1
|
Zürcher D, Wuchner K, Arosio P. Real-Time Observation of Protein Aggregation at Liquid-Liquid Interfaces in a Microfluidic Device. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024:e2401085. [PMID: 39175118 DOI: 10.1002/smll.202401085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 07/04/2024] [Indexed: 08/24/2024]
Abstract
A droplet microfluidic device to capture in real-time protein aggregation at liquid-liquid interfaces is described. In contrast to conventional methods, typically characterized by a lag time between the application of interfacial stress and the measurement of protein aggregation, here protein adsorption, the formation of a viscoelastic protein layer, aggregation, and shedding of protein particles into solution is simultaneously monitored. The device is applied to analyze the stability of antibody formulations over a wide range of concentrations (1-180 mg mL-1) at the silicone oil (SO)-water interface under controlled mechanical deformation. The adsorption onto oil droplets induces the formation of a viscoelastic protein layer on a subsecond timescale, which progressively restricts the relaxation of the droplets within the chip. Upon mechanical rupture, the protein layer releases particles in solution. The rate of particle formation increases strongly with concentration, similar to the bulk viscosity. Concentrations above 120 mg mL-1 lead to aggregation in seconds and drastically decrease the mechanical perturbations required to shed protein particles in solution. These results are important for the development of formulations at high-protein concentrations (>100 mg mL-1) and indicate that particular attention should be given to interface-induced particle formation in this concentration range. In this context, low-volume microfluidic platforms allow the assessment of protein physical instabilities early in development and represent attractive tools to optimize antibody stability and formulation design consuming limited amounts of material.
Collapse
Affiliation(s)
- Dominik Zürcher
- ETH Zürich, Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, Zürich, 8093, Switzerland
| | - Klaus Wuchner
- Cilag GmbH International, a division of Johnson & Johnson, TDS-Biologics, Analytical Development, Schaffhausen, 8200, Switzerland
| | - Paolo Arosio
- ETH Zürich, Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, Zürich, 8093, Switzerland
| |
Collapse
|
2
|
Xiong J, Wu G, Ning J, Yan J, Yang J, Kang J. Neutralizing antibody against GDF15 for treatment of cancer-associated cachexia. PLoS One 2024; 19:e0309394. [PMID: 39172988 PMCID: PMC11341059 DOI: 10.1371/journal.pone.0309394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 08/05/2024] [Indexed: 08/24/2024] Open
Abstract
GDF15 (growth differentiation factor 15), also known as macrophage inhibitory cytokine 1 (MIC-1), is a circulating protein involved in the regulation of energy balance and weight control. Elevated levels of GDF15 have been associated with cachexia and reduced survival rates in cancer patients. Through the activation of the GFRAL (GDNF-family receptor α-like)-RET (Rearranged during Transfection) signaling pathway, GDF15 can induce weight loss, making it a potential target for treating cachexia. Currently, there are no approved antibody drugs specifically targeting GDF15 for cancer cachexia treatment. However, efforts have been made to develop antibody-based therapeutics against this emerging target. In this study, we generated a monoclonal antibody KY-NAb-GDF15 against GDF15 that effectively blocks downstream signaling mediated by GFRAL upon stimulation by GDF15. This antibody demonstrates robust neutralizing activity and exhibits high binding specificity. Importantly, our findings indicate that this antibody holds promise in alleviating cancer-induced cachexia and mitigating chemotherapy-induced weight loss, thereby offering significant therapeutic potential for managing cancer cachexia.
Collapse
Affiliation(s)
- Junyi Xiong
- College of Pharmacy, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Guojin Wu
- KYINNO Biotechnology (Beijing) Co., Ltd., Beijing, China
| | - Jinying Ning
- KYINNO Biotechnology (Beijing) Co., Ltd., Beijing, China
| | - Junlin Yan
- College of Pharmacy, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Jian Yang
- College of Pharmacy, Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Jinsen Kang
- College of Pharmacy, Xinjiang Medical University, Urumqi, Xinjiang, China
- Engineering Research Center of Xinjiang and Central Asian Medicine Resources, Ministry of Education, Urumqi, Xinjiang, China
| |
Collapse
|
3
|
Makey DM, Ruotolo BT. Liquid-phase separations coupled with ion mobility-mass spectrometry for next-generation biopharmaceutical analysis. Expert Rev Proteomics 2024; 21:259-270. [PMID: 38934922 PMCID: PMC11299228 DOI: 10.1080/14789450.2024.2373707] [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: 03/28/2024] [Accepted: 06/06/2024] [Indexed: 06/28/2024]
Abstract
INTRODUCTION The pharmaceutical industry continues to expand its search for innovative biotherapeutics. The comprehensive characterization of such therapeutics requires many analytical techniques to fully evaluate critical quality attributes, making analysis a bottleneck in discovery and development timelines. While thorough characterization is crucial for ensuring the safety and efficacy of biotherapeutics, there is a need to further streamline analytical characterization and expedite the overall timeline from discovery to market. AREAS COVERED This review focuses on recent developments in liquid-phase separations coupled with ion mobility-mass spectrometry (IM-MS) for the development and characterization of biotherapeutics. We cover uses of IM-MS to improve the characterization of monoclonal antibodies, antibody-drug conjugates, host cell proteins, glycans, and nucleic acids. This discussion is based on an extensive literature search using Web of Science, Google Scholar, and SciFinder. EXPERT OPINION IM-MS has the potential to enhance the depth and efficiency of biotherapeutic characterization by providing additional insights into conformational changes, post-translational modifications, and impurity profiles. The rapid timescale of IM-MS positions it well to enhance the information content of existing assays through its facile integration with standard liquid-phase separation techniques that are commonly used for biopharmaceutical analysis.
Collapse
Affiliation(s)
- Devin M Makey
- Department of Chemistry, University of Michigan, Ann Arbor, MI, USA
| | | |
Collapse
|
4
|
Kuravsky M, Gibbons GF, Joyce C, Scott-Tucker A, Macpherson A, Lawson ADG. Modular design of bi- and multi-specific knob domain fusions. Front Immunol 2024; 15:1384467. [PMID: 38605965 PMCID: PMC11008599 DOI: 10.3389/fimmu.2024.1384467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 03/11/2024] [Indexed: 04/13/2024] Open
Abstract
Introduction The therapeutic potential of bispecific antibodies is becoming widely recognised, with over a hundred formats already described. For many applications, enhanced tissue penetration is sought, so bispecifics with low molecular weight may offer a route to enhanced potency. Here we report the design of bi- and tri-specific antibody-based constructs with molecular weights as low as 14.5 and 22 kDa respectively. Methods Autonomous bovine ultra-long CDR H3 (knob domain peptide) modules have been engineered with artificial coiled-coil stalks derived from Sin Nombre orthohantavirus nucleocapsid protein and human Beclin-1, and joined in series to produce bi- and tri-specific antibody-based constructs with exceptionally low molecular weights. Results Knob domain peptides with coiled-coil stalks retain high, independent antigen binding affinity, exhibit exceptional levels of thermal stability, and can be readily joined head-to-tail yielding the smallest described multi-specific antibody format. The resulting constructs are able to bind simultaneously to all their targets with no interference. Discussion Compared to existing bispecific formats, the reduced molecular weight of the knob domain fusions may enable enhanced tissue penetration and facilitate binding to cryptic epitopes that are inaccessible to conventional antibodies. Furthermore, they can be easily produced at high yield as recombinant products and are free from the heavy-light chain mispairing issue. Taken together, our approach offers an efficient route to modular construction of minimalistic bi- and multi-specifics, thereby further broadening the therapeutic scope for knob domain peptides.
Collapse
|
5
|
Park E, Izadi S. Molecular surface descriptors to predict antibody developability: sensitivity to parameters, structure models, and conformational sampling. MAbs 2024; 16:2362788. [PMID: 38853585 PMCID: PMC11168226 DOI: 10.1080/19420862.2024.2362788] [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: 11/28/2023] [Accepted: 05/29/2024] [Indexed: 06/11/2024] Open
Abstract
In silico assessment of antibody developability during early lead candidate selection and optimization is of paramount importance, offering a rapid and material-free screening approach. However, the predictive power and reproducibility of such methods depend heavily on the selection of molecular descriptors, model parameters, accuracy of predicted structure models, and conformational sampling techniques. Here, we present a set of molecular surface descriptors specifically designed for predicting antibody developability. We assess the performance of these descriptors by benchmarking their correlations with an extensive array of experimentally determined biophysical properties, including viscosity, aggregation, hydrophobic interaction chromatography, human pharmacokinetic clearance, heparin retention time, and polyspecificity. Further, we investigate the sensitivity of these surface descriptors to methodological nuances, such as the choice of interior dielectric constant, hydrophobicity scales, structure prediction methods, and the impact of conformational sampling. Notably, we observe systematic shifts in the distribution of surface descriptors depending on the structure prediction method used, driving weak correlations of surface descriptors across structure models. Averaging the descriptor values over conformational distributions from molecular dynamics mitigates the systematic shifts and improves the consistency across different structure prediction methods, albeit with inconsistent improvements in correlations with biophysical data. Based on our benchmarking analysis, we propose six in silico developability risk flags and assess their effectiveness in predicting potential developability issues for a set of case study molecules.
Collapse
Affiliation(s)
- Eliott Park
- Pharmaceutical Development, Genentech Inc, South San Francisco, CA, USA
| | - Saeed Izadi
- Pharmaceutical Development, Genentech Inc, South San Francisco, CA, USA
| |
Collapse
|
6
|
Norden DM, Navia CT, Sullivan JT, Doranz BJ. The emergence of cell-based protein arrays to test for polyspecific off-target binding of antibody therapeutics. MAbs 2024; 16:2393785. [PMID: 39180756 PMCID: PMC11346545 DOI: 10.1080/19420862.2024.2393785] [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: 05/28/2024] [Revised: 08/05/2024] [Accepted: 08/14/2024] [Indexed: 08/26/2024] Open
Abstract
Specificity profiling is a requirement for monoclonal antibodies (mAbs) and antibody-directed biotherapeutics such as CAR-T cells prior to initiating human trials. However, traditional approaches to assess the specificity of mAbs, primarily tissue cross-reactivity studies, have been unreliable, leading to off-target binding going undetected. Here, we review the emergence of cell-based protein arrays as an alternative and improved assessment of mAb specificity. Cell-based protein arrays assess binding across the full human membrane proteome, ~6,000 membrane proteins each individually expressed in their native structural configuration within live or unfixed cells. Our own profiling indicates a surprisingly high off-target rate across the industry, with 33% of lead candidates displaying off-target binding. Moreover, about 20% of therapeutic mAbs in clinical development and currently on the market display off-target binding. Case studies and off-target rates at different phases of biotherapeutic drug approval suggest that off-target binding is likely a major cause of adverse events and drug attrition.
Collapse
|
7
|
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.
Collapse
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
| |
Collapse
|
8
|
Herling TW, Invernizzi G, Ausserwöger H, Bjelke JR, Egebjerg T, Lund S, Lorenzen N, Knowles TPJ. Nonspecificity fingerprints for clinical-stage antibodies in solution. Proc Natl Acad Sci U S A 2023; 120:e2306700120. [PMID: 38109540 PMCID: PMC10756282 DOI: 10.1073/pnas.2306700120] [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: 04/28/2023] [Accepted: 11/06/2023] [Indexed: 12/20/2023] Open
Abstract
Monoclonal antibodies (mAbs) have successfully been developed for the treatment of a wide range of diseases. The clinical success of mAbs does not solely rely on optimal potency and safety but also require good biophysical properties to ensure a high developability potential. In particular, nonspecific interactions are a key developability parameter to monitor during discovery and development. Despite an increased focus on the detection of nonspecific interactions, their underlying physicochemical origins remain poorly understood. Here, we employ solution-based microfluidic technologies to characterize a set of clinical-stage mAbs and their interactions with commonly used nonspecificity ligands to generate nonspecificity fingerprints, providing quantitative data on the underlying physical chemistry. Furthermore, the solution-based analysis enables us to measure binding affinities directly, and we evaluate the contribution of avidity in nonspecific binding by mAbs. We find that avidity can increase the apparent affinity by two orders of magnitude. Notably, we find that a subset of these highly developed mAbs show nonspecific electrostatic interactions, even at physiological pH and ionic strength, and that they can form microscale particles with charge-complementary polymers. The group of mAb constructs flagged here for nonspecificity are among the worst performers in independent reports of surface and column-based screens. The solution measurements improve on the state-of-the-art by providing a stand-alone result for individual mAbs without the need to benchmark against cohort data. Based on our findings, we propose a quantitative solution-based nonspecificity score, which can be integrated in the development workflow for biological therapeutics and more widely in protein engineering.
