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Lenzen PS, Dingfelder F, Müller M, Arosio P. Portable Microfluidic Viscometer for Formulation Development and in Situ Quality Control of Protein and Antibody Solutions. Anal Chem 2024. [PMID: 39093923 DOI: 10.1021/acs.analchem.4c02099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Viscosity of protein solutions is a critical product quality attribute for protein therapeutics such as monoclonal antibodies. Here we introduce a portable single-use analytical chip-based viscometer for determining the viscosity of protein solutions using low sample volumes of 10 μL. Through the combined use of a microfluidic viscometer, a smartphone camera for image capture, and an automated data processing algorithm for the calculation of the viscosity of fluids, we enable measurement of viscosity of multiple samples in parallel. We first validate the viscometer using glycerol-water mixtures and subsequently demonstrate the ability to perform rapid characterization of viscosity in four different monoclonal antibody formulations in a broad concentration (1 to 320 mg/mL) and viscosity (1 to 600 cP) range, showing excellent agreement with values obtained by a conventional cone-plate rheometer. Not only does the platform offer benefits of viscosity measurements using minimal sample volumes, but enables higher throughput compared to gold-standard methodologies owing to multiplexing of the measurement and single-use characteristics of the viscometer, thus showing great promise in developability studies. Additionally, as our platform has the capability of performing viscosity measurements at the point of sample collection, it offers the opportunity to employ viscosity measurement as an in situ quality control of therapeutic proteins and antibodies.
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Affiliation(s)
- Philippe S Lenzen
- ETH Zürich, Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, 8093 Zürich, Switzerland
| | - Fabian Dingfelder
- Janssen R&D, BTDS Analytical Development, 8200 Schaffhausen, Switzerland
| | - Marius Müller
- Janssen R&D, BTDS Analytical Development, 8200 Schaffhausen, Switzerland
| | - Paolo Arosio
- ETH Zürich, Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, 8093 Zürich, Switzerland
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2
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Halim VA, de Jonker M, Esteve C, Assenberg R, Balog C. Novel EDTA mediated ethanol protein precipitation method and the application for polysorbate quantification in high protein concentration biopharmaceuticals. J Pharm Biomed Anal 2024; 245:116145. [PMID: 38631071 DOI: 10.1016/j.jpba.2024.116145] [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: 11/07/2023] [Revised: 03/18/2024] [Accepted: 03/28/2024] [Indexed: 04/19/2024]
Abstract
Non-ionic surfactants such as Polysorbate 20/ 80 (PS20/ PS80), are commonly used in protein drug formulations to increase protein stability by protecting against interfacial stress and surface absorption. Polysorbate is susceptible to degradation which can impact product stability, leading to the formation of sub-visible and/or visible particles in the drug product during its shelf-life, affecting patient safety and efficacy. Therefore, it is important to monitor polysorbate concentration in drug product formulations of biotherapeutic drugs. The common method for measuring polysorbate concentration in drug product formulations uses mixed mode ion exchange reversed phase HPLC (MAX) coupled to evaporative light scattering detection (ELSD). However, high protein concentration can adversely impact method performance due to high sample viscosity, gel formation, column clogging, interfering peaks and loss of accuracy. To overcome this, a new method was developed based on EDTA mediated ethanol protein precipitation (EDTA/EtOH). This method was successfully implemented for the analysis of polysorbate in antibody formulations with wide range of protein concentration (10-250 mg/mL).
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Affiliation(s)
- Vincentius A Halim
- Therapeutics Development and Supply, Analytical Development, Janssen Biologics BV., Einsteinweg 101, Leiden 2333 CB, the Netherlands.
| | - Maurice de Jonker
- Therapeutics Development and Supply, Analytical Development, Janssen Biologics BV., Einsteinweg 101, Leiden 2333 CB, the Netherlands
| | - Clara Esteve
- Therapeutics Development and Supply, Analytical Development, Janssen Biologics BV., Einsteinweg 101, Leiden 2333 CB, the Netherlands
| | - Rene Assenberg
- Therapeutics Development and Supply, Analytical Development, Janssen Biologics BV., Einsteinweg 101, Leiden 2333 CB, the Netherlands
| | - Crina Balog
- Therapeutics Development and Supply, Analytical Development, Janssen Biologics BV., Einsteinweg 101, Leiden 2333 CB, the Netherlands; Manufacturing Science and Technology, Janssen Biologics BV., Einsteinweg 101, Leiden 2333 CB, the Netherlands
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3
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Manning MC, Holcomb RE, Payne RW, Stillahn JM, Connolly BD, Katayama DS, Liu H, Matsuura JE, Murphy BM, Henry CS, Crommelin DJA. Stability of Protein Pharmaceuticals: Recent Advances. Pharm Res 2024; 41:1301-1367. [PMID: 38937372 DOI: 10.1007/s11095-024-03726-x] [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: 03/25/2024] [Accepted: 06/03/2024] [Indexed: 06/29/2024]
Abstract
There have been significant advances in the formulation and stabilization of proteins in the liquid state over the past years since our previous review. Our mechanistic understanding of protein-excipient interactions has increased, allowing one to develop formulations in a more rational fashion. The field has moved towards more complex and challenging formulations, such as high concentration formulations to allow for subcutaneous administration and co-formulation. While much of the published work has focused on mAbs, the principles appear to apply to any therapeutic protein, although mAbs clearly have some distinctive features. In this review, we first discuss chemical degradation reactions. This is followed by a section on physical instability issues. Then, more specific topics are addressed: instability induced by interactions with interfaces, predictive methods for physical stability and interplay between chemical and physical instability. The final parts are devoted to discussions how all the above impacts (co-)formulation strategies, in particular for high protein concentration solutions.'
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Affiliation(s)
- Mark Cornell Manning
- Legacy BioDesign LLC, Johnstown, CO, USA.
- Department of Chemistry, Colorado State University, Fort Collins, CO, USA.
| | - Ryan E Holcomb
- Legacy BioDesign LLC, Johnstown, CO, USA
- Department of Chemistry, Colorado State University, Fort Collins, CO, USA
| | - Robert W Payne
- Legacy BioDesign LLC, Johnstown, CO, USA
- Department of Chemistry, Colorado State University, Fort Collins, CO, USA
| | - Joshua M Stillahn
- Legacy BioDesign LLC, Johnstown, CO, USA
- Department of Chemistry, Colorado State University, Fort Collins, CO, USA
| | | | | | | | | | | | - Charles S Henry
- Department of Chemistry, Colorado State University, Fort Collins, CO, USA
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4
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Esfahani IC, Tehrani NA, Ji S, Sun H. Simultaneous Protein Adsorption and Viscosity Measurement using Micropillar-Enhanced Acoustic Wave (μPAW) Device for Pharmaceutical Applications. J Pharm Sci 2024:S0022-3549(24)00223-5. [PMID: 38857644 DOI: 10.1016/j.xphs.2024.06.001] [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: 01/27/2024] [Revised: 06/03/2024] [Accepted: 06/04/2024] [Indexed: 06/12/2024]
Abstract
At the early stages of drug development, the amount of drug materials is rather limited. In this case, viscosity measurement is often postponed to the later stages, where grams of proteins can be produced. Therefore, it is necessary to develop a viscometer capable of measuring the viscosity with high accuracy while requiring low sample volume. This study presents a novel viscosity measurement technique based on measuring the resonance frequency and motional resistance of a micropillar-enhanced acoustic wave (μPAW) device. The μPAW was developed by fabricating micropillars on the quartz crystal microbalance substrate in order to achieve ultra-high sensitivity, thanks to a unique coupling between the micropillar and the resonator. The experimental measurements demonstrated a nonlinear relationship between the density and viscosity of the fluid and the response of μPAW. A calibration correlation was developed using the response of μPAW in aqueous glycerol and sucrose solutions. The measurements were then extended using high-concentration BSA solutions as the model of protein solution. The main advantage of the μPAW device in this work over other viscometers is the ability to simultaneously measure solution viscosity and protein adsorption on the surface. This is a huge step forward in the development of sensing systems for the pharmaceutical industry, where real-time sensing of target biological proteins and measuring the viscosity of a solution is required.
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Affiliation(s)
| | - Nastaran A Tehrani
- Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, United States
| | - Siqi Ji
- Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, United States
| | - Hongwei Sun
- Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, United States.
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5
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Prašnikar M, Proj M, Bjelošević Žiberna M, Lebar B, Knez B, Kržišnik N, Roškar R, Gobec S, Grabnar I, Žula A, Ahlin Grabnar P. The search for novel proline analogs for viscosity reduction and stabilization of highly concentrated monoclonal antibody solutions. Int J Pharm 2024; 655:124055. [PMID: 38554741 DOI: 10.1016/j.ijpharm.2024.124055] [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: 02/12/2024] [Revised: 03/16/2024] [Accepted: 03/25/2024] [Indexed: 04/02/2024]
Abstract
Administration of monoclonal antibodies (mAbs) is currently focused on subcutaneous injection associated with increased patient adherence and reduced treatment cost, leading to sustainable healthcare. The main bottleneck is low volume that can be injected, requiring highly concentrated mAb solutions. The latter results in increased solution viscosity with pronounced mAb aggregation propensity because of intensive protein-protein interactions. Small molecule excipients have been proposed to restrict the protein-protein interactions, contributing to reduced viscosity. The aim of the study was to discover novel compounds that reduce the viscosity of highly concentrated mAb solution. First, the chemical space of proline analogs was explored and 35 compounds were determined. Viscosity measurements revealed that 18 proline analogs reduced the mAb solution viscosity similar to or more than proline. The compounds forming both electrostatic and hydrophobic interactions with mAb reduced the viscosity of the formulation more efficiently without detrimentally effecting mAb physical stability. A correlation between the level of interaction and viscosity-reducing effect was confirmed with molecular dynamic simulations. Structure rigidity of the compounds and aromaticity contributed to their viscosity-reducing effect, dependent on molecule size. The study results highlight the novel proline analogs as an effective approach in viscosity reduction in development of biopharmaceuticals for subcutaneous administration.
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Affiliation(s)
- Monika Prašnikar
- University of Ljubljana, Faculty of Pharmacy, Aškerčeva cesta 7, 1000 Ljubljana, Slovenia
| | - Matic Proj
- University of Ljubljana, Faculty of Pharmacy, Aškerčeva cesta 7, 1000 Ljubljana, Slovenia
| | | | - Blaž Lebar
- Biologics Drug Product, Technical Research and Development, Global Drug Development, Novartis, Slovenia
| | - Benjamin Knez
- Biologics Drug Product, Technical Research and Development, Global Drug Development, Novartis, Slovenia
| | - Nika Kržišnik
- University of Ljubljana, Faculty of Pharmacy, Aškerčeva cesta 7, 1000 Ljubljana, Slovenia
| | - Robert Roškar
- University of Ljubljana, Faculty of Pharmacy, Aškerčeva cesta 7, 1000 Ljubljana, Slovenia
| | - Stanislav Gobec
- University of Ljubljana, Faculty of Pharmacy, Aškerčeva cesta 7, 1000 Ljubljana, Slovenia
| | - Iztok Grabnar
- University of Ljubljana, Faculty of Pharmacy, Aškerčeva cesta 7, 1000 Ljubljana, Slovenia
| | - Aleš Žula
- Biologics Drug Product, Technical Research and Development, Global Drug Development, Novartis, Slovenia
| | - Pegi Ahlin Grabnar
- University of Ljubljana, Faculty of Pharmacy, Aškerčeva cesta 7, 1000 Ljubljana, Slovenia.
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6
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Gao H, Ge XZ, Liu JW, Wang ST, Xu J, Fang WJ. Effect of Annealing on Visible-Bubble Formation and Stability Profiles of Freeze-Dried High Concentration Omalizumab Formulations. Mol Pharm 2024; 21:1691-1704. [PMID: 38430187 DOI: 10.1021/acs.molpharmaceut.3c00991] [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] [Indexed: 03/03/2024]
Abstract
In the clinical application of freeze-dried highly concentrated omalizumab formulations, extensive visible bubbles (VBs) can be generated and remain for a long period of time in the reconstitution process, which greatly reduces the clinical use efficiency. It is necessary to understand the forming and breaking mechanism of VBs in the reconstitution process, which is a key factor for efficient and safe administration of biopharmaceutical injection. The effects of different thermal treatments on the volume of VBs and stability of omalizumab, mAb-1, and mAb-2 were investigated. The internal microvoids of the cake were characterized by scanning electron microscopy and mercury intrusion porosimetry. Electron paramagnetic resonance was applied to obtain the molecular mobility of the protein during annealing. A large number of VBs were generated in the reconstitution process of unannealed omalizumab and remained for a long period of time. When annealing steps were added, the volume of VBs was dramatically reduced. When annealed at an aggressive temperature (i.e., -6 °C), although the volume of VBs decreased, the aggregation and acidic species increased significantly. Thus, our observations highlight the importance of setting an additional annealing step with a suitable temperature, which contributes to reducing the VBs while maintaining the stability of the high concentration freeze-dried protein formulation.
