Digital Twins and the Future of Pharma Validation

In part 1 of a 2-part interview, and as a part of PDA Week 2026, Susan Schniepp, Regulatory Compliance Associates Inc., discusses the evolving role of technology in the manufacturing landscape. A central focus of her discussion is the implementation of digital twins, which she describes as systems that mimic live operators. Schniepp explains that when these digital models diverge from physical operations, it prompts corrective actions or new validations to bring the two back into alignment. A primary benefit of this technology is the ability to identify data integrity hotspots, areas where violations might occur due to how documents are handled.

The shift toward AI represents a significant change from traditional paper or middle electronic systems where humans perform every approval. With machine learning, the system can now perform much of the data collection and verification itself, allowing the machine to take on a larger role. However, this shift raises critical questions regarding where human oversight is most efficient. Schniepp suggests that discrepancies between human opinion and machine data should be treated as deviations requiring a formal investigation. She notes, "The traditional model that we have is to do an investigation on it."

Looking ahead, Schniepp acknowledges the rapid pace of machine learning and its potential to surpass human capability in data processing. She observes, "At some point the machine ultimately is probably more capable at looking at some of these things as it learns, it’s gonna absorb so much more data and information and learn at a faster pace than the human can, that at some point the human's gonna be, and this is where I get concerned, the human will be out of the loop." For now, she advocates for human precedence, suggesting that because the technology is so new, humans should investigate the digital twin during conflicts to determine the root cause of any discrepancy.