Attending this event?
Back To Schedule
Wednesday, June 22 • 1:45pm - 2:45pm
#341: New Approaches to Site Selection in Clinical Trials

Sign up or log in to save this to your schedule, view media, leave feedback and see who's attending!

Component Type: Session
Level: Intermediate
CE: ACPE 1.00 Knowledge UAN: 0286-0000-22-621-L04-P ; CME 1.00; RN 1.00

In the drug development space, there is a growing expectation demanding pharmaceutical companies generate more evidence by conducting increased number of clinical trials due to increased regulatory requirements ensuring patient safety. One of the biggest speed limiting steps in clinical trials, is patient enrollment. Selecting the right sites would potentially accelerate the overall enrollment and ultimately the clinical development timeline. We can identify and prioritize sites for clinical trials by predicting key metrics that define a site’s overall performance, including, site start-up time and enrollment rate. The traditional way of identifying sites to participate in a study could be a combination of referral, working relationship or data-driven approach like identifying sites that have had prior experience conducting trials in similar indication and analyzing their historical average performance. While field knowledge is irreplaceable, we can better leverage the data using advanced analytical techniques like machine learning and feasibility studies influencing data-driven decision making.

Learning Objectives

Describe various solutions to identify high-performing countries and sites for clinical trials; Discuss various factors influencing site performance in clinical trials; Describe how to make data-driven decision in site selection for clinical trials.


Dinesh Kumar Subbarayalu, MS


A Machine Learning-Based Approach to Identify Highly Efficient Sites to Prioritize for Clinical Trial
Dinesh Kumar Subbarayalu, MS

Streamlining the Feasibility Process to Enhance Site-Sponsor Collaboration and Accelerate Cycle Times
Kavitha Lokesh


Kavitha Lokesh

Vice President, Head of LS R&D Delivery and Products and Platforms, Cognizant Technology Solutions, United States
Kavitha Lokesh is VP, Head of LS R&D Delivery and Products & Platforms. She is a global business leader with a track record of delivering mission-critical products and solutions. Kavitha has over 25 years of IT industry experience and has held multiple leadership roles at Cognizant... Read More →
avatar for Dinesh Kumar Subbarayalu

Dinesh Kumar Subbarayalu

Data Scientist, AbbVie, Inc., United States
Dinesh Kumar is a data enthusiast who is currently working as a Data Scientist at AbbVie, North Chicago. Dinesh has a Masters in Business Analtics from the University of Illinois. Dinesh has been at AbbVie for 4 years as part of Clinical Analytics team supporting selection, activation... Read More →

Wednesday June 22, 2022 1:45pm - 2:45pm CDT
Room 175 McCormick Place 2301 South Indiana Avenue Gate 40 Chicago, IL 60616