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Affiliation(s)
- Han Gao
- Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
- Hangzhou Institute of Innovative Medicine, Zhejiang University, Hangzhou 310016, China
| | - Xin-Zhe Ge
- Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
- Hangzhou Institute of Innovative Medicine, Zhejiang University, Hangzhou 310016, China
| | - Jia-Wei Liu
- Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
- Hangzhou Institute of Innovative Medicine, Zhejiang University, Hangzhou 310016, China
| | - Si-Tao Wang
- Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
| | - Jie Xu
- Zhejiang Bioray Biopharmaceutical Co., Taizhou 317000, China
| | - Wei-Jie Fang
- Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
- Hangzhou Institute of Innovative Medicine, Zhejiang University, Hangzhou 310016, China
- Innovation Center of Translational Pharmacy, Jinhua Institute of Zhejiang University, Jinhua 321000, China
- Taizhou Institute of Zhejiang University, Taizhou 317000, China
- Jinhua Hongyao Biotech Co., Ltd., Jinhua 321000, China
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7
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Tian Z, Jiang X, Chen Z, Huang C, Qian F. Quantifying Protein Shape to Elucidate Its Influence on Solution Viscosity in High-Concentration Electrolyte Solutions. Mol Pharm 2024; 21:1719-1728. [PMID: 38411904 DOI: 10.1021/acs.molpharmaceut.3c01075] [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] [Indexed: 02/28/2024]
Abstract
Therapeutic proteins with a high concentration and low viscosity are highly desirable for subcutaneous and certain local injections. The shape of a protein is known to influence solution viscosity; however, the precise quantification of protein shape and its relative impact compared to other factors like charge-charge interactions remains unclear. In this study, we utilized seven model proteins of varying shapes and experimentally determined their shape factors (v) based on Einstein's viscosity theory, which correlate strongly with the ratios of the proteins' surface area to the 2/3 power of their respective volumes, based on protein crystal structures resolved experimentally or predicted by AlphaFold. This finding confirms the feasibility of computationally estimating protein shape factors from amino acid sequences alone. Furthermore, our results demonstrated that, in high-concentration electrolyte solutions, a more spherical protein shape increases the protein's critical concentration (C*), the transition concentration beyond which protein viscosity increases exponentially relative to concentration increases. In summary, our work elucidates protein shape as a key determinant of solution viscosity through quantitative analysis and comparison with other contributing factors. This provides insights into molecular engineering strategies to optimize the molecular design of therapeutic proteins, thus optimizing their viscosity.
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Affiliation(s)
- Zhou Tian
- School of Pharmaceutical Sciences, Beijing Frontier Research Center for Biological Structure, and Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Tsinghua University, Beijing 100084, P. R. China
| | - Xuling Jiang
- School of Pharmaceutical Sciences, Beijing Frontier Research Center for Biological Structure, and Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Tsinghua University, Beijing 100084, P. R. China
| | - Zhidong Chen
- School of Pharmaceutical Sciences, Beijing Frontier Research Center for Biological Structure, and Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Tsinghua University, Beijing 100084, P. R. China
| | - Chengnan Huang
- School of Pharmaceutical Sciences, Beijing Frontier Research Center for Biological Structure, and Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Tsinghua University, Beijing 100084, P. R. China
| | - Feng Qian
- School of Pharmaceutical Sciences, Beijing Frontier Research Center for Biological Structure, and Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology (Ministry of Education), Tsinghua University, Beijing 100084, P. R. China
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8
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Patel R, Menon J, Kumar S, Nóbrega MB, Patel DA, Sakure AA, Vaja MB. Modern day breeding approaches for improvement of castor. Heliyon 2024; 10:e27048. [PMID: 38463846 PMCID: PMC10920369 DOI: 10.1016/j.heliyon.2024.e27048] [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: 05/08/2023] [Revised: 02/12/2024] [Accepted: 02/22/2024] [Indexed: 03/12/2024] Open
Abstract
Castor (Ricinus communis L.) is an industrially important oil producing crop belongs to Euphorbiaceae family. Castor oil has unique chemical properties make it industrially important crop. It is a member of monotypic genus even though it has ample amount of variability. Using this variability, conventionally many varieties and hybrids have been developed. But, like other crops, the modern and unconventional methods of crop improvement has not fully explored in castor. This article discusses the use of polyploidy induction, distant/wide hybridization and mutation breeding as tools for generating variety. Modern approaches accelerate the speed of crop breeding as an alternative tool. To achieve this goal, molecular markers are employed in breeding to capture the genetic variability through molecular analysis and population structuring. Allele mining is used to trace the evolution of alleles, identify new haplotypes and produce allele specific markers for use in marker aided selection using Genome wide association studies (GWAS) and quantitative trait loci (QTL) mapping. Plant genetic transformation is a rapid and effective mode of castor improvement is also discussed here. The efforts towards developing stable regeneration protocol provide a wide range of utility like embryo rescue in distant crosses, development of somaclonal variation, haploid development using anther culture and callus development for stable genetic transformation has reviewed in this article. Omics has provided intuitions to the molecular mechanisms of (a)biotic stress management in castor along with dissected out the possible genes for improving the yield. Relating genes to traits offers additional scientific inevitability leading to enhancement and sympathetic mechanisms of yield improvement and several stress tolerance.
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Affiliation(s)
- Rumit Patel
- Department of Agricultural Biotechnology, Anand Agricultural University, Anand, 388110, India
- Department of Genetics & Plant Breeding, B. A. College of Agriculture, Anand Agricultural University, Anand, 388110, India
| | - Juned Menon
- Department of Genetics & Plant Breeding, B. A. College of Agriculture, Anand Agricultural University, Anand, 388110, India
| | - Sushil Kumar
- Department of Agricultural Biotechnology, Anand Agricultural University, Anand, 388110, India
| | - Márcia B.M. Nóbrega
- Embrapa Algodão, Rua Oswaldo Cruz, nº 1.143, Centenário, CEP 58428-095, Campina Grande, PB, Brazil
| | - Dipak A. Patel
- Department of Agricultural Biotechnology, Anand Agricultural University, Anand, 388110, India
| | - Amar A. Sakure
- Department of Agricultural Biotechnology, Anand Agricultural University, Anand, 388110, India
| | - Mahesh B. Vaja
- Department of Agricultural Biotechnology, Anand Agricultural University, Anand, 388110, India
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9
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Hao X, Fan L. ProtT5 and random forests-based viscosity prediction method for therapeutic mAbs. Eur J Pharm Sci 2024; 194:106705. [PMID: 38246432 DOI: 10.1016/j.ejps.2024.106705] [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: 11/09/2023] [Revised: 01/01/2024] [Accepted: 01/15/2024] [Indexed: 01/23/2024]
Abstract
Viscosity is a key characteristic of therapeutic antibodies for subcutaneous administration which requires low volume and high concentration formulations. It would be highly beneficial to accurately predict the viscosity of newly developed therapeutic antibodies in the early stages of development. In this work, a ProtT5-XL-UniRef50 (ProtT5) and Random Forests (RF)-based prediction method was proposed for accurately predicting the viscosity of monoclonal antibodies, with only corresponding sequences needed. Starting from the given heavy and light chain V-region sequences, corresponding features were first extracted from the ProtT5 pretrained model. Kernel principal analysis (Kernel-PCA) was then used for reducing the extracted 2048-D (1024-D for each sequence) feature vector to a reasonable level for efficient training of the RF-regressor. Then, the RF model was constructed on 40 commercially available therapeutic antibodies and tested with 3-folds cross-validation. Test results show that the model could reproduce the viscosity value at a high level (Pearson correlation coefficient (PCC) = 0.928). Performance on classifying high (>30 cP) and low (<30 cP) viscosity is much more satisfactory, the Accuracy (ACC) and the area under precision-recall curve (AUC) of the classification model from validation tests are 0.975 and 1.000, respectively. Compared to 5 existing state-of-the-art viscosity prediction methods, the proposed method performs best which would facilitate high concentration antibody viscosity high-throughput screening.
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Affiliation(s)
- Xiaohu Hao
- Production and R&D Center I of LSS (Life Science Service), GenScript Biotech Corporation, No. 28, Yongxi Rd., Nanjing, 211110, Jiangsu, China
| | - Long Fan
- Production and R&D Center I of LSS (Life Science Service), GenScript Biotech Corporation, No. 28, Yongxi Rd., Nanjing, 211110, Jiangsu, China; Production and R&D Center I of LSS (Life Science Service), GenScript (Shanghai) Biotech Corporation, No. 186, Hedan Rd., Shanghai, 200100, China.
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10
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Mock M, Langmead CJ, Grandsard P, Edavettal S, Russell A. Recent advances in generative biology for biotherapeutic discovery. Trends Pharmacol Sci 2024; 45:255-267. [PMID: 38378385 DOI: 10.1016/j.tips.2024.01.003] [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: 11/30/2023] [Revised: 12/22/2023] [Accepted: 01/05/2024] [Indexed: 02/22/2024]
Abstract
Generative biology combines artificial intelligence (AI), advanced life sciences technologies, and automation to revolutionize the process of designing novel biomolecules with prescribed properties, giving drug discoverers the ability to escape the limitations of biology during the design of next-generation protein therapeutics. Significant hurdles remain, namely: (i) the inherently complex nature of drug discovery, (ii) the bewildering number of promising computational and experimental techniques that have emerged in the past several years, and (iii) the limited availability of relevant protein sequence-function data for drug-like molecules. There is a need to focus on computational methods that will be most practically effective for protein drug discovery and on building experimental platforms to generate the data most appropriate for these methods. Here, we discuss recent advances in computational and experimental life sciences that are most crucial for impacting the pace and success of protein drug discovery.
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Affiliation(s)
- Marissa Mock
- Amgen Research, Amgen Inc., One Amgen Center Drive, Thousand Oaks, CA 91320, USA
| | | | - Peter Grandsard
- Amgen Research, Amgen Inc., One Amgen Center Drive, Thousand Oaks, CA 91320, USA
| | - Suzanne Edavettal
- Amgen Research, Amgen Inc., One Amgen Center Drive, Thousand Oaks, CA 91320, USA
| | - Alan Russell
- Amgen Research, Amgen Inc., One Amgen Center Drive, Thousand Oaks, CA 91320, USA.
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11
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Dignon G, Dill KA. Computational Procedure for Predicting Excipient Effects on Protein-Protein Affinities. J Chem Theory Comput 2024; 20:1479-1488. [PMID: 38294777 PMCID: PMC10868583 DOI: 10.1021/acs.jctc.3c01197] [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: 10/29/2023] [Revised: 01/16/2024] [Accepted: 01/17/2024] [Indexed: 02/01/2024]
Abstract
Protein-protein interactions lie at the center of many biological processes and are a challenge in formulating biological drugs, such as antibodies. A key to mitigating protein association is to use small-molecule additives, i.e., excipients that can weaken protein-protein interactions. Here, we develop a computationally efficient model for predicting the viscosity-reducing effect of different excipient molecules by combining atomic-resolution MD simulations, binding polynomials, and a thermodynamic perturbation theory. In a proof of principle, this method successfully ranks the order of four types of excipients known to reduce the viscosity of solutions of a particular monoclonal antibody. This approach appears useful for predicting the effects of excipients on protein association and phase separation, as well as the effects of buffers on protein solutions.
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Affiliation(s)
- Gregory
L. Dignon
- Laufer
Center for Physical and Quantitative Biology, Stony Brook University, 100 Nicolls Road, Stony Brook, New York 11794, United States
| | - Ken A. Dill
- Laufer
Center for Physical and Quantitative Biology, Stony Brook University, 100 Nicolls Road, Stony Brook, New York 11794, United States
- Department
of Chemistry, Stony Brook University, 100 Nicolls Road, Stony Brook, New York 11794, United States
- Department
of Physics and Astronomy, Stony Brook University, 100 Nicolls Road, Stony Brook, New York 11794, United States
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12
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Pang MJ, Wang MW, Mao LF, Guo Z, Qian C, Zheng XH, Fang WJ. The Osmolality and Hemolysis of High-Concentration Monoclonal Antibody Formulations. Pharm Res 2024; 41:281-291. [PMID: 38172366 DOI: 10.1007/s11095-023-03650-6] [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: 10/25/2023] [Accepted: 12/20/2023] [Indexed: 01/05/2024]
Abstract
PURPOSES Highly concentrated monoclonal antibody (mAb) formulations for subcutaneous administration are becoming increasingly preferred within the biopharmaceutical industry for ease of use and improved patient compliance. A common phenomenon observed in the industry is that osmolality detected via freezing-point depression (FPD) in high-concentration mAb formulations is much higher than the theoretical concentrations, yet the occurrence of this phenomenon and its possible safety issues have been rarely reported. METHODS The current study summarized theoretical osmolality of U.S. Food and Drug Administration approved high-concentration mAb formulations and evaluated effects of high osmolality on safety using hemolysis experiments for the first time. Two mAbs formulated at 150 mg/mL were used as models and configured into two isotonic solutions: a, a theoretically calculated molarity in the isotonic range (H) and b, an osmolality value measured via the FPD in the isotonic range (I). The H and I formulations of each mAb were individually subjected to hemolysis experiments, and the hemolysis rates of the two formulations of the same mAb were compared. Besides, the effect of mAb concentration on osmolality detected by FPD was explored as well. RESULTS The results indicated that the hemolysis rates were similar between the H and I formulations of mAbs at the same sample addition volume, and the osmolality values increased approximately linearly with the increase in mAb concentration. CONCLUSIONS High osmolality for high-concentration mAb formulations would not affect product safety and the excipients could be added at relatively high levels to maintain product stability, especially for labile products.
