1
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Bashour H, Smorodina E, Pariset M, Zhong J, Akbar R, Chernigovskaya M, Lê Quý K, Snapkow I, Rawat P, Krawczyk K, Sandve GK, Gutierrez-Marcos J, Gutierrez DNZ, Andersen JT, Greiff V. Biophysical cartography of the native and human-engineered antibody landscapes quantifies the plasticity of antibody developability. Commun Biol 2024; 7:922. [PMID: 39085379 PMCID: PMC11291509 DOI: 10.1038/s42003-024-06561-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Accepted: 07/05/2024] [Indexed: 08/02/2024] Open
Abstract
Designing effective monoclonal antibody (mAb) therapeutics faces a multi-parameter optimization challenge known as "developability", which reflects an antibody's ability to progress through development stages based on its physicochemical properties. While natural antibodies may provide valuable guidance for mAb selection, we lack a comprehensive understanding of natural developability parameter (DP) plasticity (redundancy, predictability, sensitivity) and how the DP landscapes of human-engineered and natural antibodies relate to one another. These gaps hinder fundamental developability profile cartography. To chart natural and engineered DP landscapes, we computed 40 sequence- and 46 structure-based DPs of over two million native and human-engineered single-chain antibody sequences. We find lower redundancy among structure-based compared to sequence-based DPs. Sequence DP sensitivity to single amino acid substitutions varied by antibody region and DP, and structure DP values varied across the conformational ensemble of antibody structures. We show that sequence DPs are more predictable than structure-based ones across different machine-learning tasks and embeddings, indicating a constrained sequence-based design space. Human-engineered antibodies localize within the developability and sequence landscapes of natural antibodies, suggesting that human-engineered antibodies explore mere subspaces of the natural one. Our work quantifies the plasticity of antibody developability, providing a fundamental resource for multi-parameter therapeutic mAb design.
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Affiliation(s)
- Habib Bashour
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway.
- School of Life Sciences, University of Warwick, Coventry, UK.
| | - Eva Smorodina
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | | | - Jahn Zhong
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
- Division of Genetics, Department Biology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Rahmad Akbar
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Maria Chernigovskaya
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Khang Lê Quý
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Igor Snapkow
- Department of Chemical Toxicology, Norwegian Institute of Public Health, Oslo, Norway
| | - Puneet Rawat
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | | | | | | | | | - Jan Terje Andersen
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Pharmacology, University of Oslo and Oslo University Hospital, Oslo, Norway
- Precision Immunotherapy Alliance (PRIMA), University of Oslo, Oslo, Norway
| | - Victor Greiff
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway.
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2
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Wang S, Zhang W, Yang B, Zhang X, Fang J, Rui H, Chen Z, Gu J, Chen Z, Xu J. A case study of a bispecific antibody manufacturability assessment and optimization during discovery stage and its implications. Antib Ther 2024; 7:189-198. [PMID: 39036070 PMCID: PMC11259756 DOI: 10.1093/abt/tbae013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Revised: 05/20/2024] [Accepted: 05/21/2024] [Indexed: 07/23/2024] Open
Abstract
The manufacturability assessment and optimization of bispecific antibodies (bsAbs) during the discovery stage are crucial for the success of the drug development process, impacting the speed and cost of advancing such therapeutics to the Investigational New Drug (IND) stage and ultimately to the market. The complexity of bsAbs creates challenges in employing effective evaluation methods to detect developability risks in early discovery stage, and poses difficulties in identifying the root causes and implementing subsequent engineering solutions. This study presents a case of engineering a bsAb that displayed a normal solution appearance during the discovery phase but underwent significant precipitation when subjected to agitation stress during 15 L Chemistry, Manufacturing, and Control (CMC) production Leveraging analytical tools, structural analysis, in silico prediction, and wet-lab validations, the key molecular origins responsible for the observed precipitation were identified and addressed. Sequence engineering to reduce protein surface hydrophobicity and enhance conformational stability proved effective in resolving agitation-induced aggregation. The refined bsAb sequences enabled successful mass production in CMC department. The findings of this case study contribute to the understanding of the fundamental mechanism of agitation-induced aggregation and offer a potential protein engineering procedure for addressing similar issues in bsAb. Furthermore, this case study emphasizes the significance of a close partnership between Discovery and CMC teams. Integrating CMC's rigorous evaluation methods with Discovery's engineering capability can facilitate a streamlined development process for bsAb molecules.
