly describe the potential extra- and intracellular mechanisms involved in antibody-mediated clearance of tau pathology, discuss these in the context of recent failures of some of the tau antibody trials, and finally provide a brief overview of how the intracellular efficacy of tau antibodies can potentially be further improved by certain modifications that aim to enhance tau clearance via specific intracellular degradation pathways.

Antibodies with Weakly Basic Isoelectric Points Minimize Trade-offs between Formulation and Physiological Colloidal Properties

The widespread interest in antibody therapeutics has led to much focus on identifying antibody candidates with favorable developability properties. In particular, there is broad interest in identifying antibody candidates with highly repulsive self-interactions in standard formulations (e.g., low ionic strength buffers at pH 5-6) for high solubility and low viscosity. Likewise, there is also broad interest in identifying antibody candidates with low levels of non-specific interactions in physiological solution conditions (PBS, pH 7.4) to promote favorable pharmacokinetic properties. To what extent antibodies that possess both highly repulsive self-interactions in standard formulations and weak non-specific interactions in physiological solution conditions can be systematically identified remains unclear and is a potential impediment to successful therapeutic drug development. Here, we evaluate these two properties for 42 IgG1 variants based on the variable fragments (Fvs) from four clinical-stage antibodies and complementarity-determining regions from 10 clinical-stage antibodies. Interestingly, we find that antibodies with the strongest repulsive self-interactions in a standard formulation (pH 6 and 10 mM histidine) display the strongest non-specific interactions in physiological solution conditions. Conversely, antibodies with the weakest non-specific interactions under physiological conditions display the least repulsive self-interactions in standard formulations. This behavior can be largely explained by the antibody isoelectric point, as highly basic antibodies that are highly positively charged under standard formulation conditions (pH 5-6) promote repulsive self-interactions that mediate high colloidal stability but also mediate strong non-specific interactions with negatively charged biomolecules at physiological pH and vice versa for antibodies with negatively charged Fv regions. Therefore, IgG1s with weakly basic isoelectric points between 8 and 8.5 and Fv isoelectric points between 7.5 and 9 typically display the best combinations of strong repulsive self-interactions and weak non-specific interactions. We expect that these findings will improve the identification and engineering of antibody candidates with drug-like biophysical properties.

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.

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.

Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies

Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs) are tremendous, the design and discovery of new candidates remain a time and cost-intensive endeavor. In this regard, progress in the generation of data describing antigen binding and developability, computational methodology, and artificial intelligence may pave the way for a new era of in silico on-demand immunotherapeutics design and discovery. Here, we argue that the main necessary machine learning (ML) components for an in silico mAb sequence generator are: understanding of the rules of mAb-antigen binding, capacity to modularly combine mAb design parameters, and algorithms for unconstrained parameter-driven in silico mAb sequence synthesis. We review the current progress toward the realization of these necessary components and discuss the challenges that must be overcome to allow the on-demand ML-based discovery and design of fit-for-purpose mAb therapeutic candidates.

The Therapeutic Antibody Profiler for Computational Developability Assessment

The need to consider an antibody's "developability" (immunogenicity, solubility, specificity, stability, manufacturability, and storability) is now well understood in therapeutic antibody design. Predicting these properties rapidly and inexpensively is critical to industrial workflows, to avoid devoting resources to non-productive candidates. Here, we describe a high-throughput computational developability assessment tool, the Therapeutic Antibody Profiler (TAP), which assesses the physicochemical "druglikeness" of an antibody candidate. Input variable domain sequences are converted to three-dimensional structural models, and then five developability-linked molecular surface descriptors are calculated and compared to advanced-stage clinical therapeutics. Values at the extremes of/outside of the distributions seen in therapeutics imply an increased risk of developability issues. Therefore, TAP, starting only from sequence information, provides a route to rapidly identifying drug candidate antibodies that are likely to have poor developability. Our web application ( opig.stats.ox.ac.uk/webapps/tap ) profiles input antibody sequences against a continually updated reference set of clinical therapeutics.

