Artificial Intelligence (AI) is increasingly being applied across all stages of the pharma value chain. This leads to various regulatory challenges, such as algorithmic transparency, AI failure risks, and the impact on drug development and patients' overall health. The exclusive roundtable will explore the challenges and learnings in the adoption of explainable AI and the roadmap for good machine learning practices (GMLP) in life sciences.
Explainable AI helps clinical practitioners interpret black-box models and their decision-making process. It verifies the reason a machine learning model took a particular decision.
TCS’ Life Sciences Advisory Group invites you to this exclusive roundtable as we explore and address:
- Current maturity, challenges, and learnings in the adoption of explainable AI processes, methods, and techniques
- Roadmap for adopting good machine learning practices (GMLP) in the life sciences industry
- The right way to leverage explainable AI techniques to derive new and vital insights
- Prasanna Rao, Head, Artificial Intelligence and Data Science, Pfizer
- Andrew Miles, EMEA Head of Healthcare and Life Sciences, Google Cloud
- Mehrnoosh Sameki, Responsible AI Tools Tech Lead, Microsoft, Adjunct Assistant Professor, Boston University
- Sally Embrey, Field CTO, Healthcare, DataRobot
- Sanjeev Sachdeva, Business Group Chief Technology Officer and Head Advisory Services, Life Sciences, TCS
- Kamlesh Mhashilkar, Head, Data and Analytics Practice, Analytics and Insights, TCS