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Affiliation(s)
- Shuang Wang
- Biologics Innovation Discovery, WuXi Biologics, 1951 Huifeng West Road, Fengxian District, Shanghai, 201400, China
| | - Weijie Zhang
- Biologics Innovation Discovery, WuXi Biologics, 1951 Huifeng West Road, Fengxian District, Shanghai, 201400, China
| | - Baotian Yang
- Biologics Innovation Discovery, WuXi Biologics, 1951 Huifeng West Road, Fengxian District, Shanghai, 201400, China
| | - Xudong Zhang
- Downstream Process Development (DSPD), WuXi Biologics, 288 Fute Zhong Road, Waigaoqiao Free Trade Zone, Shanghai, 200131, China
| | - Jing Fang
- Biologics Innovation Discovery, WuXi Biologics, 1951 Huifeng West Road, Fengxian District, Shanghai, 201400, China
| | - Haopeng Rui
- D3 Bio (Wuxi) Co., Ltd., 1101, 11/F, Building 1, No.6, Lane 38, Yuanshen Road, Pudong, Shanghai, 200120, China
| | - Zhijian Chen
- D3 Bio (Wuxi) Co., Ltd., 1101, 11/F, Building 1, No.6, Lane 38, Yuanshen Road, Pudong, Shanghai, 200120, China
| | - Jijie Gu
- Biologics Innovation Discovery, WuXi Biologics, 1951 Huifeng West Road, Fengxian District, Shanghai, 201400, China
| | - Zhiqiang Chen
- D3 Bio (Wuxi) Co., Ltd., 1101, 11/F, Building 1, No.6, Lane 38, Yuanshen Road, Pudong, Shanghai, 200120, China
| | - Jianqing Xu
- Biologics Innovation Discovery, WuXi Biologics, 1951 Huifeng West Road, Fengxian District, Shanghai, 201400, China
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3
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Isu S, Vinskus L, Silva D, Cunningham K, Elich T, Greenhalgh P, Sokolnicki A, Raghunath B. Leveraging bioanalytical characterization of fractionated monoclonal antibody pools to identify aggregation-prone and less filterable proteoforms during virus filtration. Biotechnol Prog 2024; 40:e3451. [PMID: 38450976 DOI: 10.1002/btpr.3451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 01/11/2024] [Accepted: 02/19/2024] [Indexed: 03/08/2024]
Abstract
Monoclonal antibodies (mAbs) are an essential class of biotherapeutics. A platform process is used for mAb development to ensure clinically safe and stable molecules. Regulatory authorities ensure that mAb production processes include sufficient viral clearance steps to achieve less than one virus particle per million doses of product. Virus filtration is used for size-based removal of enveloped and nonenveloped viruses during downstream processing of mAbs. Process development in mAb purification relies on empirical approaches and often includes adsorptive prefiltration to mitigate virus filter fouling. Opportunities for molecular-level prediction of mAb filterability are needed to plug the existing knowledge gap in downstream processing. A molecular-level approach to understanding the factors influencing mAb filterability may reduce process development time, material loss, and processing costs due to oversized virus filters. In this work, pH step gradient fractionation was applied on polished bulk mAb feed to obtain concentrated pools of fractionated mAb variants. Biophysical properties and quality attributes of fractionated pools, including oligomeric state (size), isoelectric point profile, diffusion interaction parameters, and glycoform profile, were determined using bioanalytical methods. Filterability (loading and throughput) of fractionated pools were evaluated. Statistical methods were used to obtain correlations between quality attributes of mAb fractions and filterability on the Viresolve Pro virus filter.