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Affiliation(s)
- Meng-Juan Pang
- Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
- Hangzhou Institute of Innovative Medicine, Zhejiang University, Hangzhou, 310016, China
| | - Meng-Wen Wang
- Zhejiang Bioray Biopharmaceutical Co., Taizhou, 317000, China
| | - Li-Fei Mao
- Zhejiang Hisun Pharmaceutical Co., Taizhou, 317000, China
| | - Ze Guo
- Zhejiang Hisun Pharmaceutical Co., Taizhou, 317000, China
| | - Ci Qian
- Zhejiang Bioray Biopharmaceutical Co., Taizhou, 317000, China
| | - Xiao-He Zheng
- Zhejiang Hisun Pharmaceutical Co., Taizhou, 317000, China
| | - Wei-Jie Fang
- Institute of Drug Metabolism and Pharmaceutical Analysis, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China.
- Hangzhou Institute of Innovative Medicine, Zhejiang University, Hangzhou, 310016, China.
- Innovation Center of Translational Pharmacy, Jinhua Institute of Zhejiang University, Jinhua, 321000, China.
- Taizhou Institute of Zhejiang University, Taizhou, 317000, China.
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13
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Brudar S, Breydo L, Chung E, Dill KA, Ehterami N, Phadnis K, Senapati S, Shameem M, Tang X, Tayyab M, Hribar-Lee B. Antibody association in solution: cluster distributions and mechanisms. MAbs 2024; 16:2339582. [PMID: 38666507 PMCID: PMC11057677 DOI: 10.1080/19420862.2024.2339582] [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: 12/07/2023] [Accepted: 04/02/2024] [Indexed: 05/01/2024] Open
Abstract
Understanding factors that affect the clustering and association of antibodies molecules in solution is critical to their development as therapeutics. For 19 different monoclonal antibody (mAb) solutions, we measured the viscosities, the second virial coefficients, the Kirkwood-Buff integrals, and the cluster distributions of the antibody molecules as functions of protein concentration. Solutions were modeled using the statistical-physics Wertheim liquid-solution theory, representing antibodies as Y-shaped molecular structures of seven beads each. We found that high-viscosity solutions result from more antibody molecules per cluster. Multi-body properties such as viscosity are well predicted experimentally by the 2-body Kirkwood-Buff quantity, G22, but not by the second virial coefficient, B22, and well-predicted theoretically from the Wertheim protein-protein sticking energy. Weakly interacting antibodies are rate-limited by nucleation; strongly interacting ones by propagation. This approach gives a way to relate micro to macro properties of solutions of associating proteins.
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Affiliation(s)
- Sandi Brudar
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, Ljubljana, Slovenia
| | - Leonid Breydo
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Elisha Chung
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Ken A. Dill
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY, USA
- Department of Chemistry and Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY, USA
| | - Nasim Ehterami
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Ketan Phadnis
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Samir Senapati
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Mohammed Shameem
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Xiaolin Tang
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Muhammmad Tayyab
- Formulation Development Group, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Barbara Hribar-Lee
- Faculty of Chemistry and Chemical Technology, University of Ljubljana, Ljubljana, Slovenia
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14
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Heisler J, Kovner D, Izadi S, Zarzar J, Carter PJ. Modulation of the high concentration viscosity of IgG 1 antibodies using clinically validated Fc mutations. MAbs 2024; 16:2379560. [PMID: 39028186 PMCID: PMC11262234 DOI: 10.1080/19420862.2024.2379560] [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: 04/04/2024] [Accepted: 07/09/2024] [Indexed: 07/20/2024] Open
Abstract
The self-association of therapeutic antibodies can result in elevated viscosity and create problems in manufacturing and formulation, as well as limit delivery by subcutaneous injection. The high concentration viscosity of some antibodies has been reduced by variable domain mutations or by the addition of formulation excipients. In contrast, the impact of Fc mutations on antibody viscosity has been minimally explored. Here, we studied the effect of a panel of common and clinically validated Fc mutations on the viscosity of two closely related humanized IgG1, κ antibodies, omalizumab (anti-IgE) and trastuzumab (anti-HER2). Data presented here suggest that both Fab-Fab and Fab-Fc interactions contribute to the high viscosity of omalizumab, in a four-contact model of self-association. Most strikingly, the high viscosity of omalizumab (176 cP) was reduced 10.7- and 2.2-fold by Fc modifications for half-life extension (M252Y:S254T:T256E) and aglycosylation (N297G), respectively. Related single mutations (S254T and T256E) each reduced the viscosity of omalizumab by ~6-fold. An alternative half-life extension Fc mutant (M428L:N434S) had the opposite effect in increasing the viscosity of omalizumab by 1.5-fold. The low viscosity of trastuzumab (8.6 cP) was unchanged or increased by ≤ 2-fold by the different Fc variants. Molecular dynamics simulations provided mechanistic insight into the impact of Fc mutations in modulating electrostatic and hydrophobic surface properties as well as conformational stability of the Fc. This study demonstrates that high viscosity of some IgG1 antibodies can be mitigated by Fc mutations, and thereby offers an additional tool to help design future antibody therapeutics potentially suitable for subcutaneous delivery.
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Affiliation(s)
- Joel Heisler
- Department of Antibody Engineering, Genentech, Inc, South San Francisco, CA, USA
| | - Daniel Kovner
- Department of Pharmaceutical Development, Genentech, Inc, South San Francisco, CA, USA
| | - Saeed Izadi
- Department of Pharmaceutical Development, Genentech, Inc, South San Francisco, CA, USA
| | - Jonathan Zarzar
- Department of Pharmaceutical Development, Genentech, Inc, South San Francisco, CA, USA
| | - Paul J. Carter
- Department of Antibody Engineering, Genentech, Inc, South San Francisco, CA, USA
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15
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Dai J, Izadi S, Zarzar J, Wu P, Oh A, Carter PJ. Variable domain mutational analysis to probe the molecular mechanisms of high viscosity of an IgG 1 antibody. MAbs 2024; 16:2304282. [PMID: 38269489 PMCID: PMC10813588 DOI: 10.1080/19420862.2024.2304282] [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: 10/19/2023] [Accepted: 01/08/2024] [Indexed: 01/26/2024] Open
Abstract
Subcutaneous injection is the preferred route of administration for many antibody therapeutics for reasons that include its speed and convenience. However, the small volume limit (typically ≤ 2 mL) for subcutaneous delivery often necessitates antibody formulations at high concentrations (commonly ≥100 mg/mL), which may lead to physicochemical problems. For example, antibodies with large hydrophobic or charged patches can be prone to self-interaction giving rise to high viscosity. Here, we combined X-ray crystallography with computational modeling to predict regions of an anti-glucagon receptor (GCGR) IgG1 antibody prone to self-interaction. An extensive mutational analysis was undertaken of the complementarity-determining region residues residing in hydrophobic surface patches predicted by spatial aggregation propensity, in conjunction with residue-level solvent accessibility, averaged over conformational ensembles from molecular dynamics simulations. Dynamic light scattering (DLS) was used as a medium throughput screen for self-interaction of ~ 200 anti-GCGR IgG1 variants. A negative correlation was found between the viscosity determined at high concentration (180 mg/mL) and the DLS interaction parameter measured at low concentration (2-10 mg/mL). Additionally, anti-GCGR variants were readily identified with reduced viscosity and antigen-binding affinity within a few fold of the parent antibody, with no identified impact on overall developability. The methods described here may be useful in the optimization of other antibodies to facilitate their therapeutic administration at high concentration.
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Affiliation(s)
- Jing Dai
- Department of Antibody Engineering, Genentech, Inc, South San Francisco, CA, USA
| | - Saeed Izadi
- Department of Pharmaceutical Development, Genentech, Inc, South San Francisco, CA, USA
| | - Jonathan Zarzar
- Department of Pharmaceutical Development, Genentech, Inc, South San Francisco, CA, USA
| | - Patrick Wu
- Department of Bioanalytical Sciences, Genentech, Inc, South San Francisco, CA, USA
| | - Angela Oh
- Department of Structural Biology, Genentech, Inc, South San Francisco, CA, USA
| | - Paul J. Carter
- Department of Antibody Engineering, Genentech, Inc, South San Francisco, CA, USA
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16
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Dignon GL, Dill KA. A computational procedure for predicting excipient effects on protein-protein affinities. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.22.573113. [PMID: 38187552 PMCID: PMC10769426 DOI: 10.1101/2023.12.22.573113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Protein-protein interactions lie at the center of much biology and are a challenge in formulating biological drugs such as antibodies. A key to mitigating protein association is to use small molecule additives, i.e. excipients that can weaken protein-protein interactions. Here, we develop a computationally efficient model for predicting the viscosity-reducing effect of different excipient molecules by combining atomic-resolution MD simulations, binding polynomials and a thermodynamic perturbation theory. In a proof of principle, this method successfully rank orders four types of excipients known to reduce the viscosity of solutions of a particular monoclonal antibody. This approach appears useful for predicting effects of excipients on protein association and phase separation, as well as the effects of buffers on protein solutions.
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Affiliation(s)
- Gregory L Dignon
- Laufer Center for Physical and Quantitative Biology, Stony Brook University
- Current address: Department of Chemical and Biochemical Engineering, Rutgers University
| | - Ken A Dill
- Laufer Center for Physical and Quantitative Biology, Stony Brook University
- Department of Chemistry, Stony Brook University
- Department of Physics and Astronomy, Stony Brook University
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17
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Wei Y, Qi W, Maglalang E, Pelegri-O'Day EM, Luong M, Razinkov V, Sloey C. Improved Diffusion Interaction Parameter Measurement to Predict the Viscosity of Concentrated mAb Solutions. Mol Pharm 2023; 20:6420-6428. [PMID: 37906640 DOI: 10.1021/acs.molpharmaceut.3c00797] [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] [Indexed: 11/02/2023]
Abstract
During the developability assessment of therapeutic monoclonal antibody (mAb) candidates, utilization of robust high-throughput predictive assays enables rapid selection of top candidates with low risks for late-stage development. Predicting the viscosities of highly concentrated mAbs using limited materials is an important aspect of developability assessment because high viscosity can complicate manufacturability, stability, and administration. Here, we report a high-throughput assay measuring protein-protein interactions to predict mAb viscosity. The diffusion interaction parameter (kD) measures colloidal self-association in dilute solutions and has been reported to be predictive of the mAb viscosity at high concentrations. However, kD of Amgen early stage IgG1 mAb candidates measured in 10 mM acetate at pH 5.2 containing sucrose and polysorbate (denoted A52SuT) shows only weak correlation to their viscosities at 140 mg/mL in A52SuT. We hypothesize that kD measured in A52SuT reflects primarily long-range electrostatic repulsions because most of these mAb candidates carry strong net positive charges in this low ionic strength formulation with pH (5.2) well below pI values of mAb candidates. However, the viscosities of high concentration mAbs depend heavily on short-range molecular interactions. We propose an improved kD method in which salt is added to suppress charge repulsions and to allow for detection of key short-range interactions in dilute solutions. Salt types and salt concentrations were screened, and an optimal salt condition was identified. This optimized method was further validated using two test mAb sets. Overall, the method improves the Pearson R2 between kD and viscosity (6-230 cP) from 0.24 to 0.80 for a data set consisting of 37 mAbs.
