Drug discovery is increasingly multimodal, spanning small molecules, antibodies, RNA-based therapies, cell and gene therapies, and novel combinations like ADCs. Each modality generates unique biological questions and massive datasets, creating both opportunity and complexity. Making sense of this data is now central to advancing discovery.
A concrete example comes from the work of Alex Zagajewski and the team at Novo Nordisk Research Centre Oxford, a high-throughput cellular differentiation screening platform was developed on human adipocytes, integrating single-gene knockouts, time-course imaging, and multi-omic analyses. By applying AI/ML and mechanistic modeling, novel regulators of adipogenesis and potential therapeutic targets were identified—demonstrating how computational integration can unlock insights from complex biological data.
Zev Wisotsky
PhD, Senior Principal Marketing Manager, Biologics Solutions, Revvity Signals
Zev Wisotsky is a Senior Principal Marketing Manager for Biologics Solutions at Revvity Signals. His scientific training and research background include neuroscience, biochemistry, molecular biology and drug discovery. He has spent almost 10 years in software in go-to-market teams across industries with a heavy focus on biopharma/biotech R&D.
Alexander Zagajewski
AI/ML Research Scientist At Novo Nordisk
Alexander Zagajewski is a AI Research Scientist who specialized in computer vision, deep learning, computational biology, and early-stage drug discovery. At Novo Nordisk, Alexander led the development of AI/ML solutions for complex biomedical data, collaborating with wet-lab and engineering teams to drive innovation. Also served as a Visiting Scientist at the University of Oxford, contributing to biomedical AI research. Doctoral research at Oxford focused on a novel diagnostic assay for antimicrobial resistance detection using deep learning and microscopy, developed in collaboration with NHS clinicians. Previous roles at EMBL and the University of St Andrews advanced imaging technologies with industry partners, while teaching and mentoring positions at Oxford strengthened expertise in scientific computing and biochemistry education.