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Affiliation(s)
- Solomon Isu
- Process Solutions, MilliporeSigma, Burlington, Massachusetts, USA
| | - Lilia Vinskus
- Process Solutions, MilliporeSigma, Burlington, Massachusetts, USA
| | - Derek Silva
- Process Solutions, MilliporeSigma, Burlington, Massachusetts, USA
| | | | - Thomas Elich
- Process Solutions, MilliporeSigma, Burlington, Massachusetts, USA
| | | | - Adam Sokolnicki
- Process Solutions, MilliporeSigma, Burlington, Massachusetts, USA
| | - Bala Raghunath
- Process Solutions, MilliporeSigma, Burlington, Massachusetts, USA
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4
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Li C, Yao QQ, Li J. Druggability properties of a L309K mutation in the antibody CH2 domain. 3 Biotech 2024; 14:152. [PMID: 38742229 PMCID: PMC11088599 DOI: 10.1007/s13205-024-04000-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 04/28/2024] [Indexed: 05/16/2024] Open
Abstract
In the early stages of antibody drug development, it is imperative to conduct a comprehensive assessment and enhancement of the druggability attributes of potential molecules by considering their fundamental physicochemical properties. This study specifically concentrates on the surface-exposed hydrophobic region of the candidate antibody aPDL1-WT and explores the effectiveness of the L309K mutation strategy. The resulting aPDL1-LK variant demonstrates a notable enhancement over the original antibody in addressing the issue of aggregation and formation of large molecular impurities under accelerated high-temperature conditions. The mutated molecule, aPDL1-LK, exhibits excellent physicochemical properties such as hydrophilicity, conformational stability, charge variant stability, post-translational modifications, and serum stability. In terms of biological function, aPDL1-LK maintains the same glycosylation pattern as the original antibody and shows no significant difference in affinity for antigen hPDL1 protein, CD16a-F158, CD64, CD32a-H131, and complement C1q, compared to aPDL1-WT. The L309K mutation results in an approximately twofold reduction in its affinity for CD16a-V158 and CD32a-R131. In vitro biological assays, including antibody-dependent cell-mediated cytotoxicity (ADCC), antibody-dependent cellular phagocytosis (ADCP), and complement-dependent cytotoxicity (CDC), reveal that the L309K mutation may decrease CD16a-V158-mediated ADCC activity due to the mutation-induced decrease in ligand affinity, while not affect CD32a-R131-mediated ADCP activity. In conclusion, the L309K mutation offers a promising strategy to enhance the druggability properties of candidate antibodies.
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Affiliation(s)
- Cui Li
- Department of Pharmacy, Zhejiang Provincial Hospital of Chinese Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, 310000 Zhejiang China
| | - Qing-qing Yao
- Department of Pharmacy, The First Affiliated Hospital of Soochow University, Suzhou, 215000 Jiangsu China
| | - Jiang Li
- Department of Pharmacy, Zhejiang Provincial Hospital of Chinese Medicine, The First Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, 310000 Zhejiang China
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5
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Gordon GL, Raybould MIJ, Wong A, Deane CM. Prospects for the computational humanization of antibodies and nanobodies. Front Immunol 2024; 15:1399438. [PMID: 38812514 PMCID: PMC11133524 DOI: 10.3389/fimmu.2024.1399438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 05/02/2024] [Indexed: 05/31/2024] Open
Abstract
To be viable therapeutics, antibodies must be tolerated by the human immune system. Rational approaches to reduce the risk of unwanted immunogenicity involve maximizing the 'humanness' of the candidate drug. However, despite the emergence of new discovery technologies, many of which start from entirely human gene fragments, most antibody therapeutics continue to be derived from non-human sources with concomitant humanization to increase their human compatibility. Early experimental humanization strategies that focus on CDR loop grafting onto human frameworks have been critical to the dominance of this discovery route but do not consider the context of each antibody sequence, impacting their success rate. Other challenges include the simultaneous optimization of other drug-like properties alongside humanness and the humanization of fundamentally non-human modalities such as nanobodies. Significant efforts have been made to develop in silico methodologies able to address these issues, most recently incorporating machine learning techniques. Here, we outline these recent advancements in antibody and nanobody humanization, focusing on computational strategies that make use of the increasing volume of sequence and structural data available and the validation of these tools. We highlight that structural distinctions between antibodies and nanobodies make the application of antibody-focused in silico tools to nanobody humanization non-trivial. Furthermore, we discuss the effects of humanizing mutations on other essential drug-like properties such as binding affinity and developability, and methods that aim to tackle this multi-parameter optimization problem.
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Affiliation(s)
| | | | | | - Charlotte M. Deane
- Oxford Protein Informatics Group, Department of Statistics, University of Oxford, Oxford, United Kingdom
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6
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Minatel VM, Prudencio CR, Barraviera B, Ferreira RS. Nanobodies: a promising approach to treatment of viral diseases. Front Immunol 2024; 14:1303353. [PMID: 38322011 PMCID: PMC10844482 DOI: 10.3389/fimmu.2023.1303353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 12/12/2023] [Indexed: 02/08/2024] Open
Abstract
Since their discovery in the 1990s, heavy chain antibodies have garnered significant interest in the scientific community. These antibodies, found in camelids such as llamas and alpacas, exhibit distinct characteristics from conventional antibodies due to the absence of a light chain in their structure. Furthermore, they possess a single antigen-binding domain known as VHH or Nanobody (Nb). With a small size of approximately 15 kDa, these Nbs demonstrate improved characteristics compared to conventional antibodies, including greater physicochemical stability and enhanced biodistribution, enabling them to bind inaccessible epitopes more effectively. As a result, Nbs have found numerous applications in various medical and veterinary fields, particularly in diagnostics and therapeutics. Advances in biotechnology have made the production of recombinant antibodies feasible and compatible with large-scale manufacturing. Through the construction of immune phage libraries that display VHHs and subsequent selection through biopanning, it has become possible to isolate specific Nbs targeting pharmaceutical targets of interest, such as viruses. This review describes the processes involved in nanobody production, from hyperimmunization to purification, with the aim of their application in the pharmaceutical industry.