Collapse
Affiliation(s)
- Therese W. Herling
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | | | - Hannes Ausserwöger
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Jais Rose Bjelke
- Global Research Technologies, Novo Nordisk A/S, Måløv2760, Denmark
| | - Thomas Egebjerg
- Global Research Technologies, Novo Nordisk A/S, Måløv2760, Denmark
| | - Søren Lund
- Global Research Technologies, Novo Nordisk A/S, Måløv2760, Denmark
| | - Nikolai Lorenzen
- Global Research Technologies, Novo Nordisk A/S, Måløv2760, Denmark
| | - Tuomas P. J. Knowles
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
- Department of Physics, University of Cambridge, CambridgeCB3 0HE, United Kingdom
| |
Collapse
|
9
|
Sun Z, Chu X, Adams C, Ilina TV, Guerrero M, Lin G, Chen C, Jelev D, Ishima R, Li W, Mellors JW, Calero G, Dimitrov DS. Preclinical assessment of a novel human antibody VH domain targeting mesothelin as an antibody-drug conjugate. Mol Ther Oncolytics 2023; 31:100726. [PMID: 37771390 PMCID: PMC10522976 DOI: 10.1016/j.omto.2023.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 09/08/2023] [Indexed: 09/30/2023] Open
Abstract
Mesothelin (MSLN) has been a validated tumor-associated antigen target for several solid tumors for over a decade, making it an attractive option for therapeutic interventions. Novel antibodies with high affinity and better therapeutic properties are needed. In the current study, we have isolated and characterized a novel heavy chain variable (VH) domain 3C9 from a large-size human immunoglobulin VH domain library. 3C9 exhibited high affinity (KD [dissociation constant] <3 nM) and binding specificity in a membrane proteome array (MPA). In a mouse xenograft model, 3C9 fused to human IgG1 Fc was detected at tumor sites as early as 8 h post-infusion and remained at the site for over 10 days. Furthermore, 3C9 fused to a human Fc domain drug conjugate effectively inhibited MSLN-positive tumor growth in a mouse xenograft model. The X-ray crystal structure of full-length MSLN in complex with 3C9 reveals interaction of the 3C9 domains with two distinctive residue patches on the MSLN surface. This newly discovered VH antibody domain has a high potential as a therapeutic candidate for MSLN-expressing cancers.
Collapse
Affiliation(s)
- Zehua Sun
- Center for Antibody Therapeutics, Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, 3550 Terrace Street, Pittsburgh, PA 15261, USA
| | - Xiaojie Chu
- Center for Antibody Therapeutics, Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, 3550 Terrace Street, Pittsburgh, PA 15261, USA
| | - Cynthia Adams
- Abound Bio, 1401 Forbes Avenue, Pittsburgh, PA 15219, USA
| | - Tatiana V. Ilina
- Department of Structural Biology, University of Pittsburgh School of Medicine, 3501 Fifth Avenue, Pittsburgh, PA 15260, USA
| | - Michel Guerrero
- Department of Structural Biology, University of Pittsburgh School of Medicine, 3501 Fifth Avenue, Pittsburgh, PA 15260, USA
| | - Guowu Lin
- Department of Structural Biology, University of Pittsburgh School of Medicine, 3501 Fifth Avenue, Pittsburgh, PA 15260, USA
| | - Chuan Chen
- Center for Antibody Therapeutics, Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, 3550 Terrace Street, Pittsburgh, PA 15261, USA
| | - Dontcho Jelev
- Center for Antibody Therapeutics, Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, 3550 Terrace Street, Pittsburgh, PA 15261, USA
| | - Rieko Ishima
- Department of Structural Biology, University of Pittsburgh School of Medicine, 3501 Fifth Avenue, Pittsburgh, PA 15260, USA
| | - Wei Li
- Center for Antibody Therapeutics, Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, 3550 Terrace Street, Pittsburgh, PA 15261, USA
| | - John W. Mellors
- Center for Antibody Therapeutics, Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, 3550 Terrace Street, Pittsburgh, PA 15261, USA
- Abound Bio, 1401 Forbes Avenue, Pittsburgh, PA 15219, USA
| | - Guillermo Calero
- Department of Structural Biology, University of Pittsburgh School of Medicine, 3501 Fifth Avenue, Pittsburgh, PA 15260, USA
| | - Dimiter S. Dimitrov
- Center for Antibody Therapeutics, Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, 3550 Terrace Street, Pittsburgh, PA 15261, USA
- Abound Bio, 1401 Forbes Avenue, Pittsburgh, PA 15219, USA
| |
Collapse
|
10
|
Wu Z, Zhang T, Ma X, Guo S, Zhou Q, Zahoor A, Deng G. Recent advances in anti-inflammatory active components and action mechanisms of natural medicines. Inflammopharmacology 2023; 31:2901-2937. [PMID: 37947913 DOI: 10.1007/s10787-023-01369-9] [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: 04/12/2023] [Accepted: 09/16/2023] [Indexed: 11/12/2023]
Abstract
Inflammation is a series of reactions caused by the body's resistance to external biological stimuli. Inflammation affects the occurrence and development of many diseases. Anti-inflammatory drugs have been used widely to treat inflammatory diseases, but long-term use can cause toxic side-effects and affect human functions. As immunomodulators with long-term conditioning effects and no drug residues, natural products are being investigated increasingly for the treatment of inflammatory diseases. In this review, we focus on the inflammatory process and cellular mechanisms in the development of diseases such as inflammatory bowel disease, atherosclerosis, and coronavirus disease-2019. Also, we focus on three signaling pathways (Nuclear factor-kappa B, p38 mitogen-activated protein kinase, Janus kinase/signal transducer and activator of transcription-3) to explain the anti-inflammatory effect of natural products. In addition, we also classified common natural products based on secondary metabolites and explained the association between current bidirectional prediction progress of natural product targets and inflammatory diseases.
Collapse
Affiliation(s)
- Zhimin Wu
- Department of Clinical Veterinary Medicine, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Tao Zhang
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, China
| | - Xiaofei Ma
- College of Veterinary Medicine, Gansu Agriculture University, Lanzhou, China
| | - Shuai Guo
- Department of Clinical Veterinary Medicine, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Qingqing Zhou
- Department of Clinical Veterinary Medicine, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China
| | - Arshad Zahoor
- College of Veterinary Sciences, The University of Agriculture Peshawar, Peshawar, Pakistan
| | - Ganzhen Deng
- Department of Clinical Veterinary Medicine, College of Veterinary Medicine, Huazhong Agricultural University, Wuhan, China.
| |
Collapse
|
11
|
Bauer J, Rajagopal N, Gupta P, Gupta P, Nixon AE, Kumar S. How can we discover developable antibody-based biotherapeutics? Front Mol Biosci 2023; 10:1221626. [PMID: 37609373 PMCID: PMC10441133 DOI: 10.3389/fmolb.2023.1221626] [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: 05/12/2023] [Accepted: 07/10/2023] [Indexed: 08/24/2023] Open
Abstract
Antibody-based biotherapeutics have emerged as a successful class of pharmaceuticals despite significant challenges and risks to their discovery and development. This review discusses the most frequently encountered hurdles in the research and development (R&D) of antibody-based biotherapeutics and proposes a conceptual framework called biopharmaceutical informatics. Our vision advocates for the syncretic use of computation and experimentation at every stage of biologic drug discovery, considering developability (manufacturability, safety, efficacy, and pharmacology) of potential drug candidates from the earliest stages of the drug discovery phase. The computational advances in recent years allow for more precise formulation of disease concepts, rapid identification, and validation of targets suitable for therapeutic intervention and discovery of potential biotherapeutics that can agonize or antagonize them. Furthermore, computational methods for de novo and epitope-specific antibody design are increasingly being developed, opening novel computationally driven opportunities for biologic drug discovery. Here, we review the opportunities and limitations of emerging computational approaches for optimizing antigens to generate robust immune responses, in silico generation of antibody sequences, discovery of potential antibody binders through virtual screening, assessment of hits, identification of lead drug candidates and their affinity maturation, and optimization for developability. The adoption of biopharmaceutical informatics across all aspects of drug discovery and development cycles should help bring affordable and effective biotherapeutics to patients more quickly.
Collapse
Affiliation(s)
- Joschka Bauer
- Early Stage Pharmaceutical Development Biologicals, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach/Riss, Germany
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
| | - Nandhini Rajagopal
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Priyanka Gupta
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Pankaj Gupta
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Andrew E. Nixon
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| | - Sandeep Kumar
- In Silico Team, Boehringer Ingelheim, Hannover, Germany
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc., Ridgefield, CT, United States
| |
Collapse
|
12
|
Han X, Lin H, Chen X, Wang L, Zhang Z, Wei X, Sun X, Xie H, Pavase TR, Cao L, Sui J. Amide-containing neoepitopes: the key factor in the preparation of hapten-specific antibodies and a strategy to overcome. Front Immunol 2023; 14:1144020. [PMID: 37342337 PMCID: PMC10277511 DOI: 10.3389/fimmu.2023.1144020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 05/15/2023] [Indexed: 06/22/2023] Open
Abstract
For a long time, people have suffered from uncertainty, complexity, and a low success rate in generating and screening antibodies against small molecules, which have become the core bottlenecks of immunochemistry. Here, the influence of antigen preparation on antibody generation was investigated at both molecular and submolecular levels. Neoepitopes (amide-containing neoepitopes) formed in the preparation of complete antigens are one of the most important factors limiting the efficiency of generating hapten-specific antibodies, which was verified by different haptens, carrier proteins, and conjugation conditions. Amide-containing neoepitopes present electron-dense structural components on the surface of prepared complete antigens and, therefore, induce the generation of the corresponding antibody with much higher efficiency than target hapten. Crosslinkers should be carefully selected and not overdosed. According to these results, some misconceptions in the conventional anti-hapten antibody production were clarified and corrected. By controlling the content of 1-(3-dimethylaminopropyl)-3-ethylcarbodiimide hydrochloride (EDC) during the synthesis of immunogen to limit the formation of amide-containing neoepitopes, the efficiency of hapten-specific antibody generation could be significantly improved, which verified the correctness of the conclusion and provided an efficient strategy for antibody preparation. The result of the work is of scientific significance in the preparation of high-quality antibodies against small molecules.
Collapse
Affiliation(s)
- Xiangning Han
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Hong Lin
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Xiangfeng Chen
- Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Luefeng Wang
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Ziang Zhang
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Xiaojing Wei
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Xun Sun
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Hanyi Xie
- Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Tushar Ramesh Pavase
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Limin Cao
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| | - Jianxin Sui
- College of Food Science and Engineering, Ocean University of China, Qingdao, China
| |
Collapse
|
13
|
Chen Z, Wang X, Chen X, Huang J, Wang C, Wang J, Wang Z. Accelerating therapeutic protein design with computational approaches toward the clinical stage. Comput Struct Biotechnol J 2023; 21:2909-2926. [PMID: 38213894 PMCID: PMC10781723 DOI: 10.1016/j.csbj.2023.04.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/11/2023] [Accepted: 04/27/2023] [Indexed: 01/13/2024] Open
Abstract
Therapeutic protein, represented by antibodies, is of increasing interest in human medicine. However, clinical translation of therapeutic protein is still largely hindered by different aspects of developability, including affinity and selectivity, stability and aggregation prevention, solubility and viscosity reduction, and deimmunization. Conventional optimization of the developability with widely used methods, like display technologies and library screening approaches, is a time and cost-intensive endeavor, and the efficiency in finding suitable solutions is still not enough to meet clinical needs. In recent years, the accelerated advancement of computational methodologies has ushered in a transformative era in the field of therapeutic protein design. Owing to their remarkable capabilities in feature extraction and modeling, the integration of cutting-edge computational strategies with conventional techniques presents a promising avenue to accelerate the progression of therapeutic protein design and optimization toward clinical implementation. Here, we compared the differences between therapeutic protein and small molecules in developability and provided an overview of the computational approaches applicable to the design or optimization of therapeutic protein in several developability issues.
