“The CPHI award recognizes how Self Driving Labs turns AI into practical value for pharmaceutical customers,” said Daniel Fricker, Head of the Drug Substance product line at Evonik. “By reaching robust process conditions faster and generating richer data from the outset, we can help customers shorten development timelines, use expert resources more effectively and make better-informed scale-up decisions.”
Developing manufacturing processes for APIs is becoming more complex as pipelines expand beyond small molecules to modalities such as peptides and oligonucleotides. Conventional process development relies on sequential, manual experiments that can take weeks, produce limited analytical data and depend heavily on expert judgement. Once a process has advanced into later clinical phases, changes can also become more difficult to implement without adding cost, time and risk.
Self Driving Labs digitalizes the workflow from experiment design and execution to data capture, analysis and decision-making. Continuous processing platforms, interchangeable and 3D-printed reactors, high-throughput experimentation, process analytical technology and automated chromatography are connected through a secure orchestration layer. A Bayesian optimization algorithm evaluates results in real time and selects the next experiment, while Evonik’s AI-based user interface “AIChemBuddy” gives scientists transparency, traceability and control.
Self Driving Labs helps customers develop robust processes faster, improve reproducibility and reduce the risk of costly late-stage changes. The technology is being deployed globally for new development projects and the optimization of existing products.