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Affiliation(s)
- Vitória Meneghetti Minatel
- Center for the Study of Venoms and Venomous Animals (CEVAP), São Paulo State University (UNESP—Univ Estadual Paulista), Botucatu, São Paulo, Brazil
| | | | - Benedito Barraviera
- Center for the Study of Venoms and Venomous Animals (CEVAP), São Paulo State University (UNESP—Univ Estadual Paulista), Botucatu, São Paulo, Brazil
- Graduate Program in Tropical Diseases, Botucatu Medical School (FMB), São Paulo State University (UNESP—Univ Estadual Paulista), Botucatu, São Paulo, Brazil
| | - Rui Seabra Ferreira
- Center for the Study of Venoms and Venomous Animals (CEVAP), São Paulo State University (UNESP—Univ Estadual Paulista), Botucatu, São Paulo, Brazil
- Graduate Program in Tropical Diseases, Botucatu Medical School (FMB), São Paulo State University (UNESP—Univ Estadual Paulista), Botucatu, São Paulo, Brazil
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7
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Makowski EK, Chen HT, Wang T, Wu L, Huang J, Mock M, Underhill P, Pelegri-O’Day E, Maglalang E, Winters D, Tessier PM. Reduction of monoclonal antibody viscosity using interpretable machine learning. MAbs 2024; 16:2303781. [PMID: 38475982 PMCID: PMC10939158 DOI: 10.1080/19420862.2024.2303781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 01/05/2024] [Indexed: 03/14/2024] Open
Abstract
Early identification of antibody candidates with drug-like properties is essential for simplifying the development of safe and effective antibody therapeutics. For subcutaneous administration, it is important to identify candidates with low self-association to enable their formulation at high concentration while maintaining low viscosity, opalescence, and aggregation. Here, we report an interpretable machine learning model for predicting antibody (IgG1) variants with low viscosity using only the sequences of their variable (Fv) regions. Our model was trained on antibody viscosity data (>100 mg/mL mAb concentration) obtained at a common formulation pH (pH 5.2), and it identifies three key Fv features of antibodies linked to viscosity, namely their isoelectric points, hydrophobic patch sizes, and numbers of negatively charged patches. Of the three features, most predicted antibodies at risk for high viscosity, including antibodies with diverse antibody germlines in our study (79 mAbs) as well as clinical-stage IgG1s (94 mAbs), are those with low Fv isoelectric points (Fv pIs < 6.3). Our model identifies viscous antibodies with relatively high accuracy not only in our training and test sets, but also for previously reported data. Importantly, we show that the interpretable nature of the model enables the design of mutations that significantly reduce antibody viscosity, which we confirmed experimentally. We expect that this approach can be readily integrated into the drug development process to reduce the need for experimental viscosity screening and improve the identification of antibody candidates with drug-like properties.
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Affiliation(s)
- Emily K. Makowski
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Hsin-Ting Chen
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Tiexin Wang
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Lina Wu
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Jie Huang
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
| | - Marissa Mock
- Therapeutic Discovery, Research, Amgen Inc, Thousand Oaks, CA, USA
| | - Patrick Underhill
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
| | | | - Erick Maglalang
- Drug Product Technologies, Amgen Inc, Thousand Oaks, CA, USA
| | - Dwight Winters
- Therapeutic Discovery, Research, Amgen Inc, Thousand Oaks, CA, USA
| | - Peter M. Tessier
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
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8
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Jain T, Prinz B, Marker A, Michel A, Reichel K, Czepczor V, Klieber S, Sun W, Kathuria S, Oezguer Bruederle S, Lange C, Wahl L, Starr C, Masiero A, Avery L. Assessment and incorporation of in vitro correlates to pharmacokinetic outcomes in antibody developability workflows. MAbs 2024; 16:2384104. [PMID: 39083118 PMCID: PMC11296533 DOI: 10.1080/19420862.2024.2384104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 06/27/2024] [Accepted: 07/19/2024] [Indexed: 08/04/2024] Open
Abstract
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.