Collapse
Affiliation(s)
- Zhidong Chen
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Xinpei Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Xu Chen
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Juyang Huang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Chenglin Wang
- Shenzhen Qiyu Biotechnology Co., Ltd, Shenzhen 518107, China
| | - Junqing Wang
- School of Pharmaceutical Sciences, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China
| | - Zhe Wang
- Department of Pathology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen 518033, China
| |
Collapse
|
14
|
Liu S, Shah DK. Physiologically Based Pharmacokinetic Modeling to Characterize the Effect of Molecular Charge on Whole-Body Disposition of Monoclonal Antibodies. AAPS J 2023; 25:48. [PMID: 37118220 DOI: 10.1208/s12248-023-00812-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 04/11/2023] [Indexed: 04/30/2023] Open
Abstract
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.
Collapse
Affiliation(s)
- Shufang Liu
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, 455 Pharmacy Building, Buffalo, Ney York, 14214-8033, USA
| | - Dhaval K Shah
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, The State University of New York at Buffalo, 455 Pharmacy Building, Buffalo, Ney York, 14214-8033, USA.
| |
Collapse
|
15
|
Ausserwöger H, Krainer G, Welsh TJ, Thorsteinson N, de Csilléry E, Sneideris T, Schneider MM, Egebjerg T, Invernizzi G, Herling TW, Lorenzen N, Knowles TPJ. Surface patches induce nonspecific binding and phase separation of antibodies. Proc Natl Acad Sci U S A 2023; 120:e2210332120. [PMID: 37011217 PMCID: PMC10104583 DOI: 10.1073/pnas.2210332120] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 02/06/2023] [Indexed: 04/05/2023] Open
Abstract
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.
Collapse
Affiliation(s)
- Hannes Ausserwöger
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Georg Krainer
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Timothy J. Welsh
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Nels Thorsteinson
- Research and Development, Chemical Computing Group, Montreal, QuebecH3A 2R7, Canada
| | - Ella de Csilléry
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Tomas Sneideris
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Matthias M. Schneider
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Thomas Egebjerg
- Global Research Technologies, Novo Nordisk A/S2760Måløv, Denmark
| | | | - Therese W. Herling
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Nikolai Lorenzen
- Global Research Technologies, Novo Nordisk A/S2760Måløv, Denmark
| | - Tuomas P. J. Knowles
- Yusuf Hamied Department of Chemistry, Centre for Misfolding Diseases, University of Cambridge, CambridgeCB2 1EW, United Kingdom
- Department of Physics, Cavendish Laboratory, University of Cambridge, CambridgeCB3 0HE, United Kingdom
| |
Collapse
|
16
|
Rosace A, Bennett A, Oeller M, Mortensen MM, Sakhnini L, Lorenzen N, Poulsen C, Sormanni P. Automated optimisation of solubility and conformational stability of antibodies and proteins. Nat Commun 2023; 14:1937. [PMID: 37024501 PMCID: PMC10079162 DOI: 10.1038/s41467-023-37668-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 03/24/2023] [Indexed: 04/08/2023] Open
Abstract
Biologics, such as antibodies and enzymes, are crucial in research, biotechnology, diagnostics, and therapeutics. Often, biologics with suitable functionality are discovered, but their development is impeded by developability issues. Stability and solubility are key biophysical traits underpinning developability potential, as they determine aggregation, correlate with production yield and poly-specificity, and are essential to access parenteral and oral delivery. While advances for the optimisation of individual traits have been made, the co-optimization of multiple traits remains highly problematic and time-consuming, as mutations that improve one property often negatively impact others. In this work, we introduce a fully automated computational strategy for the simultaneous optimisation of conformational stability and solubility, which we experimentally validate on six antibodies, including two approved therapeutics. Our results on 42 designs demonstrate that the computational procedure is highly effective at improving developability potential, while not affecting antigen-binding. We make the method available as a webserver at www-cohsoftware.ch.cam.ac.uk.
Collapse
Affiliation(s)
- Angelo Rosace
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Master in Bioinformatics for Health Sciences, Universitat Pompeu Fabra, Barcelona, Catalonia, Spain
- Institute for Research in Biomedicine (IRB), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Anja Bennett
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Department of Mammalian Expression, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
- BRIC, Faculty of Health and Medical Sciences, University of Copenhagen, Ole Maaløes Vej 5, 2200, Copenhagen, Denmark
| | - Marc Oeller
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
| | - Mie M Mortensen
- Department of Purification Technologies, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
- Faculty of Engineering and Science, Department of Biotechnology, Chemistry and Environmental Engineering, University of Aalborg, Fredrik Bajers Vej 7H, 9220, Aalborg, Denmark
| | - Laila Sakhnini
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK
- Department of Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, Måløv, 2760, Denmark
| | - Nikolai Lorenzen
- Department of Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, Måløv, 2760, Denmark
| | - Christian Poulsen
- Department of Mammalian Expression, Global Research Technologies, Novo Nordisk A/S, Novo Nordisk Park 1, 2760, Måløv, Denmark
| | - Pietro Sormanni
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield road, CB2 1EW, Cambridge, UK.
| |
Collapse
|
17
|
Levitt DG, Levitt MD. Development and application of a simple pharmacokinetic model that quantitatively describes the distribution and elimination of the commonly measured proteins. ADMET & DMPK 2023; 11:57-80. [PMID: 36778906 PMCID: PMC9909726 DOI: 10.5599/admet.1570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 01/22/2023] [Indexed: 01/27/2023]
Abstract
Increased plasma concentrations of a variety of cellular enzymes (alanine transaminase, aspartate aminotransferase, alkaline phosphatase, amylase, etc.) are commonly used as routine screening tests for a range of conditions. An increased concentration usually is assumed to result from an increased rate of delivery to the plasma. Factors such as decreased metabolism or excretion or altered extravascular distribution usually are ignored. As a prelude to a detailed analysis of all the factors producing altered plasma enzyme levels, we have reviewed the relevant literature describing the pharmacokinetics (PK) of 13 of the commonly measured plasma proteins and developed a PK model that provides a simple physiological description of all the data. Our model starts with the general 3-compartment, 6-parameter system previously developed for albumin and interprets the fluxes in terms of unidirectional sieved protein convectional volume flows from the plasma to the two tissue compartments and equal lymph flows returning to the plasma. This greatly constrains the model such that each protein is characterized by only two adjustable parameters (plasma clearance and sieving factor). In addition to accurately fitting the plasma kinetics, the model can accurately describe the tissue and lymph protein PK. For example, it can describe the thoracic duct lymph protein concentration following an intravenous infusion or the plasma concentration following a subcutaneous tissue injection. This simple model provides a satisfactory framework for the PK of 12 of the 13 proteins investigated. The glycoprotein intestinal alkaline phosphatase is the exception, requiring the addition of a liver recycling compartment involving the asialoglycoprotein receptor.
Collapse
Affiliation(s)
- David G. Levitt
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, MN 55455, USA; ,*Corresponding Author: E-mail:
| | - Michael D. Levitt
- Medicine Service, Veterans Affairs Medical Center, Minneapolis, MN. 55417, USA;
| |
Collapse
|
18
|
Svilenov HL, Arosio P, Menzen T, Tessier P, Sormanni P. Approaches to expand the conventional toolbox for discovery and selection of antibodies with drug-like physicochemical properties. MAbs 2023; 15:2164459. [PMID: 36629855 PMCID: PMC9839375 DOI: 10.1080/19420862.2022.2164459] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 12/22/2022] [Accepted: 12/29/2022] [Indexed: 01/12/2023] Open
Abstract
Antibody drugs should exhibit not only high-binding affinity for their target antigens but also favorable physicochemical drug-like properties. Such drug-like biophysical properties are essential for the successful development of antibody drug products. The traditional approaches used in antibody drug development require significant experimentation to produce, optimize, and characterize many candidates. Therefore, it is attractive to integrate new methods that can optimize the process of selecting antibodies with both desired target-binding and drug-like biophysical properties. Here, we summarize a selection of techniques that can complement the conventional toolbox used to de-risk antibody drug development. These techniques can be integrated at different stages of the antibody development process to reduce the frequency of physicochemical liabilities in antibody libraries during initial discovery and to co-optimize multiple antibody features during early-stage antibody engineering and affinity maturation. Moreover, we highlight biophysical and computational approaches that can be used to predict physical degradation pathways relevant for long-term storage and in-use stability to reduce the need for extensive experimentation.
Collapse
Affiliation(s)
- Hristo L. Svilenov
- Laboratory of General Biochemistry and Physical Pharmacy, Faculty of Pharmaceutical Sciences, Ghent University, Gent, Belgium
| | - Paolo Arosio
- Department of Chemistry and Applied Biosciences, ETH Zürich, Zürich, Switzerland
| | - Tim Menzen
- Coriolis Pharma Research GmbH, Martinsried, 82152, Germany
| | - Peter 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
| | - Pietro Sormanni
- Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
| |
Collapse
|
19
|
Fernández-Quintero ML, Ljungars A, Waibl F, Greiff V, Andersen JT, Gjølberg TT, Jenkins TP, Voldborg BG, Grav LM, Kumar S, Georges G, Kettenberger H, Liedl KR, Tessier PM, McCafferty J, Laustsen AH. Assessing developability early in the discovery process for novel biologics. MAbs 2023; 15:2171248. [PMID: 36823021 PMCID: PMC9980699 DOI: 10.1080/19420862.2023.2171248] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Accepted: 01/18/2023] [Indexed: 02/25/2023] Open
Abstract
Beyond potency, a good developability profile is a key attribute of a biological drug. Selecting and screening for such attributes early in the drug development process can save resources and avoid costly late-stage failures. Here, we review some of the most important developability properties that can be assessed early on for biologics. These include the influence of the source of the biologic, its biophysical and pharmacokinetic properties, and how well it can be expressed recombinantly. We furthermore present in silico, in vitro, and in vivo methods and techniques that can be exploited at different stages of the discovery process to identify molecules with liabilities and thereby facilitate the selection of the most optimal drug leads. Finally, we reflect on the most relevant developability parameters for injectable versus orally delivered biologics and provide an outlook toward what general trends are expected to rise in the development of biologics.
Collapse
Affiliation(s)
- Monica L. Fernández-Quintero
- Center for Molecular Biosciences Innsbruck (CMBI), Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innsbruck, Austria
| | - Anne Ljungars
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Franz Waibl
- Center for Molecular Biosciences Innsbruck (CMBI), Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innsbruck, Austria
| | - Victor Greiff
- Department of Immunology, University of Oslo, Oslo, Norway
| | - Jan Terje Andersen
- Department of Immunology, University of Oslo, Oslo University Hospital Rikshospitalet, Oslo, Norway
- Institute of Clinical Medicine and Department of Pharmacology, University of Oslo, Oslo, Norway
| | | | - Timothy P. Jenkins
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Bjørn Gunnar Voldborg
- National Biologics Facility, Department of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Lise Marie Grav
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Sandeep Kumar
- Biotherapeutics Discovery, Boehringer Ingelheim Pharmaceuticals Inc, Ridgefield, CT, USA
| | - Guy Georges
- Roche Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich, Penzberg, Germany
| | - Hubert Kettenberger
- Roche Pharma Research and Early Development, Large Molecule Research, Roche Innovation Center Munich, Penzberg, Germany
| | - Klaus R. Liedl
- Center for Molecular Biosciences Innsbruck (CMBI), Department of General, Inorganic and Theoretical Chemistry, University of Innsbruck, Innsbruck, Austria
| | - Peter M. Tessier
- Department of Chemical Engineering, Pharmaceutical Sciences and Biomedical Engineering, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - John McCafferty
- Department of Medicine, Cambridge Institute of Therapeutic Immunology and Infectious Disease, University of Cambridge, Cambridge, UK
- Maxion Therapeutics, Babraham Research Campus, Cambridge, UK
| | - Andreas H. Laustsen
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Kongens Lyngby, Denmark
| |
Collapse
|
20
|
Liu S, Humphreys SC, Cook KD, Conner KP, Correia AR, Jacobitz AW, Yang M, Primack R, Soto M, Padaki R, Lubomirski M, Smith R, Mock M, Thomas VA. Utility of physiologically based pharmacokinetic modeling to predict inter-antibody variability in monoclonal antibody pharmacokinetics in mice. MAbs 2023; 15:2263926. [PMID: 37824334 PMCID: PMC10572049 DOI: 10.1080/19420862.2023.2263926] [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: 05/31/2023] [Accepted: 09/24/2023] [Indexed: 10/14/2023] Open
Abstract
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.
