2021 Annual Meeting
(524d) Physics-Based Computational Models to Expedite Pharmaceutical Solid-Form Selection
Authors
Chandler Greenwell, Xtalpi, Inc.
Yuriy Abramov, VP of Scientific Affairs, Xtalpi
Qun Zeng, XtalPi Inc
Chao Chang, XtalPi Inc
Zhuocen Yang, XtalPi Inc
San Kiang, Rutgers University
Shanming Kuang, J-STAR Research
Jian Wang, J-STAR Research
Sivakumar Sekharan, XtalPi, Inc.
Improving poor physicochemical properties of active ingredients and intermediates is a challenging problem for solid formulation scientists. Physics-based computational models to select pure solvents, solvent mixtures and coformers for crystallization processes has recently attracted much attention in the pharmaceutical industry. Here, I will present some case studies to demonstrate how we employ physics-based models to (i) perform a rational solvent selection to identify solvents with high and low probability to form solvates and/or impurity purge; and (ii) select coformers to form a cocrystal and guide comprehensive experimental solid form screening to mitigate challenges in solid formulation.