Applying Artificial Intelligence, Machine Language, Natural Language Processing and Predictive Models in Clinical Trials to Deliver Value to Multiple Stakeholders
Offering Leader, Clinical Trial Transformation
IBM Watson Health, United States
With the focus on acceleration of drug development, the ever increasing complexity of clinical trials is driving companies to look for possibilities in leveraging artificial intelligence/machine learning and predictive analytics. Clinical trial protocols are written by and for humans, often with ambiguity that presents challenges to machine reading and understanding. Patient data and lack of uniform data standards are also challenges to overcome for artificial intelligence machines. This session will cover how the combination of machine learning methods and big data technology leads to high performance patient outcome optimization and clinical trial solutions that deliver value to multiple stakeholders.
Learning Objective : Recognize machine learning and the use of these techniques in the development of predictive models. Discuss the potential role for these techniques in improving and informing shared decision making.
Application of Artificial intelligence and Machine Learning in Clinical Trials
Sunil Agarwal, MS
Associate Vice President and Practice Lead, Pharma R&D
HCL America Inc., United States
Why Big Data and Machine Learning will Change the Paradigm for Demonstrating and Delivering Value to Multiple Stakeholders
Costas Boussios, PhD
Vice President, Data Science
OM1, United States