Elena Braconi, Jean-Philippe Krieger, Thomas Vent-Schmidt
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引用次数: 0
Abstract
Implementing a digital transformation in the Process Research and Development (PR&D) phase of an active ingredient offers significant opportunities to accelerate the journey from laboratory to manufacturing scale. Here, we report on three distinct initiatives undertaken at Syngenta to address concrete bottlenecks at different PR&D stages. First, Bayesian optimisation enabled efficient navigation of large reaction spaces with minimal experimental effort. Second, laboratory automation combined with multilinear calibration reduced hands-on time by ~85% and laid the foundation for autonomous closed-loop optimisation. Third, advances in Process Analytical Technology (PAT), including improved Multivariate Curve Resolution algorithms and modular Python-based pipelines, enabled real-time reaction monitoring in challenging industrial settings.
期刊介绍：
CHIMIA, a scientific journal for chemistry in the broadest sense covers the interests of a wide and diverse readership. Contributions from all fields of chemistry and related areas are considered for publication in the form of Review Articles and Notes. A characteristic feature of CHIMIA are the thematic issues, each devoted to an area of great current significance.
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