Author

Rich Cohen

Ginkgo Bioworks, Inc. (United States)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 3

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:deep learning· 2 Research Focus:drug response / drug discovery· 2 Assay:proteomics· 2 Research Focus:database / resource· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1

Frequent Co-Authors

Aanal BhattiD· 3 shared Alexander SmithiD· 3 shared Ammar ArsiwalaiD· 3 shared David W. BorhaniiD· 3 shared Joshua MolleriD· 3 shared Lucía Daniela GrippoiD· 3 shared Peter M. TessieriD· 3 shared Rebecca Bhatt· 3 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersBiophysics

Aanal BhattORCID

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Author profile →

3 papers

Recent·Most cited

Predicting VHH-Fc Developability from Large-Scale IgG Data

Joshua Moller, Seth Ritter, Laura M. Rand, Alexander Smith, Yolaine Pierre, Tim Bloomingdale, Blake Harris, Sai Karthick, Lucía Daniela Grippo, Aanal Bhatt, Jay Patel, Xiang Ao, Rebecca Bhatt, Rich Cohen, David W. Borhani, , Ammar Arsiwala

The paper introduces a dataset of VHH-Fc antibodies and shows that IgG-trained models outperform VHH-Fc-specific models in predicting developability properties.

bioRxiv · Aug 21, 2026 · PreprintBiophysics

Decoding Bispecific Antibody Developability: Design Rules and Predictive Models from a 160-Member Library

Seth Ritter, Laura M. Rand, Sai Karthick, Tim Bloomingdale, Alexander Smith, Xiang Ao, Yolaine Pierre, Blake Harris, Joshua Moller, Aanal Bhatt, Rebecca Bhatt, Jay Schwartz, Lucía Daniela Grippo, Rich Cohen, David W. Borhani, , Ammar Arsiwala

This paper analyzes 160 bispecific antibodies and their parental arms to identify developability inheritance patterns and predictive models for bispecific antibody design.

bioRxiv · Jun 19, 2026 · PreprintBiophysics

A high-throughput platform for biophysical antibody developability assessment to enable AI/ML model training

Ammar Arsiwala, Rebecca Bhatt, Lood van Niekerk, Porfirio Quintero-Cadena, Xiang Ao, Adam Rosenbaum, Aanal Bhatt, Alexander Smith, Yaoyu Yang, KC Anderson, Lucía Daniela Grippo, Xing Cao, Rich Cohen, Jay Patel, Joshua Moller, , David W. Borhani

The paper introduces a high-throughput platform to generate large datasets for training machine learning models to predict antibody developability properties.

mAbs · Dec 2, 2025Peer-reviewedBiophysics