Matt Docherty
Background and experience
Matt is a principal focused on developing and applying advanced data science and AI solutions for the life sciences industry. He leads ZS’s AI expertise center, with an emphasis on AI innovation, and works closely across pharmaceutical research and development, including leading discovery AI in collaboration with ZS’s discovery practice area.
Matt has led the development of multiple client solutions and ZS offerings in the semantic AI space as natural language processing approaches have evolved from traditional methods to large language models and agentic applications. He currently leads ZS’s AI content authoring initiative and works with clients on the development of R&D document authoring systems. His work includes a strong focus on knowledge graphs and their integration with generative AI.
Matt has worked extensively on patient modeling applications in clinical development, supporting use cases that range from program design to trial recruitment. He helps lead ZS’s in silico work and digital twin development and has supported real‑world evidence efforts focused on diagnosis and progression prediction, outcome analysis, patient risk modeling and unmet need discovery. His work on NASH prediction with Novartis has been published in JAMIA and Scientific Reports.
Earlier in his career, Matt worked on the commercial side of the business, developing AI and advanced analytics use cases and leading the development of NLP tools for market research.
Education
B.S. in industrial and systems engineering, Georgia Institute of Technology