Automated Quality Management in Life Sciences Supply Chain: Combining SAP QM with GenAI for Regulatory Compliance

Abstract

The project focuses on the possibility 
of applying Generative AI (GenAI) to SAP 
Quality Management (QM) advancing quality 
management in the life sciences supply chain. 
SAP QM is focused on guaranteeing compliance 
with the company’s regulated activities as well as 
its performance, while the use of GenAI 
incorporates the benefits of analytical as well as 
automotive approach. The framework tackles 
problems of conventional models, optimizes the 
decision process, and guarantees adaptability. 
Johnson & Johnson, AstraZeneca, and Sanofi are 
emerged as reference cases that can illustrate their 
practical use. Issues at stake include costs of 
setting up implementation processes, security of 
data processing, and information resistance to 
change. Based on that, the recommendations 
concern training activities, further integration, 
and constant improvement. The issues with the 
application of conventional quality management 
are described in this research by using life 
sciences as the field of study that may benefit 
from automation and prognosis analytics. The 
integration of SAP QM and GenAI demonstrates 
better compliance, work efficiency and even 
predictive traits