Hydrogenation Process Development in a Data-Rich Environment

A structured, three-stage workflow was developed to accelerate hydrogenation process development, facilitate rapid scale-up translation, and maximize process understanding through data-rich experimentation. The approach integrates high-throughput batch screening, intermediate-scale catalyst evaluation, and continuous flow implementation, while allowing flexible entry at any stage depending on prior process knowledge. In Stage I, a high-throughput robotic platform enables rapid screening of catalysts, solvents, and additives under pressurized conditions, supported by automated ultra-high-performance liquid chromatography (UHPLC) method development for efficient analysis. Stage II transitions to intermediate-scale reactors for catalyst optimization and safety assessment under controlled hydrogenation conditions. In Stage III, process knowledge is transferred to continuous flow, where reaction conditions are optimized and process control strategies, including automated experimentation, dynamic experiments, and model predictive control (MPC), are implemented. The workflow was demonstrated in a case study of a catalytic nitro reduction, and reaction conditions were successfully scaled up and translated from batch to continuous flow.

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Publication Details

Journal
Organic Process Research & Development
Published
2026-06-30
DOI
https://doi.org/10.1021/acs.oprd.6c00149
Primary Topic
Innovative Microfluidic and Catalytic Techniques Innovation
Type
article
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article

Hydrogenation Process Development in a Data-Rich Environment

Thomas Toupy, Giovanni Aprile, Charles D. Papageorgiou, Allan S. Myerson et al.
Organic Process Research & Development
Innovative Microfluidic and Catalytic Techniques Innovation
article

Hydrogenation Process Development in a Data-Rich Environment

Thomas Toupy, Giovanni Aprile, Charles D. Papageorgiou, Allan S. Myerson, Peter Sagmeister, Kensaku Matsunami, Aparajith Bhaskar, Darren Whitaker, Richard D. Braatz, Neda Nazemifard, John Mack, Adrian Ramirez Galilea, Mohammed Janoudi
article en

Abstract

A structured, three-stage workflow was developed to accelerate hydrogenation process development, facilitate rapid scale-up translation, and maximize process understanding through data-rich experimentation. The approach integrates high-throughput batch screening, intermediate-scale catalyst evaluation, and continuous flow implementation, while allowing flexible entry at any stage depending on prior process knowledge. In Stage I, a high-throughput robotic platform enables rapid screening of catalysts, solvents, and additives under pressurized conditions, supported by automated ultra-high-performance liquid chromatography (UHPLC) method development for efficient analysis. Stage II transitions to intermediate-scale reactors for catalyst optimization and safety assessment under controlled hydrogenation conditions. In Stage III, process knowledge is transferred to continuous flow, where reaction conditions are optimized and process control strategies, including automated experimentation, dynamic experiments, and model predictive control (MPC), are implemented. The workflow was demonstrated in a case study of a catalytic nitro reduction, and reaction conditions were successfully scaled up and translated from batch to continuous flow.

Organic Process Research & Development
Davidson College (US), Vanguard University (US), Purdue University West Lafayette (US), Takeda (United States) (US), Synthetic Biologics (United States) (US), Massachusetts Institute of Technology (US)
Openalex Percentile: Top 12%
Innovative Microfluidic and Catalytic Techniques Innovation
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