CASE STUDY

A Generative AI Chatbot Streamlines Clinical Trial Operations for a Pharma Organization

industry_pharmaceutical

Business Case

A pharma client was facing challenges in its clinical research operations. Their Research Pharmacists (RPs) were handling over 500 active clinical studies, and each of them were spending a significant amount of time in handling queries from the study teams regarding the common Investigational Product (IP). Most of these queries were repetitive and this was causing significant delays in the clinical trial progression. 

The client wanted a solution which could handle the queries on behalf of the RPs, allowing them to invest valuable time in critical activities pertaining to the study. At the same time, the solution should also help in bridging the gap between IP manual training and the study teams, which could help in effectively reducing the repetitive queries.

Our Solution

Our solution architects analyzed the situation and proposed implementing a Gen AI-driven chatbot system aiming at

  • Providing the study teams with timely responses for their queries
  • Reducing the dependency on the RPs unless an escalation is required
  • Enhanced RP performance, due to time saved in answering repetitive questions

Team i2e developed an advanced chatbot leveraging Amazon SageMaker’s generative AI capabilities along with a wrapper around Kore.ai to build a user friendly chatbot interface capable of answering queries pertaining to Investigational Product (IP). 

i2e team utilized sophisticated prompt engineering capabilities which resulted in enhanced performance and efficiency in delivering precise responses. The backend web platform was built to store and process the vast IP manual documents and direct user’s inputs to relevant responses and escalations. The team also built a notification system which triggers emails to the respective RPs in case of out-of-the-manual questions or escalations. 

The Clinical Research Coordinator wanted to plug the knowledge gaps resulting in repetitive questions directed towards the RPs. With the chatbot recording the questions and their answers, it became a central repository to identify knowledge gaps and bring about changes in the IP manual and the training modules

Benefits

  • The RPs could direct their efforts towards critical activities
  • Quick and enhanced query resolution, minimizing delays
  • Reduced risk of misinformation or outdated practices being applied at clinical trial sites.
  • Improved IP manual training and patient enrollment