Cytel is excited to invite you to join us in our next presentation in the "New Horizons Webinar Series", which will introduce you to the latest innovations in statistical trial design. Cytel’s Alind Gupta, will be presenting case studies from applying machine learning for predictive analysis and evidence generation from randomized clinical trials and real-world data.
The use of AI in clinical research promises more effective decision-making and improved patient outcomes, but its successful adoption requires a rigorous assessment of regulatory implications, transparency and added value over existing methods of analysis.
In this talk, Alind will discuss case studies from applying machine learning for predictive analysis and evidence generation from randomized clinical trials and real-world data. He will also introduce recent ongoing work at Cytel in applying methods from causal analysis and reinforcement learning in the context of comparative effectiveness research and dynamic treatment regimes.
The focus of this webinar will be on high-level concepts rather than methodological
About the Speaker
Alind Gupta is a senior data scientist at Cytel, focusing on probabilistic graphical models and Bayesian inference. His current work focuses on the use of Bayesian networks and Markov models for modelling heterogeneity in response to cancer immunotherapy and for long-term survival prediction using clinical trial and real-world data. Alind has a PhD from the University of Toronto studying genetics of rare diseases.