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Affiliation(s)
- Yangjie Wei
- Drug Product Technologies, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320, United States
| | - Wei Qi
- Drug Product Technologies, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320, United States
| | - Erick Maglalang
- Drug Product Technologies, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320, United States
| | - Emma M Pelegri-O'Day
- Molecular Analytics, Biologics Therapeutics Discovery, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320, United States
| | - Michelle Luong
- Drug Product Technologies, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320, United States
| | - Vladimir Razinkov
- Drug Product Technologies, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320, United States
| | - Christopher Sloey
- Drug Product Technologies, Amgen Inc., 1 Amgen Center Drive, Thousand Oaks, California 91320, United States
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18
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Bhandari K, Wei Y, Amer BR, Pelegri-O’Day EM, Huh J, Schmit JD. Prediction of Antibody Viscosity from Dilute Solution Measurements. Antibodies (Basel) 2023; 12:78. [PMID: 38131800 PMCID: PMC10740665 DOI: 10.3390/antib12040078] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 11/20/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023] Open
Abstract
The high antibody doses required to achieve a therapeutic effect often necessitate high-concentration products that can lead to challenging viscosity issues in production and delivery. Predicting antibody viscosity in early development can play a pivotal role in reducing late-stage development costs. In recent years, numerous efforts have been made to predict antibody viscosity through dilute solution measurements. A key finding is that the entanglement of long, flexible complexes contributes to the sharp rise in antibody viscosity at the required dosing. This entanglement model establishes a connection between the two-body binding affinity and the many-body viscosity. Exploiting this insight, this study connects dilute solution measurements of self-association to high-concentration viscosity profiles to quantify the relationship between these regimes. The resulting model has exhibited success in predicting viscosity at high concentrations (around 150 mg/mL) from dilute solution measurements, with only a few outliers remaining. Our physics-based approach provides an understanding of fundamental physics, interpretable connections to experimental data, the potential to extrapolate beyond training conditions, and the capacity to effectively explain the physical mechanics behind these outliers. Conducting hypothesis-driven experiments that specifically target the viscosity and relaxation mechanisms of outlier molecules may allow us to unravel the intricacies of their behavior and, in turn, enhance the performance of our model.
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Affiliation(s)
- Kamal Bhandari
- Department of Physics, Kansas State University, Manhattan, KS 66506, USA;
| | - Yangjie Wei
- Amgen Inc., Thousand Oaks, CA 91320, USA; (Y.W.); (B.R.A.); (E.M.P.-O.); (J.H.)
| | - Brendan R. Amer
- Amgen Inc., Thousand Oaks, CA 91320, USA; (Y.W.); (B.R.A.); (E.M.P.-O.); (J.H.)
| | | | - Joon Huh
- Amgen Inc., Thousand Oaks, CA 91320, USA; (Y.W.); (B.R.A.); (E.M.P.-O.); (J.H.)
| | - Jeremy D. Schmit
- Department of Physics, Kansas State University, Manhattan, KS 66506, USA;
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19
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Yang S, Jin M, Park CS, Moon C, Kim M, Kim J, Jang L, Jang JY, Jeong CM, Kim HH. Identification, quantification, and structural role of N-glycans in two highly purified isoforms of sheep testicular hyaluronidase. Int J Biol Macromol 2023; 252:126437. [PMID: 37611686 DOI: 10.1016/j.ijbiomac.2023.126437] [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: 03/20/2023] [Revised: 07/04/2023] [Accepted: 08/18/2023] [Indexed: 08/25/2023]
Abstract
Animal-derived hyaluronidase, which hydrolyzes the polysaccharide hyaluronic acid, has been used in medical applications despite its limited purity. Additionally, the N-glycan characterization of sheep testicular hyaluronidase (STH) and its structural role remain poorly understood. In this study, STH was purified from the commercially available STH preparation (containing at least 14 impurity proteins) using heparin-affinity chromatography followed by size exclusion chromatography. The structure and quantity of N-glycans of STH were investigated using liquid chromatography-electrospray ionization-high energy collision dissociation-tandem mass spectrometry. Two isoforms, H3S1 and H3S2, of STH were obtained (purity >98 %) with a yield of 3.4 % and 5.1 %, respectively. Fourteen N-glycans, including nine core-fucosylated N-glycans (important for the stability and function of glycoproteins), were identified in both H3S1 and H3S2, with similar quantities of each N-glycan. The amino acid sequences of the proteolytic peptides of H3S1 and H3S2 were compared with those reported in STH. The hyaluronic acid-degrading activity of deglycosylated H3S1 and H3S2 was reduced to 70.8 % and 71.1 % compared to that (100 %) of H3S1 and H3S2, respectively. This is the first report of N-glycan characterization of two highly purified isoforms of STH. These H3S1 and H3S2 will be useful for medical use without unwanted effects of partially purified STH.
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Affiliation(s)
- Subin Yang
- Biotherapeutics and Glycomics Laboratory, College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea; Department of Global Innovative Drugs, Graduate School of Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
| | - Mijung Jin
- Biotherapeutics and Glycomics Laboratory, College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea; Department of Global Innovative Drugs, Graduate School of Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
| | - Chi Soo Park
- Biotherapeutics and Glycomics Laboratory, College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea; Department of Global Innovative Drugs, Graduate School of Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
| | - Chulmin Moon
- Biotherapeutics and Glycomics Laboratory, College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea; Department of Global Innovative Drugs, Graduate School of Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
| | - Mirae Kim
- Biotherapeutics and Glycomics Laboratory, College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea; Department of Global Innovative Drugs, Graduate School of Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
| | - Jieun Kim
- Biotherapeutics and Glycomics Laboratory, College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea; Department of Global Innovative Drugs, Graduate School of Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
| | - Leeseul Jang
- Biotherapeutics and Glycomics Laboratory, College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea; Department of Global Innovative Drugs, Graduate School of Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
| | - Ji Yeon Jang
- Biotherapeutics and Glycomics Laboratory, College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea; Department of Global Innovative Drugs, Graduate School of Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
| | - Chang Myeong Jeong
- Biotherapeutics and Glycomics Laboratory, College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea; Department of Global Innovative Drugs, Graduate School of Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
| | - Ha Hyung Kim
- Biotherapeutics and Glycomics Laboratory, College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea; Department of Global Innovative Drugs, Graduate School of Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea.
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20
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Meza NP, Hardy CA, Morin KH, Huang C, Raghava S, Song J, Zhang J, Wang Y. Predicting Colloidal Stability of High-Concentration Monoclonal Antibody Formulations in Common Pharmaceutical Buffers Using Improved Polyethylene Glycol Induced Protein Precipitation Assay. Mol Pharm 2023; 20:5842-5855. [PMID: 37867303 DOI: 10.1021/acs.molpharmaceut.3c00694] [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] [Indexed: 10/24/2023]
Abstract
Colloidal stability is an important consideration when developing high concentration mAb formulations. PEG-induced protein precipitation is a commonly used assay to assess the colloidal stability of protein solutions. However, the practical usefulness and the current theoretical model for this assay have yet to be verified over a large formulation space across multiple mAbs and mAb-based modalities. In the present study, we used PEG-induced protein precipitation assays to evaluate colloidal stability of 3 mAbs in 24 common formulation buffers at 20 and 5 °C. These prediction assays were conducted at low protein concentration (1 mg/mL). We also directly characterized high concentration (100 mg/mL) formulations for cold-induced phase separation, turbidity, and concentratibility by ultrafiltration. This systematic study allowed analysis of the correlation between the results of low concentration assays and the high concentration attributes. The key findings of this study include the following: (1) verification of the usefulness of three different parameters (Cmid, μB, and Tcloud) from PEG-induced protein precipitation assays for ranking colloidal stability of high concentration mAb formulations; (2) a new method to implement PEG-induced protein precipitation assay suitable for high throughput screening with low sample consumption; (3) improvement in the theoretical model for calculating robust thermodynamic parameters of colloidal stability (μB and εB) that are independent of specific experimental settings; (4) systematic evaluation of the effects of pH and buffer salts on colloidal stability of mAbs in common formulation buffers. These findings provide improved theoretical and practical tools for assessing the colloidal stability of mAbs and mAb-based modalities during formulation development.
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Affiliation(s)
- Noemi P Meza
- Department of Chemistry and Biochemistry, University of North Carolina Wilmington, Wilmington, North Carolina 28403, United States
| | - Colin A Hardy
- Department of Chemistry and Biochemistry, University of North Carolina Wilmington, Wilmington, North Carolina 28403, United States
| | - Kylie H Morin
- Department of Chemistry and Biochemistry, University of North Carolina Wilmington, Wilmington, North Carolina 28403, United States
| | - Chengbin Huang
- Analytical Research and Development, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Smita Raghava
- Sterile and Specialty Products, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Jing Song
- Analytical Research and Development, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Jingtao Zhang
- Analytical Research and Development, Merck & Co., Inc., Rahway, New Jersey 07065, United States
| | - Ying Wang
- Department of Chemistry and Biochemistry, University of North Carolina Wilmington, Wilmington, North Carolina 28403, United States
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21
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Chowdhury AA, Manohar N, Lanzaro A, Kimball WD, Witek MA, Woldeyes MA, Majumdar R, Qian KK, Xu S, Gillilan RE, Huang Q, Truskett TM, Johnston KP. Characterizing Protein-Protein Interactions and Viscosity of a Monoclonal Antibody from Low to High Concentration Using Small-Angle X-ray Scattering and Molecular Dynamics Simulations. Mol Pharm 2023; 20:5563-5578. [PMID: 37782765 DOI: 10.1021/acs.molpharmaceut.3c00484] [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] [Indexed: 10/04/2023]
Abstract
Understanding protein-protein interactions and formation of reversible oligomers (clusters) in concentrated monoclonal antibody (mAb) solutions is necessary for designing stable, low viscosity (η) concentrated formulations for processing and subcutaneous injection. Here we characterize the strength (K) of short-range anisotropic attractions (SRA) for 75-200 mg/mL mAb2 solutions at different pH and cosolute conditions by analyzing structure factors (Seff(q)) from small-angle X-ray scattering (SAXS) using coarse-grained molecular dynamics simulations. Best fit simulations additionally provide cluster size distributions, fractal dimensions, cluster occluded volume, and mAb coordination numbers. These equilibrium properties are utilized in a model to account for increases in viscosity caused by occluded volume in the clusters (packing effects) and dissipation of stress across lubricated fractal clusters. Seff(q) is highly sensitive to K at 75 mg/mL where mAbs can mutually align to form SRA contacts but becomes less sensitive at 200 mg/mL as steric repulsion due to packing becomes dominant. In contrast, η at 200 mg/mL is highly sensitive to SRA and the average cluster size from SAXS/simulation, which is observed to track the cluster relaxation time from shear thinning. By analyzing the distribution of sub-bead hot spots on the 3D mAb surface, we identify a strongly attractive hydrophobic patch in the complementarity determining region (CDR) at pH 4.5 that contributes to the high K and consequently large cluster sizes and high η. Adding NaCl screens electrostatic interactions and increases the impact of hydrophobic attraction on cluster size and raises η, whereas nonspecific binding of Arg attenuates all SRA, reducing η. The hydrophobic patch is absent at higher pH values, leading to smaller K, smaller clusters, and lower η. This work constitutes a first attempt to use SAXS and CG modeling to link both structural and rheological properties of concentrated mAb solutions to the energetics of specific hydrophobic patches on mAb surfaces. As such, our work opens an avenue for future research, including the possibility of designing coarse-grained models with physically meaningful interacting hot spots.
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Affiliation(s)
- Amjad A Chowdhury
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Neha Manohar
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Alfredo Lanzaro
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - William D Kimball
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Marta A Witek
- Eli Lilly and Company, Indianapolis, Indiana 46225, United States
| | | | - Ranajoy Majumdar
- Eli Lilly and Company, Indianapolis, Indiana 46225, United States
| | - Ken K Qian
- Eli Lilly and Company, Indianapolis, Indiana 46225, United States
| | - Shifeng Xu
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Richard E Gillilan
- Center for High Energy X-ray Sciences at CHESS, Cornell University, Ithaca, New York 14853, United States
| | - Qingqiu Huang
- Center for High Energy X-ray Sciences at CHESS, Cornell University, Ithaca, New York 14853, United States
| | - Thomas M Truskett
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
- Department of Physics, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Keith P Johnston
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas 78712, United States
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22
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Malta R, Marques AC, da Costa PC, Amaral MH. Stimuli-Responsive Hydrogels for Protein Delivery. Gels 2023; 9:802. [PMID: 37888375 PMCID: PMC10606693 DOI: 10.3390/gels9100802] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 10/02/2023] [Accepted: 10/04/2023] [Indexed: 10/28/2023] Open
Abstract
Proteins and peptides are potential therapeutic agents, but their physiochemical properties make their use as drug substances challenging. Hydrogels are hydrophilic polymeric networks that can swell and retain high amounts of water or biological fluids without being dissolved. Due to their biocompatibility, their porous structure, which enables the transport of various peptides and proteins, and their protective effect against degradation, hydrogels have gained prominence as ideal carriers for these molecules' delivery. Particularly, stimuli-responsive hydrogels exhibit physicochemical transitions in response to subtle modifications in the surrounding environment, leading to the controlled release of entrapped proteins or peptides. This review is focused on the application of these hydrogels in protein and peptide delivery, including a brief overview of therapeutic proteins and types of stimuli-responsive polymers.
