(762a) Use of a Trickled Bed Reactor to Improve the Commercial Feasibility of the Hydrogenation of a Nitro-Compound
- Conference: AIChE Annual Meeting
- Year: 2017
- Proceeding: 2017 Annual Meeting
- Group: Pharmaceutical Discovery, Development and Manufacturing Forum
Thursday, November 2, 2017 - 3:15pm-3:40pm
Carla Luciani, Jonas Buser, Michael Laurila, Richard Cope, Kevin Cole, Bradley Campbell, Justin Burt, Martin Johnson, Joseph Martinelli, David Mitchell
Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN-46285, USA
The use of continuous processing to manufacture intermediates and drug substances has grown significantly over the last few years. While the major reasons for the rapid adoption of continuous technologies in the pharmaceutical industry are typically linked to productivity and safety as well as quality benefits, there are cases where the use of continuous processing is required long term to ensure the process robustness required for commercial manufacturing.
This work investigates the Pd-catalyzed reduction of a nitro compound to produce an aniline during the second step of the proposed registered sequence. Major challenges resulting from the complexity of the reaction matrix were overcome by the use of advanced monitoring techniques (flow-NMR and on-line HPLC). Those monitoring techniques produced exceptionally detailed kinetic profiles that were used to fit kinetic models. The kinetic models were used to simulate the reaction profiles using both continuous and batch reactor types. In addition to the typical manipulated variables investigated for the batch option, such as temperature, pressure, catalyst loading, and catalyst poisons entering the process, several other process parameters were investigated to understand the trickle bed reactor performance (e.g., temperature and concentration profiles in both radial and axial direction, flowrates, wetted catalyst surface, catalyst deactivation mechanism, etc.). The model was used to compare the resulting feasible operating regions/design spaces for both batch and flow modes. Finally, the model was used to investigate re-packing strategies and optimal temperature profiles during operation.