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mAbs Volume 13, 2021 - Issue 1
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Review

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

Emily K. Makowskia Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, USA;b Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USAORCID Iconhttps://orcid.org/0000-0002-9709-9873View further author information
ORCID Icon,
Lina Wub Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA;c Department of Chemical EngineeringView further author information
,
Priyanka Guptad Department of Biochemistry and Biophysics, Rensselaer Polytechnic Institute, Troy, NY, USA;e Biotherapeutics Discovery Department, Boehringer Ingelheim, Ridgefield, CT, USAORCID Iconhttps://orcid.org/0000-0001-6483-3069View further author information
ORCID Icon &
Peter M. Tessiera Department of Pharmaceutical Sciences, University of Michigan, Ann Arbor, MI, USA;b Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA;c Department of Chemical Engineering;f Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USACorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-3220-007XView further author information
ORCID Icon
Article: 1895540 | Received 10 Nov 2020, Accepted 22 Feb 2021, Published online: 27 Jul 2021

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Paul Arras, Han Byul Yoo, Lukas Pekar, Christian Schröter, Thomas Clarke, Simon Krah, Daniel Klewinghaus, Vanessa Siegmund, Andreas Evers & Stefan Zielonka. (2023) A library approach for the de novo high-throughput isolation of humanized VHH domains with favorable developability properties following camelid immunization. mAbs 15:1.
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Hristo L. Svilenov, Paolo Arosio, Tim Menzen, Peter Tessier & Pietro Sormanni. (2023) Approaches to expand the conventional toolbox for discovery and selection of antibodies with drug-like physicochemical properties. mAbs 15:1.
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Yumin Wu & Liangzhu Feng. (2023) Biomaterials-assisted construction of neoantigen vaccines for personalized cancer immunotherapy. Expert Opinion on Drug Delivery 20:3, pages 323-333.
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Emily K. Makowski, Hongwei Chen, Matthew Lambert, Eric M. Bennett, Nicole S. Eschmann, Yulei Zhang, Jennifer M. Zupancic, Alec A. Desai, Matthew D. Smith, Wenjia Lou, Amendra Fernando, Timothy Tully, Christopher J. Gallo, Laura Lin & Peter M. Tessier. (2022) Reduction of therapeutic antibody self-association using yeast-display selections and machine learning. mAbs 14:1.
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Christopher Negron, Joyce Fang, Michael J. McPherson, W. Blaine Stine$suffix/text()$suffix/text() & Andrew J. McCluskey. (2022) Separating clinical antibodies from repertoire antibodies, a path to in silico developability assessment. mAbs 14:1.
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Shihao Hu, Amita Datta-Mannan & David Z. D’Argenio. (2022) Physiologically Based Modeling to Predict Monoclonal Antibody Pharmacokinetics in Humans from in vitro Physiochemical Properties. mAbs 14:1.
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Pin-Kuang Lai, Austin Gallegos, Neil Mody, Hasige A. Sathish & Bernhardt L. Trout. (2022) Machine learning prediction of antibody aggregation and viscosity for high concentration formulation development of protein therapeutics. mAbs 14:1.
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Articles from other publishers (8)

Tong Li, Yupeng Li, Xiaoyi Zhu, Yao He, Yanling Wu, Tianlei Ying & Zhi Xie. (2023) Artificial intelligence in cancer immunotherapy: Applications in neoantigen recognition, antibody design and immunotherapy response prediction. Seminars in Cancer Biology 91, pages 50-69.
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Markos Trikeriotis, Sergey Akbulatov, Umberto Esposito, Athanasios Anastasiou & Oksana I. Leszczyszyn. (2022) Analytical Workflows to Unlock Predictive Power in Biotherapeutic Developability. Pharmaceutical Research 40:2, pages 487-500.
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Takahiro Hayashi, Yuji O. Kamatari & Masayuki Oda. (2022) Evaluation of multi-specificity of antibody G2 using its single-chain Fv and its covalently linked antigen peptides. Biophysical Chemistry 290, pages 106893.
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Jiangyan Feng, Min Jiang, James Shih & Qing Chai. (2022) Antibody apparent solubility prediction from sequence by transfer learning. iScience 25:10, pages 105173.
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Paul R. Sargunas & Jamie B. Spangler. (2022) Joined at the hip: The role of light chain complementarity determining region 2 in antibody self-association. Proceedings of the National Academy of Sciences 119:28.
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Emily K. Makowski, Patrick C. Kinnunen, Jie Huang, Lina Wu, Matthew D. Smith, Tiexin Wang, Alec A. Desai, Craig N. Streu, Yulei Zhang, Jennifer M. Zupancic, John S. Schardt, Jennifer J. Linderman & Peter M. Tessier. (2022) Co-optimization of therapeutic antibody affinity and specificity using machine learning models that generalize to novel mutational space. Nature Communications 13:1.
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Emily K Makowski, John S Schardt & Peter M Tessier. (2022) Improving antibody drug development using bionanotechnology. Current Opinion in Biotechnology 74, pages 137-145.
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John S. Schardt, Harkamal S. Jhajj, Ryen L. O'Meara, Timon S. Lwo, Matthew D. Smith & Peter M. Tessier. (2022) Agonist antibody discovery: Experimental, computational, and rational engineering approaches. Drug Discovery Today 27:1, pages 31-48.
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