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Affiliation(s)
- Rafaela Malta
- CeNTI—Centre for Nanotechnology and Smart Materials, Rua Fernando Mesquita, 2785, 4760-034 Vila Nova de Famalicão, Portugal;
| | - Ana Camila Marques
- UCIBIO—Applied Molecular Biosciences Unit, MEDTECH, Laboratory of Pharmaceutical Technology, Department of Drug Sciences, Faculty of Pharmacy, University of Porto, R. Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal;
- Associate Laboratory i4HB, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, R. Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal
| | - Paulo Cardoso da Costa
- UCIBIO—Applied Molecular Biosciences Unit, MEDTECH, Laboratory of Pharmaceutical Technology, Department of Drug Sciences, Faculty of Pharmacy, University of Porto, R. Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal;
- Associate Laboratory i4HB, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, R. Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal
| | - Maria Helena Amaral
- UCIBIO—Applied Molecular Biosciences Unit, MEDTECH, Laboratory of Pharmaceutical Technology, Department of Drug Sciences, Faculty of Pharmacy, University of Porto, R. Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal;
- Associate Laboratory i4HB, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, R. Jorge Viterbo Ferreira 228, 4050-313 Porto, Portugal
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23
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Campuzano IDG. A Research Journey: Over a Decade of Denaturing and Native-MS Analyses of Hydrophobic and Membrane Proteins in Amgen Therapeutic Discovery. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2023; 34:2413-2431. [PMID: 37643331 DOI: 10.1021/jasms.3c00175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Membrane proteins and associated complexes currently comprise the majority of therapeutic targets and remain among the most challenging classes of proteins for analytical characterization. Through long-term strategic collaborations forged between industrial and academic research groups, there has been tremendous progress in advancing membrane protein mass spectrometry (MS) analytical methods and their concomitant application to Amgen therapeutic project progression. Herein, I will describe a detailed and personal account of how electrospray ionization (ESI) native mass spectrometry (nMS), ion mobility-MS (IM-MS), reversed phase liquid chromatographic mass spectrometry (RPLC-MS), high-throughput solid phase extraction mass spectrometry, and matrix-assisted laser desorption ionization mass spectrometry methods were developed, optimized, and validated within Amgen Research, and importantly, how these analytical methods were applied for membrane and hydrophobic protein analyses and ultimately therapeutic project support and progression. Additionally, I will discuss all the highly important and productive collaborative efforts, both internal Amgen and external academic, which were key in generating the samples, methods, and associated data described herein. I will also describe some early and previously unpublished nano-ESI (nESI) native-MS data from Amgen Research and the highly productive University of California Los Angeles (UCLA) collaboration. I will also present previously unpublished examples of real-life Amgen biotherapeutic membrane protein projects that were supported by all the MS (and IM) analytical techniques described herein. I will start by describing the initial nESI nMS experiments performed at Amgen in 2011 on empty nanodisc molecules, using a quadrupole time-of-flight MS, and how these experiments progressed on to the 15 Tesla Fourier transform ion cyclotron resonance MS at UCLA. Then described are monomeric and multimeric membrane protein data acquired in both nESI nMS and tandem-MS modes, using multiple methods of ion activation, resulting in dramatic spectral simplification. Also described is how we investigated the far less established and less published subject, that is denaturing RPLC-MS analysis of membrane proteins, and how we developed a highly robust and reproducible RPLC-MS method capable of effective separation of membrane proteins differing in only the presence or absence of an N-terminal post translational modification. Also described is the evolution of the aforementioned RPLC-MS method into a high-throughput solid phase extraction MS method. Finally, I will give my opinion on key developments and how the area of nMS of membrane proteins needs to evolve to a state where it can be applied within the biopharmaceutical research environment for routine therapeutic project support.
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Affiliation(s)
- Iain D G Campuzano
- Amgen Research, Center for Research Acceleration by Digital Innovation, Molecular Analytics, Thousand Oaks, California 91320, United States
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24
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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.
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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
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25
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Mills BJ, Godamudunage MP, Ren S, Laha M. Predictive Nature of High-Throughput Assays in ADC Formulation Screening. J Pharm Sci 2023; 112:1821-1831. [PMID: 37037342 DOI: 10.1016/j.xphs.2023.03.021] [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: 12/19/2022] [Revised: 03/28/2023] [Accepted: 03/29/2023] [Indexed: 04/12/2023]
Abstract
Utilization of high-throughput biophysical screening techniques during early screening studies is warranted due to the limited amount of material and large number of samples. But the predictability of the data to longer-term storage stability is critical as the high-throughput methods assist in defining the design space for the longer-term studies. In this study, the biophysical properties of two ADCs in 16 formulation conditions were evaluated using high-throughput techniques. Conformational stability and colloidal stability were evaluated by determining Tm values, kD, B22, and Tagg. In addition, the samples were placed on stability and the extent of aggregate formation over the 8-week interval was determined. The rank order of the 16 different formulations in the high-throughput assays was compared to the rank order observed during the stability studies to assess the predictive capabilities of the screening methods. It was demonstrated that similar rank orders can be expected between high-throughput physical stability indicating assays such as Tagg and B22 and traditional aggregation by SEC data, whereas conformational stability read-outs (Tm) are less predictive. In addition, the high-throughput assays appropriately identified the poor performing formulation conditions, which is ultimately what is desired of screening assays.
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Affiliation(s)
- Brittney J Mills
- Biologics CMC Drug Product Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, IL 60064, United States.
| | - Malika P Godamudunage
- Biologics CMC Drug Product Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, IL 60064, United States
| | - Siyuan Ren
- Biologics CMC Drug Product Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, IL 60064, United States
| | - Malabika Laha
- Biologics CMC Drug Product Development, AbbVie Inc., 1 N Waukegan Road, North Chicago, IL 60064, United States
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26
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Rojekar S, Pallapati AR, Gimenez-Roig J, Korkmaz F, Sultana F, Sant D, Haeck C, Macdonald A, Kim SM, Rosen CJ, Barak O, Meseck M, Caminis J, Lizneva D, Yuen T, Zaidi M. Development and Biophysical Characterization of a Humanized FSH-Blocking Monoclonal Antibody Therapeutic Formulated at an Ultra-High Concentration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.11.540323. [PMID: 37214886 PMCID: PMC10197643 DOI: 10.1101/2023.05.11.540323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Highly concentrated antibody formulations are oftentimes required for subcutaneous, self-administered biologics. Here, we report the creation of a unique formulation for our first-in- class FSH-blocking humanized antibody, MS-Hu6, which we propose to move to the clinic for osteoporosis, obesity, and Alzheimer's disease. The studies were carried out using our Good Laboratory Practice (GLP) platform, compliant with the Code of Federal Regulations (Title 21, Part 58). We first used protein thermal shift, size exclusion chromatography, and dynamic light scattering to examine MS-Hu6 concentrations between 1 and 100 mg/mL. We found that thermal, monomeric, and colloidal stability of formulated MS-Hu6 was maintained at a concentration of 100 mg/mL. The addition of the antioxidant L-methionine and chelating agent disodium EDTA improved the formulation's long-term colloidal and thermal stability. Thermal stability was further confirmed by Nano differential scanning calorimetry (DSC). Physiochemical properties of formulated MS-Hu6, including viscosity, turbidity, and clarity, conformed with acceptable industry standards. That the structural integrity of MS-Hu6 in formulation was maintained was proven through Circular Dichroism (CD) and Fourier Transform Infrared (FTIR) spectroscopy. Three rapid freeze-thaw cycles at -80°C/25°C or -80°C/37°C further revealed excellent thermal and colloidal stability. Furthermore, formulated MS-Hu6, particularly its Fab domain, displayed thermal and monomeric storage stability for more than 90 days at 4°C and 25°C. Finally, the unfolding temperature (T m ) for formulated MS-Hu6 increased by >4.80°C upon binding to recombinant FSH, indicating highly specific ligand binding. Overall, we document the feasibility of developing a stable, manufacturable and transportable MS-Hu6 formulation at a ultra-high concentration at industry standards. The study should become a resource for developing biologic formulations in academic medical centers.
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27
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Rivera-Rivera LY, Moore TC, Glotzer SC. Inverse design of triblock Janus spheres for self-assembly of complex structures in the crystallization slot via digital alchemy. SOFT MATTER 2023; 19:2726-2736. [PMID: 36974942 DOI: 10.1039/d2sm01593e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
The digital alchemy framework is an extended ensemble simulation technique that incorporates particle attributes as thermodynamic variables, enabling the inverse design of colloidal particles for desired behavior. Here, we extend the digital alchemy framework for the inverse design of patchy spheres that self-assemble into target crystal structures. To constrain the potentials to non-trivial solutions, we conduct digital alchemy simulations with constant second virial coefficient. We optimize the size, range, and strength of patchy interactions in model triblock Janus spheres to self-assemble the 2D kagome and snub square lattices and the 3D pyrochlore lattice, and demonstrate self-assembly of all three target structures with the designed models. The particles designed for the kagome and snub square lattices assemble into high quality clusters of their target structures, while competition from similar polymorphs lower the yield of the pyrochlore assemblies. We find that the alchemically designed potentials do not always match physical intuition, illustrating the ability of the method to find nontrivial solutions to the optimization problem. We identify a window of second virial coefficients that result in self-assembly of the target structures, analogous to the crystallization slot in protein crystallization.
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Affiliation(s)
| | - Timothy C Moore
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.
| | - Sharon C Glotzer
- Department of Chemical Engineering, University of Michigan, Ann Arbor, MI, USA.
- Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA
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28
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Zhang C, Bye JW, Lui LH, Zhang H, Hales J, Brocchini S, Curtis RA, Dalby PA. Enhanced Thermal Stability and Reduced Aggregation in an Antibody Fab Fragment at Elevated Concentrations. Mol Pharm 2023; 20:2650-2661. [PMID: 37040431 PMCID: PMC10155210 DOI: 10.1021/acs.molpharmaceut.3c00081] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2023]
Abstract
The aggregation of protein therapeutics such as antibodies remains a major challenge in the biopharmaceutical industry. The present study aimed to characterize the impact of the protein concentration on the mechanisms and potential pathways for aggregation, using the antibody Fab fragment A33 as the model protein. Aggregation kinetics were determined for 0.05 to 100 mg/mL Fab A33, at 65 °C. A surprising trend was observed whereby increasing the concentration decreased the relative aggregation rate, ln(v) (% day-1), from 8.5 at 0.05 mg/mL to 4.4 at 100 mg/mL. The absolute aggregation rate (mol L-1 h-1) increased with the concentration following a rate order of approximately 1 up to a concentration of 25 mg/mL. Above this concentration, there was a transition to an apparently negative rate order of -1.1 up to 100 mg/mL. Several potential mechanisms were examined as possible explanations. A greater apparent conformational stability at 100 mg/mL was observed from an increase in the thermal transition midpoint (Tm) by 7-9 °C, relative to those at 1-4 mg/mL. The associated change in unfolding entropy (△Svh) also increased by 14-18% at 25-100 mg/mL, relative to those at 1-4 mg/mL, indicating reduced conformational flexibility in the native ensemble. Addition of Tween or the crowding agents Ficoll and dextran, showed that neither surface adsorption, diffusion limitations nor simple volume crowding affected the aggregation rate. Fitting of kinetic data to a wide range of mechanistic models implied a reversible two-state conformational switch mechanism from aggregation-prone monomers (N*) into non-aggregating native forms (N) at higher concentrations. kD measurements from DLS data also suggested a weak self-attraction while remaining colloidally stable, consistent with macromolecular self-crowding within weakly associated reversible oligomers. Such a model is also consistent with compaction of the native ensemble observed through changes in Tm and △Svh.
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Affiliation(s)
- Cheng Zhang
- Department of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, U.K
| | - Jordan W Bye
- School of Chemical Engineering and Analytical Science, The University of Manchester, Sackville Street, Manchester M13 9PL, U.K
| | - Lok H Lui
- UCL School of Pharmacy, 29-39 Brunswick Square, London WC1N 1AX, U.K
| | - Hongyu Zhang
- Department of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, U.K
| | - John Hales
- Department of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, U.K
| | - Steve Brocchini
- UCL School of Pharmacy, 29-39 Brunswick Square, London WC1N 1AX, U.K
| | - Robin A Curtis
- School of Chemical Engineering and Analytical Science, The University of Manchester, Sackville Street, Manchester M13 9PL, U.K
| | - Paul A Dalby
- Department of Biochemical Engineering, University College London, Gower Street, London WC1E 6BT, U.K
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29
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Algorri M, Cauchon NS, Christian T, O'Connell C, Vaidya P. Patient-Centric Product Development: A Summary of Select Regulatory CMC and Device Considerations. J Pharm Sci 2023; 112:922-936. [PMID: 36739904 DOI: 10.1016/j.xphs.2023.01.029] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/30/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023]
Abstract
Patient-centric drug development describes the systematic approach to incorporating the patient's perspectives and preferences into the design, assessment, and production of a therapeutic product. While a patient centric approach can be applied at any stage of the drug development lifecycle, an integrated end-to-end strategy is often most effective to create an optimized product for the patient at the earliest possible timepoint. The importance of patient centricity is well recognized by health authorities and biopharmaceutical organizations which have established toolsets, guidances, and methodologies for incorporating patient input during the clinical stage of development. However, in addition to clinical research, there are other significant aspects of product development that profoundly impact the patient experience. Specifically, chemistry, manufacturing, and control (CMC) and device aspects must also be acknowledged and addressed as part of a cohesive patient-centric development strategy. This review explores current applications and regulatory considerations for patient-centric approaches across the product lifecycle, including R&D, early product development, clinical development, device and combination product development, and post-approval change management. Specific topics of discussion include the contributions of product modality, formulation, and devices to the patient experience; usage of the Quality Target Product Profile (QTPP) as a patient-centered design tool; and post-approval product optimization. Future advancements in regulatory data management and information exchange are also explored as potential enablers of patient engagement which support enhanced communication and interconnectivity between stakeholders. Multidisciplinary collaboration between patients, health authorities, health care providers, and the biopharmaceutical industry is ultimately necessary for ensuring that medicinal products, and their corresponding regulatory processes, take on a patient-first mindset that prioritizes patient needs, values, and preferences.