Collapse
Affiliation(s)
- Shufang Liu
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc, South San Francisco, CA, USA
| | - Sara C. Humphreys
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc, South San Francisco, CA, USA
| | - Kevin D. Cook
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc, South San Francisco, CA, USA
| | - Kip P. Conner
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc, South San Francisco, CA, USA
| | | | | | - Melissa Yang
- Therapeutic Discovery, Amgen, Thousand Oaks, CA, USA
| | - Ronya Primack
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc, Thousand Oaks, CA, USA
| | - Marcus Soto
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc, Thousand Oaks, CA, USA
| | - Rupa Padaki
- Process Development, Amgen Inc, Thousand Oaks, CA, USA
| | | | - Richard Smith
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc, South San Francisco, CA, USA
| | - Marissa Mock
- Therapeutic Discovery, Amgen, Thousand Oaks, CA, USA
| | - Veena A. Thomas
- Department of Pharmacokinetics and Drug Metabolism, Amgen Inc, South San Francisco, CA, USA
| |
Collapse
|
21
|
Dippel A, Gallegos A, Aleti V, Barnes A, Chen X, Christian E, Delmar J, Du Q, Esfandiary R, Farmer E, Garcia A, Li Q, Lin J, Liu W, Machiesky L, Mody N, Parupudi A, Prophet M, Rickert K, Rosenthal K, Ren S, Shandilya H, Varkey R, Wons K, Wu Y, Loo YM, Esser MT, Kallewaard NL, Rajan S, Damschroder M, Xu W, Kaplan G. Developability profiling of a panel of Fc engineered SARS-CoV-2 neutralizing antibodies. MAbs 2023; 15:2152526. [PMID: 36476037 PMCID: PMC9733695 DOI: 10.1080/19420862.2022.2152526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
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.
Collapse
Affiliation(s)
- Andrew Dippel
- Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Austin Gallegos
- Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Vineela Aleti
- Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Arnita Barnes
- Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Xiaoru Chen
- Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Gaithersburg, MD, USA
| | | | - Jared Delmar
- Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Qun Du
- Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Reza Esfandiary
- Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Erika Farmer
- Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Andrew Garcia
- Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Qing Li
- Hansoh Bio, Rockville, MD, USA,Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Jia Lin
- Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Weiyi Liu
- Pfizer, La Jolla, CA, USA,Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - LeeAnn Machiesky
- Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Neil Mody
- Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Arun Parupudi
- Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Meagan Prophet
- Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Keith Rickert
- Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Kim Rosenthal
- Vaccines and Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Song Ren
- Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Gaithersburg, MD, USA
| | | | - Reena Varkey
- Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Kevin Wons
- Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Yuling Wu
- Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Yueh-Ming Loo
- Vaccines and Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Mark T. Esser
- Vaccines and Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Nicole L. Kallewaard
- Eli Lilly, Indianapolis, IN, USA,Vaccines and Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Sarav Rajan
- Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA
| | | | - Weichen Xu
- Biopharmaceutical Development, MacroGenics, Rockville, MD, USA,Biopharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA
| | - Gilad Kaplan
- Biologics Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA,CONTACT Gilad Kaplan AstraZeneca, Gaithersburg, MD20878
| |
Collapse
|
22
|
Ausserwöger H, Schneider MM, Herling TW, Arosio P, Invernizzi G, Knowles TPJ, Lorenzen N. Non-specificity as the sticky problem in therapeutic antibody development. Nat Rev Chem 2022; 6:844-861. [PMID: 37117703 DOI: 10.1038/s41570-022-00438-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/07/2022] [Indexed: 11/16/2022]
Abstract
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.
Collapse
|
23
|
Zhang W, Wang H, Feng N, Li Y, Gu J, Wang Z. Developability assessment at early-stage discovery to enable development of antibody-derived therapeutics. Antib Ther 2022; 6:13-29. [PMID: 36683767 PMCID: PMC9847343 DOI: 10.1093/abt/tbac029] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 11/01/2022] [Accepted: 11/02/2022] [Indexed: 11/13/2022] Open
Abstract
Developability refers to the likelihood that an antibody candidate will become a manufacturable, safe and efficacious drug. Although the safety and efficacy of a drug candidate will be well considered by sponsors and regulatory agencies, developability in the narrow sense can be defined as the likelihood that an antibody candidate will go smoothly through the chemistry, manufacturing and control (CMC) process at a reasonable cost and within a reasonable timeline. Developability in this sense is the focus of this review. To lower the risk that an antibody candidate with poor developability will move to the CMC stage, the candidate's developability-related properties should be screened, assessed and optimized as early as possible. Assessment of developability at the early discovery stage should be performed in a rapid and high-throughput manner while consuming small amounts of testing materials. In addition to monoclonal antibodies, bispecific antibodies, multispecific antibodies and antibody-drug conjugates, as the derivatives of monoclonal antibodies, should also be assessed for developability. Moreover, we propose that the criterion of developability is relative: expected clinical indication, and the dosage and administration route of the antibody could affect this criterion. We also recommend a general screening process during the early discovery stage of antibody-derived therapeutics. With the advance of artificial intelligence-aided prediction of protein structures and features, computational tools can be used to predict, screen and optimize the developability of antibody candidates and greatly reduce the risk of moving a suboptimal candidate to the development stage.
Collapse
Affiliation(s)
- Weijie Zhang
- Biologicals Innovation and Discovery, WuXi Biologicals, 1951 Huifeng West Road, Fengxian District, Shanghai 201400, China
| | - Hao Wang
- Biologicals Innovation and Discovery, WuXi Biologicals, 1951 Huifeng West Road, Fengxian District, Shanghai 201400, China
| | - Nan Feng
- Biologicals Innovation and Discovery, WuXi Biologicals, 1951 Huifeng West Road, Fengxian District, Shanghai 201400, China
| | - Yifeng Li
- Technology and Process Development, WuXi Biologicals, 288 Fute Zhong Road, Waigaoqiao Free Trade Zone, Shanghai 200131, China
| | - Jijie Gu
- Biologicals Innovation and Discovery, WuXi Biologicals, 1951 Huifeng West Road, Fengxian District, Shanghai 201400, China
| | - Zhuozhi Wang
- To whom correspondence should be addressed. Biologics Innovation and Discovery, WuXi Biologicals, 1951 Huifeng West Road, Fengxian District, Shanghai 201400, China, Phone number: +86-21-50518899
| |
Collapse
|
24
|
Makowski EK, Kinnunen PC, Huang J, Wu L, Smith MD, Wang T, Desai AA, Streu CN, Zhang Y, Zupancic JM, Schardt JS, Linderman JJ, Tessier PM. Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space. Nat Commun 2022; 13:3788. [PMID: 35778381 PMCID: PMC9249733 DOI: 10.1038/s41467-022-31457-3] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 06/20/2022] [Indexed: 11/08/2022] Open
Abstract
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.
Collapse
Affiliation(s)
- Emily K Makowski
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, 48109, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Patrick C Kinnunen
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jie Huang
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, 48109, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Lina Wu
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Matthew D Smith
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Tiexin Wang
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Alec A Desai
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Craig N Streu
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, 48109, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Chemistry, Albion College, Albion, MI, 49224, USA
| | - Yulei Zhang
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jennifer M Zupancic
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - John S Schardt
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, 48109, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Jennifer J Linderman
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Peter M Tessier
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, 48109, USA.
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, 48109, USA.
| |
Collapse
|
25
|
Underwood DJ, Bettencourt J, Jawad Z. The manufacturing considerations of bispecific antibodies. Expert Opin Biol Ther 2022; 22:1043-1065. [PMID: 35771976 DOI: 10.1080/14712598.2022.2095900] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Antibody therapies have made huge strides in providing safe and efficacious drugs for autoimmune, cancer and infectious disease. These bispecific antibodies can be assembled from the basic building blocks of IgGs, resulting in dozens of formats. AREAS COVERED It is important to consider the manufacturability of these formats early in the antibody discovery phases. Broadly categorizing bispecific antibodies into IgG-like, fragment-based, appended and hybrid formats can help in looking at early manufacturability considerations. EXPERT OPINION Ideally, bispecific antibody manufacturing should contain a minimal number of steps, with processes that give high yields of protein with no contaminants. Many of these have been determined for the fragment-based bispecific blinatumomab and the IgG-like bispecifics from hybridomas. However, for new formats, these need to be considered early in the research and development pipeline. The hybrid formats offer an unusual alternative in generating high pure yields of bispecific molecules if the engineering challenges can be deciphered.
Collapse
Affiliation(s)
| | | | - Zahra Jawad
- Agenus inc., 3 Forbes Road, Lexington, MA, 02421-7305, United States.,Creasallis ltd, Babraham Research Campus, Babraham, Cambridgeshire, CB22 3AT, United Kingdom
| |
Collapse
|
26
|
Suh K, Kyei I, Hage DS. Approaches for the detection and analysis of anti-drug antibodies to biopharmaceuticals: A review. J Sep Sci 2022; 45:2077-2092. [PMID: 35230731 DOI: 10.1002/jssc.202200112] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 02/10/2022] [Accepted: 02/26/2022] [Indexed: 11/10/2022]
Abstract
Antibody-based therapeutic agents and other biopharmaceuticals are now used in the treatment of many diseases. However, when these biopharmaceuticals are administrated to patients, an immune reaction may occur that can reduce the drug's efficacy and lead to adverse side effects. The immunogenicity of biopharmaceuticals can be evaluated by detecting and measuring antibodies that have been produced against these drugs, or anti-drug antibodies (ADAs). Methods for ADA detection and analysis can be important during the selection of a therapeutic approach based on such drugs and is crucial when developing and testing new biopharmaceuticals. This review examines approaches that have been used for ADA detection, measurement, and characterization. Many of these approaches are based on immunoassays and antigen binding tests, including homogeneous mobility shift assays. Other techniques that have been used for the analysis of ADAs are capillary electrophoresis, reporter gene assays, surface plasmon resonance spectroscopy, and liquid chromatography-mass spectrometry. The general principles of each approach will be discussed, along with their recent applications with regards to ADA analysis. This article is protected by copyright. All rights reserved.
Collapse
Affiliation(s)
- Kyungah Suh
- Department of Chemistry, University of Nebraska-Lincoln
| | - Isaac Kyei
- Department of Chemistry, University of Nebraska-Lincoln
| | - David S Hage
- Department of Chemistry, University of Nebraska-Lincoln
| |
Collapse
|
27
|
Khetan R, Curtis R, Deane CM, Hadsund JT, Kar U, Krawczyk K, Kuroda D, Robinson SA, Sormanni P, Tsumoto K, Warwicker J, Martin ACR. Current advances in biopharmaceutical informatics: guidelines, impact and challenges in the computational developability assessment of antibody therapeutics. MAbs 2022; 14:2020082. [PMID: 35104168 PMCID: PMC8812776 DOI: 10.1080/19420862.2021.2020082] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly enabling the development of predictive models and computational tools for the "developability assessment" of antibody drug candidates. Here, we provide an overview of the antibody informatics tools applicable to the prediction of developability issues such as stability, aggregation, immunogenicity, and chemical degradation. We further evaluate the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Finally, we discuss the potential of developability guidelines based on in silico metrics that can be used for the assessment of antibody stability and manufacturability.
Collapse
Affiliation(s)
- Rahul Khetan
- Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
| | - Robin Curtis
- Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
| | | | | | - Uddipan Kar
- Department of Biological Engineering, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA
| | | | - Daisuke Kuroda
- Department of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.,Medical Device Development and Regulation Research Center, School of Engineering, The University of Tokyo, Tokyo, Japan.,Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo, Tokyo, Japan
| | | | - Pietro Sormanni
- Chemistry of Health, Yusuf Hamied Department of Chemistry, University of Cambridge
| | - Kouhei Tsumoto
- Department of Bioengineering, School of Engineering, The University of Tokyo, Tokyo, Japan.,Medical Device Development and Regulation Research Center, School of Engineering, The University of Tokyo, Tokyo, Japan.,Department of Chemistry and Biotechnology, School of Engineering, The University of Tokyo, Tokyo, Japan.,The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Jim Warwicker
- Manchester Institute of Biotechnology, University of Manchester, Manchester, UK
| | - Andrew C R Martin
- Institute of Structural and Molecular Biology, Division of Biosciences, University College London, London, UK
| |
Collapse
|
28
|
Lu J, Ding J, Liu Z, Chen T. Retrospective analysis of the preparation and application of immunotherapy in cancer treatment (Review). Int J Oncol 2022; 60:12. [PMID: 34981814 PMCID: PMC8759346 DOI: 10.3892/ijo.2022.5302] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 12/20/2021] [Indexed: 12/11/2022] Open
Abstract
Monoclonal antibody technology plays a vital role in biomedical and immunotherapy, which greatly promotes the study of the structure and function of genes and proteins. To date, monoclonal antibodies have gone through four stages: murine monoclonal antibody, chimeric monoclonal antibody, humanised monoclonal antibody and fully human monoclonal antibody; thousands of monoclonal antibodies have been used in the fields of biology and medicine, playing a special role in the pathogenesis, diagnosis and treatment of disease. In this review, we compare the advantages and disadvantages of hybridoma technology, phage display technology, ribosome display technology, transgenic mouse technology, single B cell monoclonal antibody generation technologies, and forecast the promising applications of these technologies in clinical medicine, disease diagnosis and tumour treatment.
