Balancing In-Silico Retention Predictions with Experimental Chromatography Confidence

Pharmaceutical development is increasingly focused on faster, more efficient analytical approaches that reduce development time, cost, and resource use while improving overall sustainability in both R&D and commercial testing. The long-term direction is toward highly automated, data-driven manufacturing systems with real-time quality monitoring that reduces dependence on traditional end-point testing. AI, automation, digital technologies, and predictive models are helping move the field beyond trial-and-error workflows by increasing accuracy and reducing consumption of materials and solvents. This includes substituting some ultrahigh performance liquid chromatography (UHPLC) methods with near-infrared spectroscopy (NIR), implementing non-animal alternatives for microbiological testing, and using in-silico models to predict dissolution behavior with reduced experimental workload. Together, these developments are transforming analytical laboratories by accelerating workflows, strengthening sustainability, and maintaining the robustness required for regulatory confidence.

As In‑silico tools like retention‑time prediction gain attention, Koen Vanhoutte from Johnson & Johnson Innovative Medicine discusses how chromatographers can use these tools effectively without losing confidence in experimental data.

View Additional Commentary by Koen Vanhoutte:
Beyond Trial-and-Error: Self-Optimizing LC Workflows
The Evolving Role of Chromatography in Model-Based Analytical Science

Koen Vanhoutte is an Executive Director in pharmaceutical research and development with more than 25 years of industrial experience in analytical chemistry. He holds a Ph.D. in chemistry from the University of Antwerp, with his early scientific training and core expertise rooted in liquid chromatography–mass spectrometry (LC‑MS) and chromatographic method development. Over the course of his career, he has built extensive experience in Chemistry, Manufacturing and Controls (CMC) across both early‑ and late‑stage pharmaceutical development. He currently leads the Synthetics Analytical Development organization within Johnson & Johnson Innovative Medicine, where he is responsible for defining and delivering analytical strategies across the full product lifecycle, from development through commercial manufacture. His scope includes method development, validation, technology transfer, clinical trial material release, and ICH stability testing for synthetic therapeutics. His involvement in biologics is focused specifically on microbiology‑based analytical methods, and he has extensive experience supporting global regulatory submissions and inspections, including interactions with FDA and EMA. Dr. Vanhoutte is passionate about leading and developing global teams and fostering scientific excellence through people development. He is strongly committed to applying rigorous analytical science to advance therapeutic development, while staying closely connected to evolving analytical methodologies through pragmatic, applied innovation.