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Affiliation(s)
- Marquerita Algorri
- Department of Global Regulatory Affairs and Strategy - CMC, Amgen Inc, Thousand Oaks, CA 91320, USA
| | - Nina S Cauchon
- Department of Global Regulatory Affairs and Strategy - CMC, Amgen Inc, Thousand Oaks, CA 91320, USA.
| | | | - Chelsea O'Connell
- Department of Global Regulatory Affairs and Strategy - Global Regulatory and R&D Policy, Amgen Inc, Thousand Oaks, CA 91320, USA
| | - Pujita Vaidya
- Department of Global Regulatory Affairs and Strategy - Global Regulatory and R&D Policy, Amgen Inc, Thousand Oaks, CA 91320, USA
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30
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Chowdhury A, Manohar N, Guruprasad G, Chen AT, Lanzaro A, Blanco M, Johnston KP, Truskett TM. Characterizing Experimental Monoclonal Antibody Interactions and Clustering Using a Coarse-Grained Simulation Library and a Viscosity Model. J Phys Chem B 2023; 127:1120-1137. [PMID: 36716270 DOI: 10.1021/acs.jpcb.2c07616] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Attractive protein-protein interactions in concentrated monoclonal antibody (mAb) solutions may lead to the formation of clusters that increase viscosity. Here, we propose an analytical model that relates mAb solution viscosity to clustering by accounting for the contributions of suboptimal mAb packing within a cluster and cluster fractal dimension. The influence of short-range, anisotropic attractions and long-range Coulombic repulsion on cluster properties is investigated by analyzing the cluster-size distributions, cluster fractal dimensions, radial distribution functions, and static structure factors from a library of coarse-grained molecular dynamics simulations. The library spans a vast range of mAb charges and attractive interactions in solutions of varying ionic strength. We present a framework for combining the viscosity model and simulation library to successfully characterize the attraction, repulsion, and clustering of an experimental mAb in three different pH and cosolute conditions by fitting the measured viscosity or structure factor from small-angle X-ray scattering. At low ionic strength, the cluster-size distribution is impacted by strong charges, and both the viscosity and net charge or structure factor and net charge must be considered to deconvolute the effects of short-range attraction and long-range repulsion.
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Affiliation(s)
- Amjad Chowdhury
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Neha Manohar
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Geetika Guruprasad
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Amy T Chen
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Alfredo Lanzaro
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Marco Blanco
- Analytical Enabling Capabilities, Analytical R&D, Merck & Co., Inc., Rahway, New Jersey07065, United States
| | - Keith P Johnston
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States
| | - Thomas M Truskett
- McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas78712, United States.,Department of Physics, The University of Texas at Austin, Austin, Texas78712, United States
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31
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Condado-Morales I, Sokolova V, Wahlund PO, Heding KE, Auclair S, Kingsbury JS, Arosio P, Lorenzen N. AF4 and PEG Precipitation as Predictive Assays for Antibody Self-Association. Mol Pharm 2023; 20:1323-1330. [PMID: 36668814 DOI: 10.1021/acs.molpharmaceut.2c00946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Monoclonal antibodies (mAbs) are often formulated as high-protein-concentration solutions, which in some cases can exhibit physical stability issues such as high viscosity and opalescence. To ensure that mAb-based drugs can meet their manufacturing, stability, and delivery requirements, it is advantageous to screen for and select mAbs during discovery that are not prone to such behaviors. It has been recently shown that both these macroscopic properties can be predicted to a certain extent from the diffusion interaction parameter (kD), which is a measure of self-association under dilute conditions.1 However, kD can be challenging to measure at the early stage of discovery, where a relatively large amount of a high-purity material, which is required by traditional methods, is often not available. In this study, we demonstrate asymmetric field-flow fractionation (AF4) as a tool to measure self-association and therefore identify antibodies with problematic issues at high concentrations. The principle lies on the ability to concentrate the sample close to the membrane during the injection mode, which can reach formulation-relevant concentrations (>100 mg/mL).2 By analyzing a well-characterized library of commercial antibodies, we show that the measured retention time of the antibodies allows us to pinpoint molecules that exhibit issues at high concentrations. Remarkably, our AF4 assay requires very little (30 μg) sample under dilute conditions and does not need extensive sample purification. Furthermore, we show that a polyethylene glycol (PEG) precipitation assay provides results consistent with AF4 and moreover can further differentiate molecules with issues of opalescence or high viscosity. Overall, our results delineate a two-step strategy for the identification of problematic variants at high concentrations, with AF4 for early developability screening, followed by a PEG assay to validate the problematic molecules and further discriminate between opalescence or high-viscosity issues. This two-step antibody selection strategy enables us to select antibodies early in the discovery process, which are compatible with high-concentration formulations.
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Affiliation(s)
- Itzel Condado-Morales
- Global Research Technology, Novo Nordisk A/S, Maaloev 2760, Denmark.,Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, ETH Zürich, Zürich 8093, Switzerland
| | - Viktoria Sokolova
- Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, ETH Zürich, Zürich 8093, Switzerland
| | - Per-Olof Wahlund
- Global Research Technology, Novo Nordisk A/S, Maaloev 2760, Denmark
| | | | - Sarah Auclair
- Global CMC Development, Sanofi, Framingham, Massachusetts 02210, United States
| | | | - Paolo Arosio
- Department of Chemistry and Applied Biosciences, Institute for Chemical and Bioengineering, ETH Zürich, Zürich 8093, Switzerland
| | - Nikolai Lorenzen
- Global Research Technology, Novo Nordisk A/S, Maaloev 2760, Denmark
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32
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Desai PG, Garidel P, Gbormittah FO, Kamen DE, Mills BJ, Narasimhan CN, Singh S, Stokes ESE, Walsh ER. An Intercompany Perspective on Practical Experiences of Predicting, Optimizing and Analyzing High Concentration Biologic Therapeutic Formulations. J Pharm Sci 2023; 112:359-369. [PMID: 36442683 DOI: 10.1016/j.xphs.2022.11.020] [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: 09/02/2022] [Revised: 11/18/2022] [Accepted: 11/18/2022] [Indexed: 11/27/2022]
Abstract
Developing high-dose biologic drugs for subcutaneous injection often requires high-concentration formulations and optimizing viscosity, solubility, and stability while overcoming analytical, manufacturing, and administration challenges. To understand industry approaches for developing high-concentration formulations, the Formulation Workstream of the BioPhorum Development Group, an industry-wide consortium, conducted an inter-company collaborative exercise which included several surveys. This collaboration provided an industry perspective, experience, and insight into the practicalities for developing high-concentration biologics. To understand solubility and viscosity, companies desire predictive tools, but experience indicates that these are not reliable and experimental strategies are best. Similarly, most companies prefer accelerated and stress stability studies to in-silico or biophysical-based prediction methods to assess aggregation. In addition, optimization of primary container-closure and devices are pursued to mitigate challenges associated with high viscosity of the formulation. Formulation strategies including excipient selection and application of studies at low concentration to high-concentration formulations are reported. Finally, analytical approaches to high concentration formulations are presented. The survey suggests that although prediction of viscosity, solubility, and long-term stability is desirable, the outcome can be inconsistent and molecule dependent. Significant experimental studies are required to confirm robust product definition as modeling at low protein concentrations will not necessarily extrapolate to high concentration formulations.
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Affiliation(s)
- Preeti G Desai
- Bristol Myers Squibb, Sterile Product Development, 556 Morris Avenue, Summit, NJ 07901, USA
| | - Patrick Garidel
- Boehringer Ingelheim Pharma GmbH Co KG, Innovation Unit, PDB-TIP, 88397 Biberach an der Riss, Germany
| | - Francisca O Gbormittah
- GlaxoSmithKline, Strategic External Development, 1000 Winter Street North, Waltham, MA 02451, USA
| | - Douglas E Kamen
- Regeneron Pharmaceuticals Inc., Formulation Development, 777 Old Saw Mill River Road, Tarrytown, NY 10591, USA
| | - Brittney J Mills
- AbbVie, NBE Drug Product Development, 1 N Waukegan Road, North Chicago, IL 60064, USA
| | | | - Shubhadra Singh
- GlaxoSmithKline R&D, Biopharmaceutical Product Sciences, Collegeville, PA 19426, USA
| | - Elaine S E Stokes
- BioPhorum, The Gridiron Building, 1 Pancras Square, London N1C 4AG UK.
| | - Erika R Walsh
- Merck & Co., Inc., Sterile and Specialty Products, Rahway, NJ, USA
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33
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Schmitt J, Razvi A, Grapentin C. Predictive modeling of concentration-dependent viscosity behavior of monoclonal antibody solutions using artificial neural networks. MAbs 2023; 15:2169440. [PMID: 36705325 PMCID: PMC9888472 DOI: 10.1080/19420862.2023.2169440] [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: 01/28/2023] Open
Abstract
Solutions of monoclonal antibodies (mAbs) can show increased viscosity at high concentration, which can be a disadvantage during protein purification, filling, and administration. The viscosity is determined by protein-protein-interactions, which are influenced by the antibody's sequence as well as solution conditions, like pH, buffer type, or the presence of salts and other excipients. To predict viscosity, experimental parameters, like the diffusion interaction parameter (kD), or computational tools harnessing information derived from primary sequence, are often used, but a reliable predictive tool is still missing. We present a modeling approach employing artificial neural networks (ANNs) using experimental factors combined with simulation-derived parameters plus viscosity data from 27 highly concentrated (180 mg/mL) mAbs. These ANNs can be used to predict if mAbs exhibit problematic viscosity at distinct concentrations or to model viscosity-concentration-curves.
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Affiliation(s)
| | - Abbas Razvi
- Lonza AG/Ltd, Drug Product Services, Basel, Switzerland
| | - Christoph Grapentin
- Lonza AG/Ltd, Drug Product Services, Basel, Switzerland,CONTACT Christoph Grapentin
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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: 12] [Impact Index Per Article: 12.0] [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.
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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
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35
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Mock M, Jacobitz AW, Langmead CJ, Sudom A, Yoo D, Humphreys SC, Alday M, Alekseychyk L, Angell N, Bi V, Catterall H, Chen CC, Chou HT, Conner KP, Cook KD, Correia AR, Dykstra A, Ghimire-Rijal S, Graham K, Grandsard P, Huh J, Hui JO, Jain M, Jann V, Jia L, Johnstone S, Khanal N, Kolvenbach C, Narhi L, Padaki R, Pelegri-O'Day EM, Qi W, Razinkov V, Rice AJ, Smith R, Spahr C, Stevens J, Sun Y, Thomas VA, van Driesche S, Vernon R, Wagner V, Walker KW, Wei Y, Winters D, Yang M, Campuzano IDG. Development of in silico models to predict viscosity and mouse clearance using a comprehensive analytical data set collected on 83 scaffold-consistent monoclonal antibodies. MAbs 2023; 15:2256745. [PMID: 37698932 PMCID: PMC10498806 DOI: 10.1080/19420862.2023.2256745] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 08/16/2023] [Accepted: 09/05/2023] [Indexed: 09/14/2023] Open
Abstract
Biologic drug discovery pipelines are designed to deliver protein therapeutics that have exquisite functional potency and selectivity while also manifesting biophysical characteristics suitable for manufacturing, storage, and convenient administration to patients. The ability to use computational methods to predict biophysical properties from protein sequence, potentially in combination with high throughput assays, could decrease timelines and increase the success rates for therapeutic developability engineering by eliminating lengthy and expensive cycles of recombinant protein production and testing. To support development of high-quality predictive models for antibody developability, we designed a sequence-diverse panel of 83 effector functionless IgG1 antibodies displaying a range of biophysical properties, produced and formulated each protein under standard platform conditions, and collected a comprehensive package of analytical data, including in vitro assays and in vivo mouse pharmacokinetics. We used this robust training data set to build machine learning classifier models that can predict complex protein behavior from these data and features derived from predicted and/or experimental structures. Our models predict with 87% accuracy whether viscosity at 150 mg/mL is above or below a threshold of 15 centipoise (cP) and with 75% accuracy whether the area under the plasma drug concentration-time curve (AUC0-672 h) in normal mouse is above or below a threshold of 3.9 × 106 h x ng/mL.