Collapse
Affiliation(s)
- Jiachen Lu
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| | - Jianing Ding
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| | - Zhaoxia Liu
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| | - Tingtao Chen
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| |
Collapse
|
29
|
Hu S, Datta-Mannan A, D’Argenio DZ. Physiologically Based Modeling to Predict Monoclonal Antibody Pharmacokinetics in Humans from in vitro Physiochemical Properties. MAbs 2022; 14:2056944. [PMID: 35491902 PMCID: PMC9067474 DOI: 10.1080/19420862.2022.2056944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 02/28/2022] [Accepted: 03/20/2022] [Indexed: 11/01/2022] Open
Abstract
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.
Collapse
Affiliation(s)
- Shihao Hu
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Amita Datta-Mannan
- Department of Exploratory Medicine and Pharmacology, Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN, USA
| | - David Z. D’Argenio
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| |
Collapse
|
30
|
Makowski EK, Chen H, Lambert M, Bennett EM, Eschmann NS, Zhang Y, Zupancic JM, Desai AA, Smith MD, Lou W, Fernando A, Tully T, Gallo CJ, Lin L, Tessier PM. Reduction of therapeutic antibody self-association using yeast-display selections and machine learning. MAbs 2022; 14:2146629. [PMID: 36433737 PMCID: PMC9704398 DOI: 10.1080/19420862.2022.2146629] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Self-association governs the viscosity and solubility of therapeutic antibodies in high-concentration formulations used for subcutaneous delivery, yet it is difficult to reliably identify candidates with low self-association during antibody discovery and early-stage optimization. Here, we report a high-throughput protein engineering method for rapidly identifying antibody candidates with both low self-association and high affinity. We find that conjugating quantum dots to IgGs that strongly self-associate (pH 7.4, PBS), such as lenzilumab and bococizumab, results in immunoconjugates that are highly sensitive for detecting other high self-association antibodies. Moreover, these conjugates can be used to rapidly enrich yeast-displayed bococizumab sub-libraries for variants with low levels of immunoconjugate binding. Deep sequencing and machine learning analysis of the enriched bococizumab libraries, along with similar library analysis for antibody affinity, enabled identification of extremely rare variants with co-optimized levels of low self-association and high affinity. This analysis revealed that co-optimizing bococizumab is difficult because most high-affinity variants possess positively charged variable domains and most low self-association variants possess negatively charged variable domains. Moreover, negatively charged mutations in the heavy chain CDR2 of bococizumab, adjacent to its paratope, were effective at reducing self-association without reducing affinity. Interestingly, most of the bococizumab variants with reduced self-association also displayed improved folding stability and reduced nonspecific binding, revealing that this approach may be particularly useful for identifying antibody candidates with attractive combinations of drug-like properties.Abbreviations: AC-SINS: affinity-capture self-interaction nanoparticle spectroscopy; CDR: complementarity-determining region; CS-SINS: charge-stabilized self-interaction nanoparticle spectroscopy; FACS: fluorescence-activated cell sorting; Fab: fragment antigen binding; Fv: fragment variable; IgG: immunoglobulin; QD: quantum dot; PBS: phosphate-buffered saline; VH: variable heavy; VL: variable light.
Collapse
Affiliation(s)
- Emily K. Makowski
- Departments of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA,Biointerfaces Institute, University of Michigan, Ann Arbor, MI48109, USA
| | - Hongwei Chen
- Departments of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA,Biointerfaces Institute, University of Michigan, Ann Arbor, MI48109, USA,Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | | | | | | | - Yulei Zhang
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI48109, USA,Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer M. Zupancic
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI48109, USA,Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Alec A. Desai
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI48109, USA,Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Matthew D. Smith
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI48109, USA,Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Wenjia Lou
- Departments of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA,Biointerfaces Institute, University of Michigan, Ann Arbor, MI48109, USA,Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Timothy Tully
- Bioprocess Research & Development, Pfizer Inc., St. Louis, MO, USA
| | | | - Laura Lin
- BioMedicine Design, Pfizer Inc, Cambridge, MA, USA
| | - Peter M. Tessier
- Departments of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA,Biointerfaces Institute, University of Michigan, Ann Arbor, MI48109, USA,Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA,Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA,CONTACT Peter M. Tessier Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA
| |
Collapse
|
31
|
Makowski EK, Schardt JS, Tessier PM. Improving antibody drug development using bionanotechnology. Curr Opin Biotechnol 2021; 74:137-145. [PMID: 34890875 DOI: 10.1016/j.copbio.2021.10.027] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 10/25/2021] [Accepted: 10/31/2021] [Indexed: 12/20/2022]
Abstract
Monoclonal antibodies are being used to treat a remarkable breadth of human disorders. Nevertheless, there are several key challenges at the earliest stages of antibody drug development that need to be addressed using simple and widely accessible methods, especially related to generating antibodies against membrane proteins and identifying antibody candidates with drug-like biophysical properties (high solubility and low viscosity). Here we highlight key bionanotechnologies for preparing functional and stable membrane proteins in diverse types of lipoparticles that are being used to improve antibody discovery and engineering efforts. We also highlight key bionanotechnologies for high-throughput and ultra-dilute screening of antibody biophysical properties during antibody discovery and optimization that are being used for identifying antibodies with superior combinations of in vitro (formulation) and in vivo (half-life) properties.
Collapse
Affiliation(s)
- Emily K Makowski
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - John S Schardt
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Peter M Tessier
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA; Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; Departmant of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA.
| |
Collapse
|
32
|
Jiskoot W, Hawe A, Menzen T, Volkin DB, Crommelin DJA. Ongoing Challenges to Develop High Concentration Monoclonal Antibody-based Formulations for Subcutaneous Administration: Quo Vadis? J Pharm Sci 2021; 111:861-867. [PMID: 34813800 DOI: 10.1016/j.xphs.2021.11.008] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 11/12/2021] [Accepted: 11/12/2021] [Indexed: 11/26/2022]
Abstract
Although many subcutaneously (s.c.) delivered, high-concentration antibody formulations (HCAF) have received regulatory approval and are widely used commercially, formulation scientists are still presented with many ongoing challenges during HCAF development with new mAb and mAb-based candidates. Depending on the specific physicochemical and biological properties of a particular mAb-based molecule, such challenges vary from pharmaceutical attributes e.g., stability, viscosity, manufacturability, to clinical performance e.g., bioavailability, immunogenicity, and finally to patient experience e.g., preference for s.c. vs. intravenous delivery and/or preferred interactions with health-care professionals. This commentary focuses on one key formulation obstacle encountered during HCAF development: how to maximize the dose of the drug? We examine methodologies for increasing the protein concentration, increasing the volume delivered, or combining both approaches together. We discuss commonly encountered hurdles, i.e., physical protein instability and solution volume limitations, and we provide recommendations to formulation scientists to facilitate their development of s.c. administered HCAF with new mAb-based product candidates.
Collapse
Affiliation(s)
- W Jiskoot
- Coriolis Pharma Research GmbH, Fraunhoferstr. 18 b, 82152 Martinsried, Germany; Leiden Academic Center for Drug Research (LACDR), Leiden University, 2300 RA Leiden, the Netherlands
| | - Andrea Hawe
- Coriolis Pharma Research GmbH, Fraunhoferstr. 18 b, 82152 Martinsried, Germany
| | - Tim Menzen
- Coriolis Pharma Research GmbH, Fraunhoferstr. 18 b, 82152 Martinsried, Germany
| | - David B Volkin
- Department of Pharmaceutical Chemistry, Vaccine Analytics and Formulation Center, University of Kansas, Lawrence, KS 66047, USA
| | - Daan J A Crommelin
- Department of Pharmaceutics, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, 3584 CG Utrecht, the Netherlands.
| |
Collapse
|
33
|
Nilvebrant J, Ereño-Orbea J, Gorelik M, Julian MC, Tessier PM, Julien JP, Sidhu SS. Systematic Engineering of Optimized Autonomous Heavy-Chain Variable Domains. J Mol Biol 2021; 433:167241. [PMID: 34508727 DOI: 10.1016/j.jmb.2021.167241] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/16/2021] [Accepted: 09/03/2021] [Indexed: 01/06/2023]
Abstract
Autonomous heavy-chain variable (VH) domains are the smallest functional antibody fragments, and they possess unique features, including small size and convex paratopes, which provide enhanced targeting of concave epitopes that are difficult to access with larger conventional antibodies. However, human VH domains have evolved to fold and function with a light chain partner, and alone, they typically suffer from low stability and high aggregation propensity. Development of autonomous human VH domains, in which aggregation propensity is reduced without compromising antigen recognition, has proven challenging. Here, we used an autonomous human VH domain as a scaffold to construct phage-displayed synthetic libraries in which aspartate was systematically incorporated at different paratope positions. In selections, the library yielded many anti-EphA1 receptor VH domains, which were characterized in detail. Structural analyses of a parental anti-EphA1 VH domain and an improved variant provided insights into the effects of aspartate and other substitutions on preventing aggregation while retaining function. Our naïve libraries and in vitro selection procedures offer a systematic approach to generating highly functional autonomous human VH domains that resist aggregation and could be used for basic research and biomedical applications.
Collapse
Affiliation(s)
- Johan Nilvebrant
- Banting and Best Department of Medical Research and Department of Molecular Genetics, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada
| | - June Ereño-Orbea
- Program in Molecular Medicine, The Hospital for Sick Children Research Institute and Departments of Biochemistry and Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Maryna Gorelik
- Banting and Best Department of Medical Research and Department of Molecular Genetics, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada
| | - Mark C Julian
- Isermann Department of Chemical & Biological Engineering, Center for Biotechnology & Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| | - Peter M Tessier
- Isermann Department of Chemical & Biological Engineering, Center for Biotechnology & Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, NY 12180, USA; Departments of Chemical Engineering, Pharmaceutical Sciences, and Biomedical Engineering, Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jean-Philippe Julien
- Program in Molecular Medicine, The Hospital for Sick Children Research Institute and Departments of Biochemistry and Immunology, University of Toronto, Toronto, Ontario, Canada
| | - Sachdev S Sidhu
- Banting and Best Department of Medical Research and Department of Molecular Genetics, The Donnelly Centre, University of Toronto, Toronto, Ontario M5S 3E1, Canada.
| |
Collapse
|
34
|
Intrinsic physicochemical profile of marketed antibody-based biotherapeutics. Proc Natl Acad Sci U S A 2021; 118:2020577118. [PMID: 34504010 PMCID: PMC8449350 DOI: 10.1073/pnas.2020577118] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/03/2021] [Indexed: 01/28/2023] Open
Abstract
Successful biologic drug discovery and development involves finding functional as well as developable candidates. Once a candidate has been demonstrated to be functional, the next step is to determine whether it can be translated into a drug product. This requires that the candidate can withstand stresses encountered during manufacturing, shipping, and storage. Additionally, it must be safe, efficacious, and possess good pharmacology. In silico analyses of the variable regions of 77 marketed antibody-based biotherapeutics have revealed five nonredundant physicochemical descriptors. Distributions of these descriptors, observed for marketed biotherapeutics, can help prioritize a drug candidate for experimental testing at early discovery stages, guide engineering efforts to further optimize it, and help increase the productivity of biologic drug discovery and development. Feeding biopharma pipelines with biotherapeutic candidates that possess desirable developability profiles can help improve the productivity of biologic drug discovery and development. Here, we have derived an in silico profile by analyzing computed physicochemical descriptors for the variable regions (Fv) found in 77 marketed antibody-based biotherapeutics. Fv regions of these biotherapeutics demonstrate significant diversities in their germlines, complementarity determining region loop lengths, hydrophobicity, and charge distributions. Furthermore, an analysis of 24 physicochemical descriptors, calculated using homology-based molecular models, has yielded five nonredundant descriptors whose distributions represent stability, isoelectric point, and molecular surface characteristics of their Fv regions. Fv regions of candidates from our internal discovery campaigns, human next-generation sequencing repertoires, and those in clinical-stages (CST) were assessed for similarity with the physicochemical profile derived here. The Fv regions in 33% of CST antibodies show physicochemical properties that are dissimilar to currently marketed biotherapeutics. In comparison, physicochemical characteristics of ∼29% of the Fv regions in human antibodies and ∼27% of our internal hits deviated significantly from those of marketed biotherapeutics. The early availability of this information can help guide hit selection, lead identification, and optimization of biotherapeutic candidates. Insights from this work can also help support portfolio risk assessment, in-licensing, and biopharma collaborations.
