Computational Pharmaceutical Science: Guiding Experiments in a Sea of Variables
The phrase “from molecules to medicine” is often used to describe the process of drug development. The idea is that medicinal chemist isolate molecules which have been optimized for absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties and drug development enables those molecules to be functional medicines. This can pose many problems, as often a particular molecule may not exhibit good “developability” properties as the solid form the chemist isolated, like solubility or physical stability.
Extensive efforts are taken to determine which physical form of a molecule can enable it for good pharmacokinetic properties to drive exposure. This includes finding neat polymorphs, cocrystals, salts, solvates, hydrates, etc. However, there are certain risks associated with physical forms as physical properties may not be suitable for typical oral dosing strategies (i.e. making good tablets).
When most people think about pharmaceutical risk, they focus quite specifically on the idea of thermodynamic polymorph stability, and the risk of a more stable polymorph on a drug molecule's PK; however, while computational chemistry can most assuredly assist in understanding thermodynamic stability, this is not the only way it can assist. In this talk we outline how computational chemistry can assist the solid-form screening efforts as well as getting an early read on some risk analyses.
In addition, there will be a case study focused on the complex form landscape and analysis of a small chiral drug-intermediate with a focus on how computational material science can help to understand structural analysis that goes beyond traditional techniques.