Joga Gobburu: Leveraging Scientific ML to Revolutionize Predictive Healthcare Analytics

Scientific modeling has transformed healthcare phenomenally. There are several problems in healthcare that are not solved yet owing to lack of full understanding of the underlying mechanism.  More recently, machine learning has come into prominence. Several problems are shown to be addressed by machine learning. However, the limitation is its indifference to biology and natural principles. A novel hybrid approach called Scientific ML which leverages the best of both approaches will be presented. The potential problems that this revolutionary paradigm can help with will be discussed.  

A renowned scientist in the area of quantitative disease models and their application to decisions, Joga heads the interdisciplinary team at Pumas-AI and is instrumental in shaping the company’s vision and roadmap. He is a Professor with the School of Pharmacy and the School of Medicine, University of Maryland, Baltimore and has held various positions at the US FDA between 1999 and 2011.

During his illustrious tenure at the US FDA, Joga oversaw the review of thousands of Investigational New Drug Applications (INDs), over 250 New Drug and Biological Licensing Applications, numerous FDA guidances and policies and was part of the committee responsible for the 21st Review Process. He led both the formation of the Division of Pharmacometrics and a Pharmacometrics Fellowship Program at the FDA. Besides a number of FDA awards, Joga received the Outstanding Leadership Award from the American Conference on Pharmacometrics (2008), the Tanabe Young Investigator Award from the American College of Clinical Pharmacology (ACCP) (2008) and the Sheiner-Beal Pharmacometrics Award from the American Society of Clinical Pharmacology and Therapeutics in 2019.

Joga is on the editorial boards of several journals and a Fellow of ACCP, AAPS and International Society of Pharmacometrics. He has published over 100 papers and book chapters.