Collapse
|
35
|
Dyson MR, Masters E, Pazeraitis D, Perera RL, Syrjanen JL, Surade S, Thorsteinson N, Parthiban K, Jones PC, Sattar M, Wozniak-Knopp G, Rueker F, Leah R, McCafferty J. Beyond affinity: selection of antibody variants with optimal biophysical properties and reduced immunogenicity from mammalian display libraries. MAbs 2021; 12:1829335. [PMID: 33103593 PMCID: PMC7592150 DOI: 10.1080/19420862.2020.1829335] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
The early phase of protein drug development has traditionally focused on target binding properties leading to a desired mode of therapeutic action. As more protein therapeutics pass through the development pipeline; however, it is clear that non-optimal biophysical properties can emerge, particularly as proteins are formulated at high concentrations, causing aggregation or polyreactivity. Such late-stage "developability" problems can lead to delay or failure in traversing the development process. Aggregation propensity is also correlated with increased immunogenicity, resulting in expensive, late-stage clinical failures. Using nucleases-directed integration, we have constructed large mammalian display libraries where each cell contains a single antibody gene/cell inserted at a single locus, thereby achieving transcriptional normalization. We show a strong correlation between poor biophysical properties and display level achieved in mammalian cells, which is not replicated by yeast display. Using two well-documented examples of antibodies with poor biophysical characteristics (MEDI-1912 and bococizumab), a library of variants was created based on surface hydrophobic and positive charge patches. Mammalian display was used to select for antibodies that retained target binding and permitted increased display level. The resultant variants exhibited reduced polyreactivity and reduced aggregation propensity. Furthermore, we show in the case of bococizumab that biophysically improved variants are less immunogenic than the parental molecule. Thus, mammalian display helps to address multiple developability issues during the earliest stages of lead discovery, thereby significantly de-risking the future development of protein drugs.
Collapse
Affiliation(s)
| | | | | | | | - Johanna L Syrjanen
- WM Keck Structural Biology Laboratory, Cold Spring Harbor Laboratory , NY, USA
| | | | | | | | | | | | - Gordana Wozniak-Knopp
- Department of Biotechnology, BOKU-University of Natural Resources and Life Sciences , Vienna, Austria
| | - Florian Rueker
- Department of Biotechnology, BOKU-University of Natural Resources and Life Sciences , Vienna, Austria
| | | | | |
Collapse
|
36
|
Bullen G, Galson JD, Hall G, Villar P, Moreels L, Ledsgaard L, Mattiuzzo G, Bentley EM, Masters EW, Tang D, Millett S, Tongue D, Brown R, Diamantopoulos I, Parthiban K, Tebbutt C, Leah R, Chaitanya K, Ergueta-Carballo S, Pazeraitis D, Surade SB, Ashiru O, Crippa L, Cowan R, Bowler MW, Campbell JI, Lee WYJ, Carr MD, Matthews D, Pfeffer P, Hufton SE, Sawmynaden K, Osbourn J, McCafferty J, Karatt-Vellatt A. Cross-Reactive SARS-CoV-2 Neutralizing Antibodies From Deep Mining of Early Patient Responses. Front Immunol 2021; 12:678570. [PMID: 34211469 PMCID: PMC8239432 DOI: 10.3389/fimmu.2021.678570] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 05/13/2021] [Indexed: 12/22/2022] Open
Abstract
Passive immunization using monoclonal antibodies will play a vital role in the fight against COVID-19. The recent emergence of viral variants with reduced sensitivity to some current antibodies and vaccines highlights the importance of broad cross-reactivity. This study describes deep-mining of the antibody repertoires of hospitalized COVID-19 patients using phage display technology and B cell receptor (BCR) repertoire sequencing to isolate neutralizing antibodies and gain insights into the early antibody response. This comprehensive discovery approach has yielded a panel of potent neutralizing antibodies which bind distinct viral epitopes including epitopes conserved in SARS-CoV-1. Structural determination of a non-ACE2 receptor blocking antibody reveals a previously undescribed binding epitope, which is unlikely to be affected by the mutations in any of the recently reported major viral variants including B.1.1.7 (from the UK), B.1.351 (from South Africa) and B.1.1.28 (from Brazil). Finally, by combining sequences of the RBD binding and neutralizing antibodies with the B cell receptor repertoire sequencing, we also describe a highly convergent early antibody response. Similar IgM-derived sequences occur within this study group and also within patient responses described by multiple independent studies published previously.
Collapse
Affiliation(s)
| | | | - Gareth Hall
- Leicester Institute of Structural and Chemical Biology and Department of Molecular and Cell Biology, University of Leicester, Leicester, United Kingdom
| | | | | | | | - Giada Mattiuzzo
- National Institute for Biological Standards and Control, Potters Bar, United Kingdom
| | - Emma M Bentley
- National Institute for Biological Standards and Control, Potters Bar, United Kingdom
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Richard Cowan
- Leicester Institute of Structural and Chemical Biology and Department of Molecular and Cell Biology, University of Leicester, Leicester, United Kingdom
| | | | | | - Wing-Yiu Jason Lee
- Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Mark D Carr
- Leicester Institute of Structural and Chemical Biology and Department of Molecular and Cell Biology, University of Leicester, Leicester, United Kingdom
| | | | - Paul Pfeffer
- Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Simon E Hufton
- National Institute for Biological Standards and Control, Potters Bar, United Kingdom
| | | | - Jane Osbourn
- Alchemab Therapeutics Ltd., London, United Kingdom
| | | | | |
Collapse
|
37
|
Starr CG, Makowski EK, Wu L, Berg B, Kingsbury JS, Gokarn YR, Tessier PM. Ultradilute Measurements of Self-Association for the Identification of Antibodies with Favorable High-Concentration Solution Properties. Mol Pharm 2021; 18:2744-2753. [PMID: 34105965 DOI: 10.1021/acs.molpharmaceut.1c00280] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
There is significant interest in formulating antibody therapeutics as concentrated liquid solutions, but early identification of developable antibodies with optimal manufacturability, stability, and delivery attributes remains challenging. Traditional methods of identifying developable mAbs with low self-association in common antibody formulations require relatively concentrated protein solutions (>1 mg/mL), and this single challenge has frustrated early-stage and large-scale identification of antibody candidates with drug-like colloidal properties. Here, we describe charge-stabilized self-interaction nanoparticle spectroscopy (CS-SINS), an affinity-capture nanoparticle assay that measures colloidal self-interactions at ultradilute antibody concentrations (0.01 mg/mL), and is predictive of antibody developability issues of high viscosity and opalescence that manifest at four orders of magnitude higher concentrations (>100 mg/mL). CS-SINS enables large-scale, high-throughput selection of developable antibodies during early discovery.
Collapse
Affiliation(s)
- Charles G Starr
- Biologics Development, Sanofi, Framingham, Massachusetts 01701, United States
| | | | | | | | | | - Yatin R Gokarn
- Biologics Development, Sanofi, Framingham, Massachusetts 01701, United States
| | | |
Collapse
|
38
|
Berner C, Menzen T, Winter G, Svilenov HL. Combining Unfolding Reversibility Studies and Molecular Dynamics Simulations to Select Aggregation-Resistant Antibodies. Mol Pharm 2021; 18:2242-2253. [PMID: 33928776 DOI: 10.1021/acs.molpharmaceut.1c00017] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
The efficient development of new therapeutic antibodies relies on developability assessment with biophysical and computational methods to find molecules with drug-like properties such as resistance to aggregation. Despite the many novel approaches to select well-behaved proteins, antibody aggregation during storage is still challenging to predict. For this reason, there is a high demand for methods that can identify aggregation-resistant antibodies. Here, we show that three straightforward techniques can select the aggregation-resistant antibodies from a dataset with 13 molecules. The ReFOLD assay provided information about the ability of the antibodies to refold to monomers after unfolding with chemical denaturants. Modulated scanning fluorimetry (MSF) yielded the temperatures that start causing irreversible unfolding of the proteins. Aggregation was the main reason for poor unfolding reversibility in both ReFOLD and MSF experiments. We therefore performed temperature ramps in molecular dynamics (MD) simulations to obtain partially unfolded antibody domains in silico and used CamSol to assess their aggregation potential. We compared the information from ReFOLD, MSF, and MD to size-exclusion chromatography (SEC) data that shows whether the antibodies aggregated during storage at 4, 25, and 40 °C. Contrary to the aggregation-prone molecules, the antibodies that were resistant to aggregation during storage at 40 °C shared three common features: (i) higher tendency to refold to monomers after unfolding with chemical denaturants, (ii) higher onset temperature of nonreversible unfolding, and (iii) unfolding of regions containing aggregation-prone sequences at higher temperatures in MD simulations.
Collapse
Affiliation(s)
- Carolin Berner
- Department of Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstr. 5, 81377 Munich, Germany
| | - Tim Menzen
- Coriolis Pharma Research GmbH, Fraunhoferstr. 18 b, 82152 Martinsried, Germany
| | - Gerhard Winter
- Department of Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstr. 5, 81377 Munich, Germany
| | - Hristo L Svilenov
- Department of Pharmacy, Ludwig-Maximilians-Universität München, Butenandtstr. 5, 81377 Munich, Germany
| |
Collapse
|
39
|
Villacrés C, Tayi VS, Butler M. Strategic feeding of NS0 and CHO cell cultures to control glycan profiles and immunogenic epitopes of monoclonal antibodies. J Biotechnol 2021; 333:49-62. [PMID: 33901620 DOI: 10.1016/j.jbiotec.2021.04.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 04/03/2021] [Accepted: 04/18/2021] [Indexed: 01/12/2023]
Abstract
The control of glycosylation profiles is essential to the consistent manufacture of therapeutic monoclonal antibodies that may be produced from a variety of cell lines including CHO and NS0. Of particular concern is the potential for generating non-human epitopes such as N-glycolylneuraminic acid (Neu5Gc) and Galα1-3 Gal that may be immunogenic. We have looked at the effects of a commonly used media supplements of manganese, galactose and uridine (MGU) on Mab production from CHO and NS0 cells in enhancing galactosylation and sialylation as well as the generation of these non-human glycan epitopes. In the absence of the MGU supplement, the humanized IgG1 antibody (Hu1D10) produced from NS0 cells showed a low level of mono- and di-sialylated structures (SI:0.09) of which 75 % of sialic acid was Neu5Gc. The chimeric human-llama Mab (EG2-hFc) produced from CHO cells showed an equally low level of sialylation (SI: 0.12) but the Neu5Gc content of sialic acid was negligible (<3%). Combinations of the MGU supplements added to the production cultures resulted in a substantial increase in the galactosylation of both Mabs (up to GI:0.78 in Hu1D10 and 0.81 in EG2-hFc). However, the effects on sialylation differed between the two Mabs. We observed a slight increase in sialylation of the EG2-hFc Mab by a combination of MG but it appeared that one of the components (uridine) was inhibitory to sialylation. On the other hand, MG or MGU increased sialylation of Hu1D10 substantially (SI:0.72) with an increase that could be attributed predominantly to the formation of Neu5Ac rather than Neu5Gc. The increased level of galactosylation observed with MG or MGU was attributed to an activation of the galactosyl transferase enzymes through enhanced intracellular levels of UDP-Gal and the availability of Mn2+ as an enzymic co-factor. However, this effect not only increased the desirable beta 1-4 Gal linkage to GlcNAc but unfortunately in NS0 cells increased the formation of Galα1-3 Gal which was shown to increase x3 in the presence of combinations of the MGU supplements. Supplementation of media with fetal bovine serum (FBS) increased the availability of free Neu5Ac which resulted in a significant increase in the sialylation of Hu1D10 from NS0 cells. This also resulted in a significant decrease in the proportion of Neu5Gc in the measured sialic acid from the Mab.
