DIA 2018 Global Annual Meeting

Component Type: Session
Level: Intermediate
CE: ACPE 1.25 Knowledge UAN: 0286-0000-18-541-L04-P; CME 1.25; IACET 1.25; RN 1.25

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 Objectives

Apply artificial intelligence, machine learning, natural language processing, and predictive analytics in clinical trial solutions to discover the nuances in clinical protocols and EHR data; Identify how these innovations enable pharma to achieve patient centricity, cost reduction, and improved productivity in the trial process

Chair

Prasanna Rao

Speaker

Application of Artificial intelligence and Machine Learning in Clinical Trials
Sunil Agarwal, MS

Why Big Data and Machine Learning will Change the Paradigm for Demonstrating and Delivering Value to Multiple Stakeholders
Costas Boussios, PhD