(640g) Kinetic Modeling to De-Risk Process Changes As a Part of Life-Cycle Management

During drug substance development, project teams invent, optimize, and thoroughly characterize manufacturing processes to make the drug substance in a safe, sustainable, and robust manner. Many of the overall goals are set by projected commercial demand. For instance, sustainability and volumetric efficiency may be a larger driver for a high-volume drug compared to a low-volume drug. As drug candidates transition out of development and into the commercial space, actual demand could be substantially higher (or lower) than the projected volume during development. As such, a key feature of life-cycle management should be a constant re-evaluation of development team goals versus commercial goals to determine whether cost-saving opportunities exist. With much clearer ROIs than possible during development, process teams can gain mechanistic understanding of reactions and complex processes to de-risk potential process changes in the manufacturing space. Further, the technological advancements in process analytical technology often enable teams to thoroughly interrogate reaction systems that may not have been possible during development.

Herein we present a case study on a heterogenous catalyzed nitroreduction employed in the penultimate step of a commercial drug. Due to the global demand of the drug itself, multiple opportunities for cost savings and reduced environmental impact were identified throughout the synthetic route, including reducing the catalyst loading within the filed proven acceptable ranges (PARs) for the nitroreduction. A known issue with reducing catalyst loading is the formation of dimer impurities that can impact API quality (color) even at low levels (<1000 ppm). To de-risk this process change, we employed data-rich experimentation and kinetic modeling to gain a mechanistic understanding of this high-pressure, heterogeneous reaction system, with a specific focus on dimer formation. High-pressure automated sampling enabled time-resolved LC analysis to help understand the kinetics of the reaction and the risks associated with impurity formation. Ultimately, we identified temperature and age times as a means minimize residual dimers in the reaction stream. These changes are being employed across multiple sites in our vendor network, resulting in >1$M in savings on precious metals per site, while still maintaining a robust and safe process to manufacture high-quality API.