Collapse
Affiliation(s)
- Carina Villacrés
- Department of Microbiology, University of Manitoba, Winnipeg, MB, R3T2N2, Canada
| | - Venkata S Tayi
- Department of Microbiology, University of Manitoba, Winnipeg, MB, R3T2N2, Canada
| | - Michael Butler
- Department of Microbiology, University of Manitoba, Winnipeg, MB, R3T2N2, Canada; National Institute for Bioprocessing Research & Training (NIBRT), Fosters Avenue, Dublin, A94 X099, Ireland.
| |
Collapse
|
40
|
Shahfar H, Forder JK, Roberts CJ. Toward a Suite of Coarse-Grained Models for Molecular Simulation of Monoclonal Antibodies and Therapeutic Proteins. J Phys Chem B 2021; 125:3574-3588. [PMID: 33821645 DOI: 10.1021/acs.jpcb.1c01903] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A series of coarse-grained models for molecular simulation of proteins are considered, with emphasis on the application of predicting protein-protein self-interactions for monoclonal antibodies (MAbs). As an illustrative example and for quantitative comparison, the models are used to predict osmotic virial coefficients over a broad range of attractive and repulsive self-interactions and solution conditions for a series of MAbs where the second osmotic virial coefficient has been experimentally determined in prior work. The models are compared based on how well they can predict experimental behavior, their computational burdens, and scalability. An intermediate-resolution model is also introduced that can capture specific electrostatic interactions with improved efficiency and similar or improved accuracy when compared to the previously published models. Guidance is included for the selection of coarse-grained models more generally for capturing a balance of electrostatic, steric, and short-ranged nonelectrostatic interactions for proteins from low to high concentrations.
Collapse
Affiliation(s)
- Hassan Shahfar
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States.,Department of Physics and Astronomy, University of Delaware, Newark, Delaware 19716, United States
| | - James K Forder
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States
| | - Christopher J Roberts
- Department of Chemical and Biomolecular Engineering, University of Delaware, Newark, Delaware 19716, United States
| |
Collapse
|
41
|
Desai AA, Smith MD, Zhang Y, Makowski EK, Gerson JE, Ionescu E, Starr CG, Zupancic JM, Moore SJ, Sutter AB, Ivanova MI, Murphy GG, Paulson HL, Tessier PM. Rational affinity maturation of anti-amyloid antibodies with high conformational and sequence specificity. J Biol Chem 2021; 296:100508. [PMID: 33675750 PMCID: PMC8081927 DOI: 10.1016/j.jbc.2021.100508] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 02/05/2021] [Accepted: 03/02/2021] [Indexed: 01/01/2023] Open
Abstract
The aggregation of amyloidogenic polypeptides is strongly linked to several neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. Conformational antibodies that selectively recognize protein aggregates are leading therapeutic agents for selectively neutralizing toxic aggregates, diagnostic and imaging agents for detecting disease, and biomedical reagents for elucidating disease mechanisms. Despite their importance, it is challenging to generate high-quality conformational antibodies in a systematic and site-specific manner due to the properties of protein aggregates (hydrophobic, multivalent, and heterogeneous) and limitations of immunization (uncontrolled antigen presentation and immunodominant epitopes). Toward addressing these challenges, we have developed a systematic directed evolution procedure for affinity maturing antibodies against Alzheimer's Aβ fibrils and selecting variants with strict conformational and sequence specificity. We first designed a library based on a lead conformational antibody by sampling combinations of amino acids in the antigen-binding site predicted to mediate high antibody specificity. Next, we displayed this library on the surface of yeast, sorted it against Aβ42 aggregates, and identified promising clones using deep sequencing. The resulting antibodies displayed similar or higher affinities than clinical-stage Aβ antibodies (aducanumab and crenezumab). Moreover, the affinity-matured antibodies retained high conformational specificity for Aβ aggregates, as observed for aducanumab and unlike crenezumab. Notably, the affinity-maturated antibodies displayed extremely low levels of nonspecific interactions, as observed for crenezumab and unlike aducanumab. We expect that our systematic methods for generating antibodies with unique combinations of desirable properties will improve the generation of high-quality conformational antibodies specific for diverse types of aggregated conformers.
Collapse
Affiliation(s)
- Alec A Desai
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew D Smith
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Yulei Zhang
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Emily K Makowski
- Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA; Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, Michigan, USA
| | - Julia E Gerson
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA
| | - Edward Ionescu
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Charles G Starr
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA; Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, Michigan, USA
| | - Jennifer M Zupancic
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Shannon J Moore
- Protein Folding Disease Initiative, University of Michigan, Ann Arbor, Michigan, USA; Department of Molecular & Integrative Physiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Alexandra B Sutter
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA; Biophysics Program, University of Michigan, Ann Arbor, Michigan, USA
| | - Magdalena I Ivanova
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA; Biophysics Program, University of Michigan, Ann Arbor, Michigan, USA
| | - Geoffrey G Murphy
- Protein Folding Disease Initiative, University of Michigan, Ann Arbor, Michigan, USA; Department of Molecular & Integrative Physiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Henry L Paulson
- Department of Neurology, University of Michigan, Ann Arbor, Michigan, USA; Protein Folding Disease Initiative, University of Michigan, Ann Arbor, Michigan, USA; Michigan Alzheimer's Disease Center, University of Michigan, Ann Arbor, Michigan, USA
| | - Peter M Tessier
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA; Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, Michigan, USA; Protein Folding Disease Initiative, University of Michigan, Ann Arbor, Michigan, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
| |
Collapse
|
42
|
Wahlund PO, Lorenzen N, Rischel C. Screening for protein-protein interactions with asymmetrical flow field-flow fractionation. J Pharm Sci 2021; 110:2336-2339. [PMID: 33640337 DOI: 10.1016/j.xphs.2021.02.026] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 01/27/2021] [Accepted: 02/19/2021] [Indexed: 11/30/2022]
Abstract
We describe a new method for screening protein-protein interaction of biopharmaceutical molecules at dilute concentrations to predict development issues at high concentration. The method is based on Asymmetrical Flow Field-Flow Fractionation (AF4) measurements using well known effects of protein-protein attraction on the fractionation profile due to elevated protein concentrations occurring close to the membrane. We explore the effect for 4 different monoclonal antibodies and show that the profiles obtained are quite different. Interestingly, we find that the recovery in AF4 correlates with the diffusion interaction parameter, which is a standard method for the analysis of protein-protein attraction. The results are insensitive to the protein concentration and buffer composition of the sample solution and only depend on the absolute amount of protein loaded and on the running buffer. This makes the method highly suitable for developability assessment in a compound discovery workflow.
Collapse
Affiliation(s)
- Per-Olof Wahlund
- Department Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, 2760 Måløv, Denmark.
| | - Nikolai Lorenzen
- Department Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, 2760 Måløv, Denmark
| | - Christian Rischel
- Department Biophysics and Injectable Formulation 2, Global Research Technologies, Novo Nordisk A/S, 2760 Måløv, Denmark
| |
Collapse
|
43
|
Kang SH, Lee CH. Development of Therapeutic Antibodies and Modulating the Characteristics of Therapeutic Antibodies to Maximize the Therapeutic Efficacy. BIOTECHNOL BIOPROC E 2021; 26:295-311. [PMID: 34220207 PMCID: PMC8236339 DOI: 10.1007/s12257-020-0181-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 08/13/2020] [Accepted: 08/17/2020] [Indexed: 02/06/2023]
Abstract
Monoclonal antibodies (mAb) have been used as therapeutic agents for various diseases, and immunoglobulin G (IgG) is mainly used among antibody isotypes due to its structural and functional properties. So far, regardless of the purpose of the therapeutic antibody, wildtype IgG has been mainly used, but recently, the engineered antibodies with various strategies according to the role of the therapeutic antibody have been used to maximize the therapeutic efficacy. In this review paper, first, the overall structural features and functional characteristics of antibody IgG, second, the old and new techniques for antibody discovery, and finally, several antibody engineering strategies for maximizing therapeutic efficacy according to the role of a therapeutic antibody will be introduced.
Collapse
Affiliation(s)
- Seung Hyun Kang
- grid.31501.360000 0004 0470 5905Department of Pharmacology, Seoul National University College of Medicine, Seoul, 03080 Korea
| | - Chang-Han Lee
- grid.31501.360000 0004 0470 5905Department of Pharmacology, Seoul National University College of Medicine, Seoul, 03080 Korea ,grid.31501.360000 0004 0470 5905Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, 03080 Korea ,Hongcheon, 25159 Korea ,grid.31501.360000 0004 0470 5905SNU Dementia Research Center, Seoul National University College of Medicine, Seoul, 03080 Korea
| |
Collapse
|
44
|
Lai PK, Fernando A, Cloutier TK, Kingsbury JS, Gokarn Y, Halloran KT, Calero-Rubio C, Trout BL. Machine Learning Feature Selection for Predicting High Concentration Therapeutic Antibody Aggregation. J Pharm Sci 2020; 110:1583-1591. [PMID: 33346034 DOI: 10.1016/j.xphs.2020.12.014] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/25/2020] [Accepted: 12/11/2020] [Indexed: 02/03/2023]
Abstract
Protein aggregation can hinder the development, safety and efficacy of therapeutic antibody-based drugs. Developing a predictive model that evaluates aggregation behaviors during early stage development is therefore desirable. Machine learning is a widely used tool to train models that predict data with different attributes. However, most machine learning techniques require more data than is typically available in antibody development. In this work, we describe a rational feature selection framework to develop accurate models with a small number of features. We applied this framework to predict aggregation behaviors of 21 approved monospecific monoclonal antibodies at high concentration (150 mg/mL), yielding a correlation coefficient of 0.71 on validation tests with only two features using a linear model. The nearest neighbors and support vector regression models further improved the performance, which have correlation coefficients of 0.86 and 0.80, respectively. This framework can be extended to train other models that predict different physical properties.
Collapse
Affiliation(s)
- Pin-Kuang Lai
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Amendra Fernando
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Theresa K Cloutier
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | - Yatin Gokarn
- Biologics Development, Sanofi, Framingham, MA, USA
| | | | | | - Bernhardt L Trout
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| |
Collapse
|
45
|
Domnowski M, Lo Presti K, Binder J, Reindl J, Lehmann L, Kummer F, Wolber M, Satzger M, Dehling M, Jaehrling J, Frieß W. Generation of mAb Variants with Less Attractive Self-Interaction but Preserved Target Binding by Well-Directed Mutation. Mol Pharm 2020; 18:236-245. [PMID: 33331157 DOI: 10.1021/acs.molpharmaceut.0c00848] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Strongly attractive self-interaction of therapeutic protein candidates can impose challenges for manufacturing, filling, stability, and administration due to elevated viscosity or aggregation propensity. Suitable formulations can mitigate these issues to a certain extent. Understanding the self-interaction mechanism on a molecular basis and rational protein engineering provides a more fundamental approach, and it can save costs and efforts as well as alleviate risks at later stages of development. In this study, we used computational methods for the identification of aggregation-prone regions in a mAb and generated mutants based on these findings. We applied hydrogen-deuterium exchange mass spectrometry to identify distinct self-interaction hot spots. Ultimately, we generated mAb variants based on a combination of both approaches and identified mutants with low attractive self-interaction propensity, minimal off-target binding, and even improved target binding. Our data show that the introduction of arginine in spatial proximity to hydrophobic patches is highly beneficial on all these levels. For our mAb, variants that contain more than one aspartate residue flanking to the hydrophobic HCDR3 show decreased attractive self-interaction at unaffected off-target and target binding. The combined engineering strategy described here underlines the high potential of understanding self-interaction in the early stages of development to predict and reduce the risk of failure in subsequent development.
