Peer-Reviewed Publication
Adv Sci (Weinh)2026;e75947.June 11, 2026Journal Article
Lessons From Drug Discovery for Cryoprotective Agent Design: An AI-Oriented Perspective.
Dominika Wilczok1,2, Jesús Valdés-Hernández3, Varinia Bernales3,4,5, Alán Aspuru-Guzik3,4,5,6,7,8,9,10,11, Alex Zhavoronkov12,13,14
1Duke University, Durham, North Carolina, USA.
2Duke Kunshan University, Kunshan, Jiangsu, China.
3Department of Chemistry, University of Toronto, Toronto, Ontario, Canada.
4Acceleration Consortium, Toronto, Ontario, Canada.
5Department of Computer Science, University of Toronto, Toronto, Ontario, Canada.
6Vector Institute for Artificial Intelligence, Schwartz Reisman Innovation Campus, Toronto, Ontario, Canada.
7Department of Chemical Engineering & Applied Chemistry, University of Toronto, Toronto, Ontario, Canada.
8Department of Materials Science & Engineering, University of Toronto, Toronto, Ontario, Canada.
9Institute of Medical Science, Toronto, Ontario, Canada.
10NVIDIA, Toronto, Ontario, Canada.
11Canadian Institute for Advanced Research (CIFAR), Toronto, Ontario, Canada.
12Insilico Medicine US Inc., Cambridge, Massachusetts, USA.
13Insilico Medicine AI Ltd, Abu Dhabi, UAE.
14Insilico Medicine Hong Kong Ltd, Hong Kong SAR, China.
Abstract
Cryopreservation is the storage of biological materials like cells, tissues, or even organs at cryogenic temperatures. This technology is a key enabler for biobanking, reproductive medicine, and cell therapy, and is positioned as a vital part of the future of transplantation. Successful cryopreservation relies on cryoprotective agents (CPAs) that protect biological structures from ice-induced dama…
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