AI Case Study
Bayer aims to spot drug-associated side effects earlier with the use of machine learning, RPA and natural language processing
Bayer has partnered with Genpact to leverage artificial intelligence for its effort to process adverse events and spot drug-associated side effects earlier. The vendor is providing a solution that is able to optimise Bayer's pharmacovigilinace practice for consumer health and pharmaceuticals. The Pharmacovigilance Artificial Intelligence (PVAI) solution works by automatically drawing AE data from unstructured and semi-structured source documents with the use of optical character recognition, robotic process automation, natural language processing, and machine learning.
Industry
Healthcare
Healthcare Providers And Services
Project Overview
"Bayer is seeking to expedite it’s patient safety data monitoring through artificial intelligence (AI) in an initiative that it hope will enable any drug-associated side effects to be spotted earlier.
The German-based pharmaceutical has partnered with Genpact, a professional services company for this work through signing an agreement for several years for its pharmacovigilance AI products.
According to Bayer, such efforts will help in reinforcing its commitment to patient safety.
Bayer’s Global Head of pharmacovigilinace for consumer health and pharmaceuticals said: “With Genpact, we have found a partner whose innovative capabilities in the area of applying advanced AI and machine learning technologies to pharmacovigilance provide us with an opportunity to further increase the efficiency of our pharmacovigilance operating model and case processing, while maintaining our high quality and compliance standards.”
Genpact asserted that its PVAI solution that draws severe event data from various source documents in an automated manner, has participated, and won, several highly competitive proof-of-concept exercises undertaken by big pharmaceutical firms.
Genpact’s Business Leader of Life Sciences and Healthcare Balkrishan ‘BK’ Kalra said: “We expect safety issues can be identified more rapidly, and resources can be freed up to focus on advanced and effective risk minimization measures"."
Reported Results
Proof Of Concept; results not yet available
Technology
"Genpact’s PVAI offering brings together and integrates optical character recognition, robotic process automation, natural language processing, and machine learning technologies to automatically extract and code AE data from unstructured and semi-structured source documents – eliminating manual workflow, saving pharmaceutical companies significant time and resources, and helping to establish a scalable PV operating model. Most importantly, the solution continuously builds predictive insights as more and more AE goes through it over time." (Genpact)
Function
R And D
Core Research And Development
Background
"Bayer’s partnership with Genpact introduces a new ground for the use of AI by pharmaceutical companies."
Benefits
Data
"AE data from unstructured and semi-structured source documents" (Genpact)