On January 21, 2026 Soley Therapeutics reported the publication of a peer-reviewed study in Scientific Reports describing a new approach to understanding how living cells react to drug molecules, inverting traditional target-based drug discovery methods. The study shows that dynamic live-cell stress responses to drugs over time encode mechanistic information about a cell’s trajectory to survive, adapt, or die – information that is largely missed by traditional snapshot-based assays. This work establishes the scientific foundation for Soley’s platform, which enables a novel, proprietary live-cell approach to drug discovery based on how cells sense and respond to stress.
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"This work reflects more than a decade of foundational research into how cells sense and respond to drugs and other external signals," said Yerem Yeghiazarians, M.D., Co-founder and CEO of Soley Therapeutics. "By focusing on the dynamic flow of information inside the cell, rather than static endpoints, we can delineate biology that conventional discovery methods often miss. Live Cell Dynamics is one piece of a much larger platform that Soley has created to translate whole-cell behavior into medicines. Our growing pipeline demonstrates the real-world impact of this pathbreaking science in moving drug hits to clinical candidates faster and at lower cost than traditional approaches."
Using live, label-free cell imaging, which follows living cells over time without dyes or reporter tags, the study establishes a novel approach to extract information that describes cellular stress responses by using proprietary self-supervised machine learning methods. The authors show that subtle information extracted from cells indicates dynamic responses to a drug, providing insight into a drug’s real mechanism across multiple dimensions, including toxicity and selectivity, even when compounds have similar targets and/or produce similar outcomes such as cell death. Incorporating temporal and dose-dependent information improves detection of a drug’s biological activity and mechanism-of-action, highlighting the limitations of binary readouts and morphology-only profiling approaches, particularly in complex cellular disease states.
"Through this research, our goal was to extract dynamic information from live cells for drug discovery and development purposes," said Kurosh Ameri, Ph.D., Co-founder and Chief Scientific Officer of Soley Therapeutics. "We have now shown that live cells sense drugs dynamically and convey different mechanistic information, which is dose- and time-dependent. Our proprietary machine learning methods can extract information about drugs directly from live, unstained images. This ability to measure and interpret detailed information directly from live cells in a scalable and reproducible way demonstrates a significant advance in drug discovery. This comprehensive approach provides a more accurate understanding of complex cellular responses and a drug’s true mechanism-of-action, moving beyond single endpoint and time point assays."
These experimental principles form the scientific underpinnings of Soley’s proprietary platform, which scales this biology-first approach using automation and AI to drive drug discovery across oncology and other complex diseases. The publication adds to Soley’s growing body of peer-reviewed research supporting its differentiated approach as the company advances multiple internally discovered programs toward the clinic.
(Press release, Soley Therapeutics, JAN 21, 2026, View Source [SID1234662135])