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Affiliation(s)
- Marissa Mock
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Alex W Jacobitz
- Process Development, Amgen Operations, Thousand Oaks, CA, USA
| | | | - Athena Sudom
- Structural Biology, Amgen Research, South San Francisco, CA, USA
| | - Daniel Yoo
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Sara C Humphreys
- Pharmacokinetics & Drug Metabolism, Amgen Research, South San Francisco, CA, USA
| | - Mai Alday
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | | | - Nicolas Angell
- Process Development, Amgen Operations, Thousand Oaks, CA, USA
| | - Vivian Bi
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Hannah Catterall
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Chen-Chun Chen
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Hui-Ting Chou
- Structural Biology, Amgen Research, South San Francisco, CA, USA
| | - Kip P Conner
- Pharmacokinetics & Drug Metabolism, Amgen Research, South San Francisco, CA, USA
| | - Kevin D Cook
- Pharmacokinetics & Drug Metabolism, Amgen Research, South San Francisco, CA, USA
| | - Ana R Correia
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Andrew Dykstra
- Process Development, Amgen Operations, Thousand Oaks, CA, USA
| | | | - Kevin Graham
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Peter Grandsard
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Joon Huh
- Process Development, Amgen Operations, Thousand Oaks, CA, USA
| | - John O Hui
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Mani Jain
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Victoria Jann
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Lei Jia
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Sheree Johnstone
- Structural Biology, Amgen Research, South San Francisco, CA, USA
| | - Neelam Khanal
- Process Development, Amgen Operations, Thousand Oaks, CA, USA
| | - Carl Kolvenbach
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Linda Narhi
- Process Development, Amgen Operations, Thousand Oaks, CA, USA
| | - Rupa Padaki
- Process Development, Amgen Operations, Thousand Oaks, CA, USA
| | | | - Wei Qi
- Process Development, Amgen Operations, Thousand Oaks, CA, USA
| | | | - Austin J Rice
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Richard Smith
- Pharmacokinetics & Drug Metabolism, Amgen Research, South San Francisco, CA, USA
| | - Christopher Spahr
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | | | - Yax Sun
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Veena A Thomas
- Pharmacokinetics & Drug Metabolism, Amgen Research, South San Francisco, CA, USA
| | | | - Robert Vernon
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Victoria Wagner
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Kenneth W Walker
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Yangjie Wei
- Process Development, Amgen Operations, Thousand Oaks, CA, USA
| | - Dwight Winters
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
| | - Melissa Yang
- Biologic Therapeutic Discovery, Amgen Research, Thousand Oaks, CA, USA
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Mieczkowski C, Zhang X, Lee D, Nguyen K, Lv W, Wang Y, Zhang Y, Way J, Gries JM. Blueprint for antibody biologics developability. MAbs 2023; 15:2185924. [PMID: 36880643 PMCID: PMC10012935 DOI: 10.1080/19420862.2023.2185924] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2023] Open
Abstract
Large-molecule antibody biologics have revolutionized medicine owing to their superior target specificity, pharmacokinetic and pharmacodynamic properties, safety and toxicity profiles, and amenability to versatile engineering. In this review, we focus on preclinical antibody developability, including its definition, scope, and key activities from hit to lead optimization and selection. This includes generation, computational and in silico approaches, molecular engineering, production, analytical and biophysical characterization, stability and forced degradation studies, and process and formulation assessments. More recently, it is apparent these activities not only affect lead selection and manufacturability, but ultimately correlate with clinical progression and success. Emerging developability workflows and strategies are explored as part of a blueprint for developability success that includes an overview of the four major molecular properties that affect all developability outcomes: 1) conformational, 2) chemical, 3) colloidal, and 4) other interactions. We also examine risk assessment and mitigation strategies that increase the likelihood of success for moving the right candidate into the clinic.
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Affiliation(s)
- Carl Mieczkowski
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Xuejin Zhang
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Dana Lee
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Khanh Nguyen
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Wei Lv
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Yanling Wang
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Yue Zhang
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Jackie Way
- Department of Protein Sciences, Hengenix Biotech, Inc, Milpitas, CA, USA
| | - Jean-Michel Gries
- President, Discovery Research, Hengenix Biotech, Inc, Milpitas, CA, USA
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37
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Shimomura T, Sekiguchi M, Honda R, Yamazaki M, Yokoyama M, Uchiyama S. Estimation of the Viscosity of an Antibody Solution from the Diffusion Interaction Parameter. Biol Pharm Bull 2022; 45:1300-1305. [DOI: 10.1248/bpb.b22-00263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Affiliation(s)
| | | | - Reisa Honda
- Department of Pharmaceutical Technology, Astellas Pharma Inc
| | - Miki Yamazaki
- Department of Pharmaceutical Technology, Astellas Pharma Inc
| | - Masami Yokoyama
- Department of Biotechnology, Graduate School of Engineering, Osaka University
| | - Susumu Uchiyama
- Department of Biotechnology, Graduate School of Engineering, Osaka University
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38
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A Novel MATLAB®-Algorithm-Based Video Analysis to Quantitatively Determine Solution Creeping in Intact Pharmaceutical Glass Vials. Eur J Pharm Biopharm 2022; 178:117-130. [PMID: 35961565 DOI: 10.1016/j.ejpb.2022.08.003] [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: 05/18/2022] [Revised: 08/05/2022] [Accepted: 08/07/2022] [Indexed: 11/20/2022]
Abstract
During the filling process of a biopharmaceutical drug product (DP), a liquid DP film might creep up the inner vial wall which is barely discernible, appears as milky-white haze after lyophilisation and is known as fogging. Creeping and fogging are mainly dependent on the primary packaging material surface and its hydration, vial preparation process as well as DP composition. The occurrence of both can impede visual inspection and might lead to DP rejection. Hence, our studies focused on the early detection of liquid solution and glass vial surface interaction directly after filling. For a fast and highly sensitive evaluation a novel video-based analysis was used. To our knowledge, this is the first time a MATLAB®-algorithm-based video analysis was applied to quantitatively determine creeping time-resolved. Furthermore, creeping in dependence of vial processing sites, surfactant type and concentration, filling temperature, and vial format were investigated. The results were verified using orthogonal conventional methods such as surface tension, wetting behaviour, and contact angle measurements, as well as ToF-SIMS, ICP-MS, and SEM. Additionally, the methods applied were assessed regarding their cross-validation capability. The observations indicate that the vial preparation process can have a pronounced impact on alteration of the glass vial surface and related creeping behaviour of the filled solution.
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39
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Azzouz I, Khlifi K, Faure J, Dhiflaoui H, Larbi ABC, Benhayoune H. Mechanical behavior and corrosion resistance of sol-gel derived 45S5 bioactive glass coating on Ti6Al4V synthesized by electrophoretic deposition. J Mech Behav Biomed Mater 2022; 134:105352. [DOI: 10.1016/j.jmbbm.2022.105352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/23/2022] [Accepted: 06/28/2022] [Indexed: 10/17/2022]
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40
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Srivastava A, O'Dell C, Bolessa E, McLinden S, Fortin L, Deorkar N. Viscosity reduction and stability enhancement of monoclonal antibody formulations using derivatives of amino acids. J Pharm Sci 2022; 111:2848-2856. [DOI: 10.1016/j.xphs.2022.05.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 05/12/2022] [Accepted: 05/12/2022] [Indexed: 11/26/2022]
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41
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Effects of Monovalent Salt on Protein-Protein Interactions of Dilute and Concentrated Monoclonal Antibody Formulations. Antibodies (Basel) 2022; 11:antib11020024. [PMID: 35466277 PMCID: PMC9036246 DOI: 10.3390/antib11020024] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 03/17/2022] [Accepted: 03/24/2022] [Indexed: 02/04/2023] Open
Abstract
In this study, we used sodium chloride (NaCl) to extensively modulate non-specific protein-protein interactions (PPI) of a humanized anti-streptavidin monoclonal antibody class 2 molecule (ASA-IgG2). The changes in PPI with varying NaCl (CNaCl) and monoclonal antibody (mAb) concentration (CmAb) were assessed using the diffusion interaction parameter kD and second virial coefficient B22 measured from solutions with low to moderate CmAb. The effective structure factor S(q)eff measured from concentrated mAb solutions using small-angle X-ray and neutron scattering (SAXS/SANS) was also used to characterize the PPI. Our results found that the nature of net PPI changed not only with CNaCl, but also with increasing CmAb. As a result, parameters measured from dilute and concentrated mAb samples could lead to different predictions on the stability of mAb formulations. We also compared experimentally determined viscosity results with those predicted from interaction parameters, including kD and S(q)eff. The lack of a clear correlation between interaction parameters and measured viscosity values indicates that the relationship between viscosity and PPI is concentration-dependent. Collectively, the behavior of flexible mAb molecules in concentrated solutions may not be correctly predicted using models where proteins are considered to be uniform colloid particles defined by parameters derived from low CmAb.
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42
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Blanco MA. Computational models for studying physical instabilities in high concentration biotherapeutic formulations. MAbs 2022; 14:2044744. [PMID: 35282775 PMCID: PMC8928847 DOI: 10.1080/19420862.2022.2044744] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.
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Affiliation(s)
- Marco A. Blanco
- Materials and Biophysical Characterization, Analytical R & D, Merck & Co., Inc, Kenilworth, NJ USA
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43
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Wang C, Hong J, Yang Z, Zhou X, Yang Y, Kong Y, Chen B, Wu H, Qian BZ, Dimitrov DS, Zhou X, Wu Y, Ying T. Design of a Novel Fab-Like Antibody Fragment with Enhanced Stability and Affinity for Clinical use. SMALL METHODS 2022; 6:e2100966. [PMID: 35174992 DOI: 10.1002/smtd.202100966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 11/05/2021] [Indexed: 06/14/2023]
Abstract
With increasing interest in applying recombinant monoclonal antibodies (mAbs) in human medicine, engineered mAb fragments with reduced size and improved stability are in demand to overcome current limitations in clinical use. Herein, a novel Fab-like antibody fragment generated via an in silico-based engineering approach where the CH1 and CL domains of Fab are replaced by the IgG1 CH3 domains is described. This construct, designated as FabCH3, maintains the natural N-terminus and C-terminus of IgG antibody, can be expressed at a high level in bacterial cells and, importantly, exhibits much higher stability and affinity than the parental Fab when tested in a mesothelin-specific Fab m912, as well as a vascular endothelial growth factor A (VEGFA)-specific Fab Ranibizumab (in vivo). The high-resolution crystal structures of m912 FabCH3 and m912 Fab are determined, and the comparative analysis reveals more rigid structures in both constant domains and complementarity-determining regions of FabCH3, explaining its enhanced stability and affinity. Overall, the stabilized FabCH3 described in this report provides a versatile platform for engineering Fab-like antibody fragments with higher stability and antigen-binding affinity that can be used as a distinct class of antibody therapeutics.
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Affiliation(s)
- Chunyu Wang
- MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Jiaxu Hong
- Department of Ophthalmology and Vision Science, Eye, Ear, Nose and Throat Hospital, Fudan University, Shanghai, 200031, China
- Department of Ophthalmology, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China
| | - Zhenlin Yang
- Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Shanghai Key Laboratory of Lung Inflammation and Injury, Shanghai, 200032, China
| | - Xujiao Zhou
- Department of Ophthalmology and Vision Science, Eye, Ear, Nose and Throat Hospital, Fudan University, Shanghai, 200031, China
| | - Yuhan Yang
- Department of Ophthalmology, The Affiliated Hospital of Guizhou Medical University, Guiyang, 550004, China
| | - Yu Kong
- MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Binfan Chen
- MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Huifang Wu
- MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Bin-Zhi Qian
- Medical Research Council Centre for Reproductive Health, College of Medicine and Veterinary Medicine, Queen's Medical Research Institute, The University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Dimiter S Dimitrov
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Xingtao Zhou
- Department of Ophthalmology and Vision Science, Eye, Ear, Nose and Throat Hospital, Fudan University, Shanghai, 200031, China
| | - Yanling Wu
- MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Shanghai Engineering Research Center for Synthetic Immunology, Shanghai, 200032, China
| | - Tianlei Ying
- MOE/NHC Key Laboratory of Medical Molecular Virology, Shanghai Institute of Infectious Disease and Biosecurity, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai, 200032, China
- Shanghai Engineering Research Center for Synthetic Immunology, Shanghai, 200032, China
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44
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Lai PK, Gallegos A, Mody N, Sathish HA, Trout BL. Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics. MAbs 2022; 14:2026208. [PMID: 35075980 PMCID: PMC8794240 DOI: 10.1080/19420862.2022.2026208] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Machine learning has been recently used to predict therapeutic antibody aggregation rates and viscosity at high concentrations (150 mg/ml). These works focused on commercially available antibodies, which may have been optimized for stability. In this study, we measured accelerated aggregation rates at 45°C and viscosity at 150 mg/ml for 20 preclinical and clinical-stage antibodies. Features obtained from molecular dynamics simulations of the full-length antibody and sequences were used for machine learning model construction. We found a k-nearest neighbors regression model with two features, spatial positive charge map on the CDRH2 and solvent-accessible surface area of hydrophobic residues on the variable fragment, gives the best performance for predicting antibody aggregation rates (r = 0.89). For the viscosity classification model, the model with the highest accuracy is a logistic regression model with two features, spatial negative charge map on the heavy chain variable region and spatial negative charge map on the light chain variable region. The accuracy and the area under precision recall curve of the classification model from validation tests are 0.86 and 0.70, respectively. In addition, we combined data from another 27 commercial mAbs to develop a viscosity predictive model. The best model is a logistic regression model with two features, number of hydrophobic residues on the light chain variable region and net charges on the light chain variable region. The accuracy and the area under precision recall curve of the classification model are 0.85 and 0.6, respectively. The aggregation rates and viscosity models can be used to predict antibody stability to facilitate pharmaceutical development.