Elimination of plasma soluble antigen in cynomolgus monkeys by combining pH-dependent antigen binding and novel Fc engineering

A conventional antibody targeting a soluble antigen in circulation typically requires a huge dosage and frequent intravenous administration to neutralize the antigen. This is because antigen degradation is reduced by the formation of antigen–antibody immune complexes, which escape from lysosomal degradation using neonatal Fc receptor (FcRn)-mediated recycling. To address this, we developed an antigen-sweeping antibody that combines pH-dependent antigen binding and Fc engineering to enhance Fc receptor binding. The sweeping antibody actively eliminates the plasma antigens by increasing the cellular uptake of the immune complex and dissociating the antigens in the acidic endosome for degradation. Strong antigen sweeping can reduce the dosage, potentially achieve higher efficacy, and expand the scope of antigen space available for targeting by antibodies. In this study, to further improve the sweeping efficacy, we developed a novel antibody Fc variant by enhancing Fcγ receptor IIb (FcγRIIb) binding and modulating charge characteristics for increased cellular uptake of the immune complex, together with enhancing FcRn binding for efficient salvage of the antigen-free antibodies. Our Fc variant achieved strong antigen sweeping in cynomolgus monkeys with antibody pharmacokinetics comparable to a wild-type human IgG₁ antibody. The positive-charge substitutions enhanced uptake of the immune complex by FcγRIIb-expressing cells in vitro, which was completely inhibited by an anti-FcγRIIb antibody. This suggests that the strong in vivo sweeping efficacy improved by the charge engineering is more likely achieved by FcγRIIb-dependent uptake of the immune complex rather than nonspecific uptake. We expect this novel Fc engineering can maximize the antigen sweeping efficacy even in humans and create novel therapeutic antibodies that meet unmet medical needs for patients.

Antibody variable sequences have a pronounced effect on cellular transport and plasma half-life

Monoclonal IgG antibodies are the fastest growing class of biologics, but large differences exist in their plasma half-life in humans. Thus, to design IgG antibodies with favorable pharmacokinetics, it is crucial to identify the determinants of such differences. Here, we demonstrate that the variable region sequences of IgG antibodies greatly affect cellular uptake and subsequent recycling and rescue from intracellular degradation by endothelial cells. When the variable sequences are masked by the cognate antigen, it influences both their transport behavior and binding to the neonatal Fc receptor (FcRn), a key regulator of IgG plasma half-life. Furthermore, we show how charge patch differences in the variable domains modulate both binding and transport properties and that a short plasma half-life, due to unfavorable charge patches, may partly be overcome by Fc-engineering for improved FcRn binding.

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IgG variable region sequences greatly affect cellular uptake and recycling

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Variable region charge patches affect FcRn binding and transport

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The presence of cognate antigen modulates cellular transport and FcRn binding

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Fc-engineering for improved FcRn binding can overcome unfavorable charge patches

Pharmacokinetic Developability and Disposition Profiles of Bispecific Antibodies: A Case Study with Two Molecules

Bispecific antibodies (BsAb) that engage multiple pathways are a promising therapeutic strategy to improve and prolong the efficacy of biologics in complex diseases. In the early stages of discovery, BsAbs often exhibit a broad range of pharmacokinetic (PK) behavior. Optimization of the neonatal Fc receptor (FcRn) interactions and removal of undesirable physiochemical properties have been used to improve the 'pharmacokinetic developability' for various monoclonal antibody (mAb) therapeutics, yet there is a sparsity of such information for BsAbs. The present work evaluated the influence of FcRn interactions and inherent physiochemical properties on the PK of two related single chain variable fragment (scFv)-based BsAbs. Despite their close relation, the two BsAbs exhibit disparate PK in cynomolgus monkeys with BsAb-1 having an aberrant clearance of ~2 mL/h/kg and BsAb-2 displaying a an ~10-fold slower clearance (~0.2 mL/h/kg). Evaluation of the physiochemical characteristics of the molecules, including charge, non-specific binding, thermal stability, and hydrophobic properties, as well as FcRn interactions showed some differences. In-depth drug disposition results revealed that a substantial disparity in the complete release from FcRn at a neutral pH is a primary factor contributing to the rapid clearance of the BsAb-1 while other biophysical characteristics were largely comparable between molecules.

Polyreactivity and polyspecificity in therapeutic antibody development: risk factors for failure in preclinical and clinical development campaigns

Antibody-based drugs, which now represent the dominant biologic therapeutic modality, are used to modulate disparate signaling pathways across diverse disease indications. One fundamental premise that has driven this therapeutic antibody revolution is the belief that each monoclonal antibody exhibits exquisitely specific binding to a single-drug target. Herein, we review emerging evidence in antibody off-target binding and relate current key findings to the risk of failure in therapeutic development. We further summarize the current state of understanding of structural mechanisms underpining the different phenomena that may drive polyreactivity and polyspecificity, and highlight current thinking on how de-risking studies may be best implemented in the screening triage. We conclude with a summary of what we believe to be key observations in the field to date, and a call for the wider antibody research community to work together to build the tools needed to maximize our understanding in this nascent area.