Collapse
Affiliation(s)
- Martin Domnowski
- Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig Maximilians-Universitaet, Munich 81377, Germany.,MorphoSys AG, Department of Protein Sciences (Research), Planegg 82152, Germany
| | - Ken Lo Presti
- Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig Maximilians-Universitaet, Munich 81377, Germany
| | - Jonas Binder
- Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig Maximilians-Universitaet, Munich 81377, Germany
| | - Josef Reindl
- MorphoSys AG, Department of Protein Sciences (Research), Planegg 82152, Germany
| | - Lucille Lehmann
- MorphoSys AG, Department of Protein Sciences (Research), Planegg 82152, Germany
| | - Felix Kummer
- MorphoSys AG, Department of Protein Sciences (Research), Planegg 82152, Germany
| | - Meike Wolber
- MorphoSys AG, Department of Protein Sciences (Research), Planegg 82152, Germany
| | - Marion Satzger
- MorphoSys AG, Department of Protein Sciences (Research), Planegg 82152, Germany
| | - Marco Dehling
- MorphoSys AG, Department of Protein Sciences (Research), Planegg 82152, Germany
| | - Jan Jaehrling
- MorphoSys AG, Department of Protein Sciences (Research), Planegg 82152, Germany
| | - Wolfgang Frieß
- Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig Maximilians-Universitaet, Munich 81377, Germany
| |
Collapse
|
46
|
Lou W, Stimple SD, Desai AA, Makowski EK, Kalyoncu S, Mogensen JE, Spang LT, Asgreen DJ, Staby A, Duus K, Amstrup J, Zhang Y, Tessier PM. Directed evolution of conformation-specific antibodies for sensitive detection of polypeptide aggregates in therapeutic drug formulations. Biotechnol Bioeng 2020; 118:797-808. [PMID: 33095442 DOI: 10.1002/bit.27610] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 10/15/2020] [Accepted: 10/19/2020] [Indexed: 12/22/2022]
Abstract
Biologics such as peptides and proteins possess a number of attractive attributes that make them particularly valuable as therapeutics, including their high activity, high specificity, and low toxicity. However, one of the key challenges associated with this class of drugs is their propensity to aggregate. Given the safety and immunogenicity concerns related to polypeptide aggregates, it is particularly important to sensitively detect aggregates in therapeutic drug formulations as part of the quality control process. Here, we report the development of conformation-specific antibodies that recognize polypeptide aggregates composed of a GLP-1 receptor agonist (liraglutide) and their integration into a sensitive immunoassay for detecting liraglutide amyloid fibrils. We sorted single-chain antibody libraries against liraglutide fibrils using yeast surface display and magnetic-activated cell sorting, and identified several antibodies with high conformational specificity. Interestingly, these antibodies cross-react with amyloid fibrils formed by several other polypeptides, revealing that they recognize molecular features common to different types of fibrils. Moreover, we find that our immunoassay using these antibodies is >50-fold more sensitive than the conventional method for detecting liraglutide aggregation (Thioflavin T fluorescence). We expect that our systematic approach for generating a sensitive, aggregate-specific immunoassay can be readily extended to other biologics to improve the quality and safety of formulated drug products.
Collapse
Affiliation(s)
- Wenjia Lou
- Department of Pharmaceutical Sciences, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA.,Department of Chemical Engineering, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Samuel D Stimple
- Department of Pharmaceutical Sciences, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA.,Department of Chemical Engineering, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Alec A Desai
- Department of Chemical Engineering, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Emily K Makowski
- Department of Pharmaceutical Sciences, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Sibel Kalyoncu
- Isermann Department of Chemical and Biological Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, New York, USA
| | | | | | | | | | | | | | - Yulei Zhang
- Department of Chemical Engineering, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| | - Peter M Tessier
- Department of Pharmaceutical Sciences, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA.,Department of Chemical Engineering, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA.,Isermann Department of Chemical and Biological Engineering, Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute, Troy, New York, USA.,Department of Biomedical Engineering, Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA
| |
Collapse
|
47
|
Boughter CT, Borowska MT, Guthmiller JJ, Bendelac A, Wilson PC, Roux B, Adams EJ. Biochemical patterns of antibody polyreactivity revealed through a bioinformatics-based analysis of CDR loops. eLife 2020; 9:61393. [PMID: 33169668 PMCID: PMC7755423 DOI: 10.7554/elife.61393] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 11/09/2020] [Indexed: 12/20/2022] Open
Abstract
Antibodies are critical components of adaptive immunity, binding with high affinity to pathogenic epitopes. Antibodies undergo rigorous selection to achieve this high affinity, yet some maintain an additional basal level of low affinity, broad reactivity to diverse epitopes, a phenomenon termed ‘polyreactivity’. While polyreactivity has been observed in antibodies isolated from various immunological niches, the biophysical properties that allow for promiscuity in a protein selected for high-affinity binding to a single target remain unclear. Using a database of over 1000 polyreactive and non-polyreactive antibody sequences, we created a bioinformatic pipeline to isolate key determinants of polyreactivity. These determinants, which include an increase in inter-loop crosstalk and a propensity for a neutral binding surface, are sufficient to generate a classifier able to identify polyreactive antibodies with over 75% accuracy. The framework from which this classifier was built is generalizable, and represents a powerful, automated pipeline for future immune repertoire analysis. To defend itself against bacteria and viruses, the body depends on a group of proteins known as antibodies. Each subset of antibodies undergoes a rigorous training regimen to ensure it recognizes a single epitope well – that is, one specific region on the surface of foreign, harmful organisms. Most antibodies stick extremely tightly to their one unique epitope, but some can also weakly bind to molecules that are vastly different from their main trained targets. This feature – known as polyreactivity – can in some cases help the immune system fight against multiple strains of viruses. On the other hand, when antibodies are designed in the laboratory to treat diseases, this characteristic can sometimes lead to the failure of pre-clinical trials. Yet it is currently unclear why some antibodies are polyreactive when others are not. To investigate this question, Boughter et al. compared over 1,000 polyreactive and non-polyreactive antibody sequences from a large database, revealing differences in the physical properties of the region of the antibodies that attaches to epitopes. Using these defining features, Boughter et al. went on to design a new piece of freely available, automated software that could predict which antibodies would be polyreactive more than 75% of the time. Such software could ultimately help to guide the design of antibody-based treatments, while bypassing the need for costly laboratory tests.
Collapse
Affiliation(s)
| | - Marta T Borowska
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, United States
| | - Jenna J Guthmiller
- Department of Medicine, Section of Rheumatology, University of Chicago, Chicago, United States
| | - Albert Bendelac
- Committee on Immunology, University of Chicago, Chicago, United States.,Department of Pathology, University of Chicago, Chicago, United States
| | - Patrick C Wilson
- Department of Medicine, Section of Rheumatology, University of Chicago, Chicago, United States.,Committee on Immunology, University of Chicago, Chicago, United States
| | - Benoit Roux
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, United States
| | - Erin J Adams
- Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, United States.,Committee on Immunology, University of Chicago, Chicago, United States
| |
Collapse
|
48
|
Sawant MS, Streu CN, Wu L, Tessier PM. Toward Drug-Like Multispecific Antibodies by Design. Int J Mol Sci 2020; 21:E7496. [PMID: 33053650 PMCID: PMC7589779 DOI: 10.3390/ijms21207496] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 10/02/2020] [Accepted: 10/02/2020] [Indexed: 12/18/2022] Open
Abstract
The success of antibody therapeutics is strongly influenced by their multifunctional nature that couples antigen recognition mediated by their variable regions with effector functions and half-life extension mediated by a subset of their constant regions. Nevertheless, the monospecific IgG format is not optimal for many therapeutic applications, and this has led to the design of a vast number of unique multispecific antibody formats that enable targeting of multiple antigens or multiple epitopes on the same antigen. Despite the diversity of these formats, a common challenge in generating multispecific antibodies is that they display suboptimal physical and chemical properties relative to conventional IgGs and are more difficult to develop into therapeutics. Here we review advances in the design and engineering of multispecific antibodies with drug-like properties, including favorable stability, solubility, viscosity, specificity and pharmacokinetic properties. We also highlight emerging experimental and computational methods for improving the next generation of multispecific antibodies, as well as their constituent antibody fragments, with natural IgG-like properties. Finally, we identify several outstanding challenges that need to be addressed to increase the success of multispecific antibodies in the clinic.
Collapse
Affiliation(s)
- Manali S. Sawant
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA; (M.S.S.); (C.N.S.)
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA;
| | - Craig N. Streu
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA; (M.S.S.); (C.N.S.)
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA;
- Department of Chemistry, Albion College, Albion, MI 49224, USA
| | - Lina Wu
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA;
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| | - Peter M. Tessier
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA; (M.S.S.); (C.N.S.)
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA;
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
| |
Collapse
|
49
|
Krieg D, Berner C, Winter G, Svilenov HL. Biophysical Characterization of Binary Therapeutic Monoclonal Antibody Mixtures. Mol Pharm 2020; 17:2971-2986. [PMID: 32687367 DOI: 10.1021/acs.molpharmaceut.0c00370] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Coformulations containing two therapeutic monoclonal antibodies (mAbs) could offer various benefits like enhanced therapeutic efficacy and better patient compliance. However, there are very few published studies on coformulations and binary mixtures of mAbs. It remains unclear to what extent mAbs with different physicochemical properties can be combined in solution without detrimental effects on protein stability. Here, we present a study including six model mAbs of the IgG1 subclass that are commercially available. In silico and biophysical characterization shows that the proteins have different physicochemical properties. Thus, their combinations represent various scenarios for coformulation development. We prepared all possible binary mixtures of the six mAbs and determined several biophysical parameters that are assessed during early-stage protein drug product development. The measured biophysical parameters are indicative of the conformational protein stability (inflection points of the thermal protein unfolding transitions) and the colloidal protein stability (aggregation onset temperatures and interaction parameter kD from dynamic light scattering). Remarkably, all 15 binary mAb mixtures do not exhibit biophysical parameters that indicate inferior conformational or colloidal stability compared to the least stable mAb in the mixture. Our findings suggest that the coformulation of some therapeutic monoclonal antibodies of the IgG1 subclass could be possible in a straightforward way as severe detrimental effects on the stability of these proteins in binary mixtures were not observed.
Collapse
Affiliation(s)
- Dennis Krieg
- Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig-Maximilians-Universitaet Muenchen, Butenandtstrasse 5-13, Munich D-81377, Germany
| | - Carolin Berner
- Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig-Maximilians-Universitaet Muenchen, Butenandtstrasse 5-13, Munich D-81377, Germany
| | - Gerhard Winter
- Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig-Maximilians-Universitaet Muenchen, Butenandtstrasse 5-13, Munich D-81377, Germany
| | - Hristo L Svilenov
- Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, Ludwig-Maximilians-Universitaet Muenchen, Butenandtstrasse 5-13, Munich D-81377, Germany.,Department of Chemistry, Technische Universitaet Muenchen, Garching 85747, Germany
| |
Collapse
|
50
|
Zhang Y, Wu L, Gupta P, Desai AA, Smith MD, Rabia LA, Ludwig SD, Tessier PM. Physicochemical Rules for Identifying Monoclonal Antibodies with Drug-like Specificity. Mol Pharm 2020; 17:2555-2569. [PMID: 32453957 PMCID: PMC7936472 DOI: 10.1021/acs.molpharmaceut.0c00257] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The ability of antibodies to recognize their target antigens with high specificity is fundamental to their natural function. Nevertheless, therapeutic antibodies display variable and difficult-to-predict levels of nonspecific and self-interactions that can lead to various drug development challenges, including antibody aggregation, abnormally high viscosity, and rapid antibody clearance. Here we report a method for predicting the overall specificity of antibodies in terms of their relative risk for displaying high levels of nonspecific or self-interactions at physiological conditions. We find that individual and combined sets of chemical rules that limit the maximum and minimum numbers of certain solvent-exposed amino acids in antibody variable regions are strong predictors of specificity for large panels of preclinical and clinical-stage antibodies. We also demonstrate how the chemical rules can be used to identify sites that mediate nonspecific interactions in suboptimal antibodies and guide the design of targeted sublibraries that yield variants with high antibody specificity. These findings can be readily used to improve the selection and engineering of antibodies with drug-like specificity.
Collapse
Affiliation(s)
- Yulei Zhang
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lina Wu
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Priyanka Gupta
- Department of Biochemistry and Biophysics, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
- Biotherapeutics Discovery Department, Boehringer Ingelheim, Ridgefield, CT 06877
| | - Alec A. Desai
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Matthew D. Smith
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lilia A. Rabia
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
- Isermann Department of Chemical & Biological Engineering, Troy, NY 12180, USA
| | - Seth D. Ludwig
- Isermann Department of Chemical & Biological Engineering, Troy, NY 12180, USA
| | - Peter M. Tessier
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI 48109, USA
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI 48109, USA
- Isermann Department of Chemical & Biological Engineering, Troy, NY 12180, USA
- Department of Biochemistry and Biophysics, Rensselaer Polytechnic Institute, Troy, NY 12180, USA
| |
Collapse
|