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Affiliation(s)
- Pin-Kuang Lai
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Department of Chemical Engineering and Materials Science, Stevens Institute of Technology, Hoboken, New Jersey, USA
| | - Austin Gallegos
- Dosage Form Design and Development, AstraZeneca, Gaithersburg, Maryland, USA
| | - Neil Mody
- Dosage Form Design and Development, AstraZeneca, Gaithersburg, Maryland, USA
| | - Hasige A Sathish
- Dosage Form Design and Development, AstraZeneca, Gaithersburg, Maryland, USA
| | - Bernhardt L Trout
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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45
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Hartl J, Friesen S, Johannsmann D, Buchner R, Hinderberger D, Blech M, Garidel P. Dipolar Interactions and Protein Hydration in Highly Concentrated Antibody Formulations. Mol Pharm 2022; 19:494-507. [PMID: 35073097 DOI: 10.1021/acs.molpharmaceut.1c00587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Molecular interaction mechanisms in high-concentrated protein systems are of fundamental importance for the rational development of biopharmaceuticals such as monoclonal antibody (mAb) formulations. In such high-concentrated protein systems, the intermolecular distances between mAb molecules are reduced to the size of the protein diameter (approx. 10 nm). Thus, protein-protein interactions are more pronounced at high concentrations; so a direct extrapolation of physicochemical properties obtained from measurements at a low protein concentration of the corresponding properties at a high protein concentration is highly questionable. Besides the charge-charge interaction, the effects of molecular crowding, dipolar interaction, changes in protein hydration, and self-assembling tendency become more relevant. Here, protein hydration, protein dipole moment, and protein-protein interactions were studied in protein concentrations up to 200 mg/mL (= 1.3 mM) in different formulations for selected mAbs using dielectric relaxation spectroscopy (DRS). These data are correlated with the second virial coefficient, A2, the diffusion interaction parameter, kD, the elastic shear modulus, G', and the dynamic viscosity, η. When large contributions of dipolar protein-protein interactions were observed, the tendency of self-assembling and an increase in solution viscosity were detected. These effects were examined using specific buffer conditions. Furthermore, different types of protein-water interactions were identified via DRS, whereby the effect of high protein concentration on protein hydration was investigated for different high-concentrated liquid formulations (HCLFs).
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Affiliation(s)
- Josef Hartl
- Institute of Chemistry, Martin-Luther-University Halle-Wittenberg, 06120 Halle (Saale), Germany
| | - Sergej Friesen
- Institute of Physical and Theoretical Chemistry, University of Regensburg, 93053 Regensburg, Germany
| | - Diethelm Johannsmann
- Institute of Physical Chemistry, Clausthal University of Technology, 38678 Clausthal-Zellerfeld, Germany
| | - Richard Buchner
- Institute of Physical and Theoretical Chemistry, University of Regensburg, 93053 Regensburg, Germany
| | - Dariush Hinderberger
- Institute of Chemistry, Martin-Luther-University Halle-Wittenberg, 06120 Halle (Saale), Germany
| | - Michaela Blech
- Boehringer Ingelheim Pharma GmbH & Co. KG, Innovation Unit, PDB, 88397 Biberach an der Riss, Germany
| | - Patrick Garidel
- Boehringer Ingelheim Pharma GmbH & Co. KG, Innovation Unit, PDB, 88397 Biberach an der Riss, Germany
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Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2022; 2313:57-113. [PMID: 34478132 DOI: 10.1007/978-1-0716-1450-1_4] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.
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Deciphering the high viscosity of a therapeutic monoclonal antibody in high concentration formulations by microdialysis-hydrogen/deuterium exchange mass spectrometry. J Pharm Sci 2022; 111:1335-1345. [PMID: 34999091 DOI: 10.1016/j.xphs.2021.12.027] [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: 03/17/2021] [Revised: 12/30/2021] [Accepted: 12/31/2021] [Indexed: 11/22/2022]
Abstract
High concentration formulations of therapeutic monoclonal antibodies (mAbs) are highly desired for subcutaneous injection. However, high concentration formulations can exhibit unusual molecular behaviors, such as high viscosity or aggregation, that present challenges for manufacturing and administration. To understand the molecular mechanism of the high viscosity exhibited by high concentration protein formulations, we analyzed a human IgG4 (mAb1) at high protein concentrations using sedimentation velocity analytical ultracentrifugation (SV-AUC), X-ray crystallography, hydrogen/deuterium exchange mass spectrometry (HDX-MS), and protein surface patches analysis. Particularly, we developed a microdialysis HDX-MS method to determine intermolecular interactions at different protein concentrations. SV-AUC revealed that mAb1 displayed a propensity for self-association of Fab-Fab, Fab-Fc, and Fc-Fc. mAb1 crystal structure and HDX-MS results demonstrated self-association between complementarity-determining regions (CDRs) and Fc through electrostatic interactions. HDX-MS also indicated Fab-Fab interactions through hydrophobic surface patches constructed by mAb1 CDRs. Our multi-method approach, including fast screening of SV-AUC as well as interface analysis by X-ray crystallography and HDX-MS, helped to elucidate the high viscosity of mAb1 at high concentrations as induced by self-associations of Fab-Fc and Fab-Fab.
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Akbar R, Bashour H, Rawat P, Robert PA, Smorodina E, Cotet TS, Flem-Karlsen K, Frank R, Mehta BB, Vu MH, Zengin T, Gutierrez-Marcos J, Lund-Johansen F, Andersen JT, Greiff V. Progress and challenges for the machine learning-based design of fit-for-purpose monoclonal antibodies. MAbs 2022; 14:2008790. [PMID: 35293269 PMCID: PMC8928824 DOI: 10.1080/19420862.2021.2008790] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 11/04/2021] [Accepted: 11/17/2021] [Indexed: 12/15/2022] Open
Abstract
Although the therapeutic efficacy and commercial success of monoclonal antibodies (mAbs) are tremendous, the design and discovery of new candidates remain a time and cost-intensive endeavor. In this regard, progress in the generation of data describing antigen binding and developability, computational methodology, and artificial intelligence may pave the way for a new era of in silico on-demand immunotherapeutics design and discovery. Here, we argue that the main necessary machine learning (ML) components for an in silico mAb sequence generator are: understanding of the rules of mAb-antigen binding, capacity to modularly combine mAb design parameters, and algorithms for unconstrained parameter-driven in silico mAb sequence synthesis. We review the current progress toward the realization of these necessary components and discuss the challenges that must be overcome to allow the on-demand ML-based discovery and design of fit-for-purpose mAb therapeutic candidates.
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Affiliation(s)
- Rahmad Akbar
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Habib Bashour
- School of Life Sciences, University of Warwick, Coventry, UK
| | - Puneet Rawat
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India
| | - Philippe A. Robert
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Eva Smorodina
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Russia
| | | | - Karine Flem-Karlsen
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Department of Pharmacology, University of Oslo and Oslo University Hospital, Norway
| | - Robert Frank
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Brij Bhushan Mehta
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Mai Ha Vu
- Department of Linguistics and Scandinavian Studies, University of Oslo, Norway
| | - Talip Zengin
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
- Department of Bioinformatics, Mugla Sitki Kocman University, Turkey
| | | | | | - Jan Terje Andersen
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, Department of Pharmacology, University of Oslo and Oslo University Hospital, Norway
| | - Victor Greiff
- Department of Immunology, University of Oslo and Oslo University Hospital, Oslo, Norway
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Taghizadeh B, Jaafari MR, Zarghami N. New insight into the importance of formulation variables on parenteral growth hormone preparations: potential effect on the injection-site pain. Front Endocrinol (Lausanne) 2022; 13:963336. [PMID: 36263321 PMCID: PMC9576007 DOI: 10.3389/fendo.2022.963336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022] Open
Abstract
Reducing injection-site pain (ISP) in patients with chronic conditions such as growth hormone deficiency is a valuable strategy to improve patient compliance and therapeutic efficiency. Thus understanding different aspects of pain induction following subcutaneous injection of biotherapeutics and identifying the responsible factors are vital. Here we have discussed the effects of formulation's viscosity, concentration, osmolality, buffering agents, pH, and temperature as well as injection volume, dosing frequency, and different excipients on ISP following subcutaneous injection of commercially available recombinant human growth hormone products. Our literature review found limited available data on the effects of different components of parenteral rhGH products on ISP. This may be due to high cost associated with conducting various clinical trials to assess each excipient in the formulation or to determine the complex interactions of different components and its impact on ISP. Recently, conducting molecular dynamics simulation studies before formulation design has been recommended as an alternative and less-expensive approach. On the other hand, the observed inconsistencies in the available data is mainly due to different pain measurement approaches used in each study. Moreover, it is difficult to translate data obtained from animal studies to human subjects. Despite all these limitations, our investigation showed that components of parenteral rhGH products can significantly contribute to ISP. We suggest further investigation is required for development of long acting, buffer-free, preservative-free formulations. Besides, various excipients are currently being investigated for reducing ISP which can be used as alternatives for common buffers, surfactants or preservatives in designing future rhGH formulations.
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Affiliation(s)
- Bita Taghizadeh
- Department of Medical Biotechnology, School of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Mahmoud Reza Jaafari
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
- Department of Pharmaceutical Nanotechnology, School of Pharmacy, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Nosratollah Zarghami
- Department of Medical Biotechnology, School of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
- Department of Clinical Biochemistry and Laboratory Medicine, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
- *Correspondence: Nosratollah Zarghami,
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Negron C, Fang J, McPherson MJ, Stine WB, McCluskey AJ. Separating clinical antibodies from repertoire antibodies, a path to in silico developability assessment. MAbs 2022; 14:2080628. [PMID: 35771588 PMCID: PMC9255221 DOI: 10.1080/19420862.2022.2080628] [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: 11/22/2022] Open
Abstract
Approaches for antibody discovery have seen substantial improvement and success in recent years. Yet, advancing antibodies into the clinic remains difficult because therapeutic developability concerns are challenging to predict. We developed a computational model to simplify antibody developability assessment and enable accelerated early-stage screening. To this end, we quantified the ability of hundreds of sequence- and structure-based descriptors to differentiate clinical antibodies that have undergone rigorous screening and characterization for drug-like properties from antibodies in the human repertoire that are not natively paired. This analysis identified 144 descriptors capable of distinguishing clinical from repertoire antibodies. Five descriptors were selected and combined based on performance and orthogonality into a single model referred to as the Therapeutic Antibody Developability Analysis (TA-DA). On a hold-out test set, this tool separated clinical antibodies from repertoire antibodies with an AUC = 0.8, demonstrating the ability to identify developability attributes unique to clinical antibodies. Based on our results, the TA-DA score may serve as an approach for selecting lead antibodies for further development. Abbreviations: Affinity-Capture Self-Interaction Nanoparticle Spectroscopy (AC-SINS), Area Under the Curve (AUC), Complementary-Determining Region (CDR), Clinical-Stage Therapeutics (CST), Framework (FR), Monoclonal Antibodies (mAbs), Observed Antibody Space (OAS), Receiver Operating Characteristic (ROC), Size-Exclusion Chromatography (SEC), Structural Aggregation Propensity (SAP), Therapeutic Antibody Developability Analysis (TA-DA), Therapeutic Antibody Profiler (TAP), Therapeutic Structural Antibody Database (Thera-SAbDab), Variable Heavy (VH), Variable Light (VL).
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Affiliation(s)
| | - Joyce Fang
- AbbVie Bioresearch Center, Worcester, MA, USA
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