Author

Akashdeep Singh Virk

Rensselaer Polytechnic InstituteORCID 0000-0002-9157-4637Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Biophysics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Sabitoj Singh VirkiD· 2 shared Collin Taylor· 1 shared Connor Smith· 1 shared Deepika Venkataramani· 1 shared Joshin George· 1 shared Maria Calderon Vaca· 1 shared Matthew Matusewicz· 1 shared Maureen CramesiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Sabitoj Singh VirkORCID

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2 papers

Recent·Most cited

Monoclonal Antibody Developability from Early Assay Panels: Machine Learning for Formulation and Pharmacokinetic Risk

Sabitoj Singh Virk, Akashdeep Singh Virk

This paper introduces ACeT, a machine learning framework that predicts formulation and pharmacokinetic risks of monoclonal antibodies using early assay panels, achieving high predictive accuracy and interpretability.

Machine Learning Health · Oct 3, 2026Peer-reviewedBioinformatics

Temperature and Excipient Mediated Modulation of Monoclonal Antibody Interactions Revealed by kD, Rheology, and Raman Spectroscopy

Olivia Noelle Eskens, Sabitoj Singh Virk, Akashdeep Singh Virk, Deepika Venkataramani, Maureen Crames, Maria Calderon Vaca, Matthew Matusewicz, Connor Smith, Joshin George, Collin Taylor, Michael S. Marlow, Samiul Amin

This study investigates how temperature and excipients modulate monoclonal antibody interactions using kD, rheology, and Raman spectroscopy, revealing strategies to improve formulation stability.

mAbs · Jun 25, 2025Peer-reviewedBiophysics