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Affiliation(s)
- Tushar Jain
- Department of Computational Biology, Adimab LLC, Mountain View, CA, USA
| | - Bianka Prinz
- Department of Antibody Discovery, Adimab LLC, Lebanon, NH, USA
| | - Alexander Marker
- Department of Drug Metabolism and Pharmacokinetics, Sanofi, Frankfurt, Germany
| | - Alexander Michel
- Department of Drug Metabolism and Pharmacokinetics, Sanofi, Cambridge, MA, USA
| | - Katrin Reichel
- Department of Large Molecule Research, Sanofi, Frankfurt, Germany
| | - Valerie Czepczor
- Department of Drug Metabolism and Pharmacokinetics, Sanofi, Paris, France
| | - Sylvie Klieber
- Department of Drug Metabolism and Pharmacokinetics, Sanofi, Paris, France
| | - Wei Sun
- Department of Drug Metabolism and Pharmacokinetics, Sanofi, Cambridge, MA, USA
| | - Sagar Kathuria
- Department of Large Molecule Research, Sanofi, Cambridge, MA, USA
| | | | - Christian Lange
- Department of Large Molecule Research, Sanofi, Frankfurt, Germany
| | - Lena Wahl
- Department of Large Molecule Research, Sanofi, Frankfurt, Germany
| | | | | | - Lindsay Avery
- Department of Drug Metabolism and Pharmacokinetics, Sanofi, Cambridge, MA, USA
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9
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Jain T, Boland T, Vásquez M. Identifying developability risks for clinical progression of antibodies using high-throughput in vitro and in silico approaches. MAbs 2023; 15:2200540. [PMID: 37072706 PMCID: PMC10114995 DOI: 10.1080/19420862.2023.2200540] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 04/03/2023] [Accepted: 04/04/2023] [Indexed: 04/20/2023] Open
Abstract
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.
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Affiliation(s)
| | - Todd Boland
- Computational Biology, Adimab LLC, Lebanon, NH, USA
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10
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Müller T, Tasser C, Tesar M, Fucek I, Schniegler-Mattox U, Koch J, Ellwanger K. Selection of bispecific antibodies with optimal developability using FcRn‑Ph‑HPLC as an optimized FcRn affinity chromatography method. MAbs 2023; 15:2245519. [PMID: 37599441 PMCID: PMC10443974 DOI: 10.1080/19420862.2023.2245519] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 07/27/2023] [Accepted: 08/03/2023] [Indexed: 08/22/2023] Open
Abstract
A challenge when developing therapeutic antibodies is the identification of candidates with favorable pharmacokinetics (PK) early in development. A key determinant of immunoglobulin (IgG) serum half‑life in vivo is the efficiency of pH-dependent binding to the neonatal Fc receptor (FcRn). Numerous studies have proposed techniques to assess FcRn binding of IgG-based therapeutics in vitro, enabling prediction of serum half-life prior to clinical assessment. FcRn high-performance liquid chromatography (HPLC) assays FcRn binding of therapeutic IgGs across a pH gradient, allowing the correlation of IgG column retention time to the half‑life of a therapeutic IgG in vivo. However, as FcRn retention time cannot be directly compared to an in vivo parameter, modifications to FcRn-HPLC are required to enable interpretation of the data within a physiological context, to provide more accurate estimations of serum half-life. This study presents an important modification to this method, FcRn-pH-HPLC, which reproducibly measures FcRn dissociation pH, allowing correlation with previously established half-lives of therapeutic antibodies. Furthermore, the influence of incorporating various antibody modifications, binding modules, and their orientations within IgGs and bispecifics on FcRn dissociation pH was evaluated using antibodies from the redirected optimized cell killing (ROCK®) platform. Target and effector antigen-binding domain sequences, their presentation format and orientation within a bispecific antibody alter FcRn retention; tested Fc domain modifications and incorporating stabilizing disulfide bonds had minimal effect. This study may inform the generation of mono-, bi- and multi-specific antibodies with tailored half-lives based on FcRn binding properties in vitro, to differentiate antibody-based therapeutic candidates with optimal developability.
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Affiliation(s)
- Thomas Müller
- Discovery Research and Translational Immunology, Affimed GmbH, Heidelberg, Germany
| | - Carolin Tasser
- Discovery Research and Translational Immunology, Affimed GmbH, Heidelberg, Germany
| | - Michael Tesar
- Discovery Research and Translational Immunology, Affimed GmbH, Heidelberg, Germany
| | - Ivica Fucek
- Discovery Research and Translational Immunology, Affimed GmbH, Heidelberg, Germany
| | | | - Joachim Koch
- Discovery Research and Translational Immunology, Affimed GmbH, Heidelberg, Germany
| | - Kristina Ellwanger
- Discovery Research and Translational Immunology, Affimed GmbH, Heidelberg, Germany
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