Interaction with 2,4-dinitrophenol correlates with polyreactivity, self-binding, and stability of clinical-stage therapeutic antibodies

Therapeutic antibodies should cover particular physicochemical and functional requirements for successful entry into clinical practice. Numerous experimental and computational approaches have been developed for early identification of different unfavourable features of antibodies. Immune repertoires of healthy humans contain a fraction of antibodies that recognize nitroarenes. These antibodies have been demonstrated to manifest antigen-binding polyreactivity. Here we observed that >20 % of 112 clinical stage therapeutic antibodies show pronounced binding to 2,4-dinitrophenol conjugated to albumin. This interaction predicts a number of unfavourable functional and physicochemical features of antibodies such as polyreactivity, tendency for self-association, stability and expression yields. Based on these findings we proposed a simple approach that may add to the armamentarium of assays for early identification of developability liabilities of antibodies intended for therapeutic use.

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.

Protein engineering of a stable and potent anti-inflammatory IL-37-Fc fusion with enhanced therapeutic potential

Harnessing the immunomodulatory activity of cytokines is a focus of therapies targeting inflammatory disease. The interleukin (IL)-1 superfamily contains pro-inflammatory and anti-inflammatory members that help orchestrate the immune response in adaptive and innate immunity. Of these molecules, IL-37 has robust anti-inflammatory activity across a range of disease models through inhibition of pro-inflammatory signaling cascades downstream of tumor necrosis factor, IL-1, and toll-like receptor pathways. We find that IL-37 is unstable with a poor pharmacokinetic and manufacturing profile. Here, we present the engineering of IL-37 from an unstable cytokine into an anti-inflammatory molecule with an excellent therapeutic likeness. We overcame these shortcomings through site-directed mutagenesis, the addition of a non-native disulfide bond, and the engineering of IL-37 as an Fc-fusion protein. Our results provide a platform for preclinical testing of IL-37 Fc-fusion proteins. The engineering approaches undertaken herein will apply to the conversion of similar potent yet short-acting cytokines into therapeutics.

Identification of a Zika NS2B epitope as a biomarker for severe clinical phenotypes

The identification of specific biomarkers for Zika infection and its clinical complications is fundamental to mitigate the infection spread, which has been associated with a broad range of neurological sequelae. We present the characterization of antibody responses in serum samples from individuals infected with Zika, presenting non-severe (classical) and severe (neurological disease) phenotypes, with high-density peptide arrays comprising the Zika NS1 and NS2B proteins. The data pinpoints one strongly IgG-targeted NS2B epitope in non-severe infections, which is absent in Zika patients, where infection progressed to the severe phenotype. This differential IgG profile between the studied groups was confirmed by multivariate data analysis. Molecular dynamics simulations and circular dichroism have shown that the peptide in solution presents itself in a sub-optimal conformation for antibody recognition, which led us to computationally engineer an artificial protein able to stabilize the NS2B epitope structure. The engineered protein was used to interrogate paired samples from mothers and their babies presenting Zika-associated microcephaly and confirmed the absence of NS2B IgG response in those samples. These findings suggest that the assessment of antibody responses to the herein identified NS2B epitope is a strong candidate biomarker for the diagnosis and prognosis of Zika-associated neurological disease.

Progress and challenges in mass spectrometry-based analysis of antibody repertoires

Humoral immunity is divided into the cellular B cell and protein-level antibody responses. High-throughput sequencing has advanced our understanding of both these fundamental aspects of B cell immunology as well as aspects pertaining to vaccine and therapeutics biotechnology. Although the protein-level serum and mucosal antibody repertoire make major contributions to humoral protection, the sequence composition and dynamics of antibody repertoires remain underexplored. This limits insight into important immunological and biotechnological parameters such as the number of antigen-specific antibodies, which are for example, relevant for pathogen neutralization, microbiota regulation, severity of autoimmunity, and therapeutic efficacy. High-resolution mass spectrometry (MS) has allowed initial insights into the antibody repertoire. We outline current challenges in MS-based sequence analysis of antibody repertoires and propose strategies for their resolution.