Summary
Salil Pendse is a computational biologist and Principal Consultant with eight years of experience building quantitative systems pharmacology and multi-omics workflows that bridge literature, in vitro assays, and mechanistic models. He has progressed from hands-on research roles at The Hamner and University of Utah to leadership positions at ScitoVation, Nuventra, Allucent, and now SysDHI, designing PBPK and intracellular signaling models to inform drug discovery decisions. Skilled in R, Python, and custom visualization techniques, he extracts actionable insights from large transcriptomics and ChIP datasets and creates reproducible analysis pipelines. Known for translating complex biological data into decision-ready models, he combines academic rigor with industry pragmatism and a track record of enabling cross-functional teams to leverage computational approaches. An early background building cortical neuron network models and imaging algorithms gives him an uncommon blend of systems neuroscience and pharmacology perspectives.
8 years of coding experience
13 years of employment as a software developer
The University of Utah
Bachelor of Engineering (B.E.) Bioengineering and Biomedical Engineering, Bachelor of Engineering (B.E.) Bioengineering and Biomedical Engineering at University of Mumbai
English, German, Marathi, Hindi