(34e) A Case Study and Design Considerations for the Robust Removal of Dissolved Hydrogen Chloride
- Conference: AIChE Annual Meeting
- Year: 2018
- Proceeding: 2018 AIChE Annual Meeting
- Group: Pharmaceutical Discovery, Development and Manufacturing Forum
- Time: Sunday, October 28, 2018 - 4:54pm-5:15pm
A potential therapeutic asset utilized a chlorination reaction which generated hydrogen chloride (HCl) gas as the reaction progressed. The presence of low levels of HCl in the liquid phase was found to cause the crystallization of a hydrochloride salt when coupled with the next stepâs reagent, thereby inhibiting the reaction and generating an impurity that would result in the product failing specifications. A simple nitrogen sweep of the reactor headspace, at laboratory scales, was initially deemed effective to reduce the dissolved HCl to acceptable levels within a few hours. However, severe reaction conditions (high temperature and a corrosive environment) inhibited the ability to quantify the degassing kinetics, which were required to predict the - degassing performance at scale. Additionally, mass-transfer effects at scale could provide a dominative resistance, perhaps slowing down the degassing efficiency. It was desirable to design an optimum protocol for the HCl degassing options to ensure successful degassing during scale-up. A mathematical model including the solubility of HCl in the liquid phase and mass-transfer rates was developed to assess and predict the performance of various options to remove dissolved HCl: 1) a nitrogen sweep of the reactor headspace, 2) nitrogen pressure/purge cycles with the reactor vent open to atmospheric pressure, and 3) nitrogen pressure/purge cycles with the reactor vent connected to vacuum. HCl degassing data was collected experimentally using a setup equipped with a pH meter and flow NMR; this data was used to verify the model predictions. This contribution will summarize the integrated approach of coupling experiments and model predictions to devise the most effective degassing methodology to be implemented at scale and ensure consistent product quality during scale-up.