Redica Systems has been assisting pharmaceutical companies in determining GMP quality risks at their manufacturing sites, and with AI, it has a relatively new addition to its toolbox.
As part of its AAPS PharmSci 360 2024 coverage, Pharmaceutical Technology® interviewed Jerry Chapman, senior good manufacturing practice (GMP) quality expert with Redica Systems, about his presentation at the conference, “Using AI to Evaluate GMP Health of Drug Manufacturing Sites,” to be delivered on Tuesday, Oct. 22, 2024. Chapman discussed the importance of determining GMP quality risks for any company, and how artificial intelligence (AI) is now assisting Redica in facilitating these evaluations.
“What we have done is, we've built something called an ontology, and the ontology is really, for lack of a better analogy, it’s like a dictionary of terms and what they mean with our industry,” Chapman says in the interview. “So, if you went to ChatGPT and asked it about an API, it would think you were talking about an application program interface. In the ... wide world, if you will, that that's what people would equate that to. In the pharmaceutical industry, it is an active pharmaceutical ingredient, right? So, we have to spend a fair amount of time training the AI on our ontology and being able to train it so that it can recognize those terms and be able to ferret them out in inspection documents.”
Click the above video to watch the full interview.
Chapman’s presentation will be at 10:30 a.m. MT on the 22nd, in Room 155E. AAPS PharmSci 360 is being held from Oct. 20–23, 2024 in Salt Lake City, Utah.
A Novel, Enhanced, and Sustainable Approach to Audit Trail Review
July 4th 2025Eli Lilly and Company developed an innovative and sustainable approach to audit trail review (ATR) aimed at reducing the ATR burden while adhering to regulatory expectations and data integrity (DI) principles. The process has transformed employees' understanding of ATR and complemented the DI by design approach, leading to better system designs that meet expected controls and reduce non-value-added data reviews.