op0c00222_si_001.xlsx (46.81 kB)
Applications of Quantum Chemistry in Pharmaceutical Process Development: Current State and Opportunities
dataset
posted on 2020-08-07, 15:15 authored by Yu-hong Lam, Yuriy Abramov, Ravi S. Ananthula, Jennifer M. Elward, Lori R. Hilden, Sten O. Nilsson Lill, Per-Ola Norrby, Antonio Ramirez, Edward C. Sherer, Jason Mustakis, Gerald J. TanouryApplication of computational
methods to understanding and predicting
properties of analogues for drug discovery has enjoyed a long history
of success. However, the drug development space (post-candidate selection)
is currently experiencing a rapid growth in this arena. Due to the
revolution in computing hardware development and improved computational
techniques, quantum chemical (QC) calculations have become an essential
tool in this space, allowing results from complex calculations to
inform chemical development efforts. As a result, numerous pharmaceutical
companies are employing QC as part of their drug development workflow.
Calculations cover the range of transition state calculations, reaction
path determination, and potential energy surface scans, among others.
The impact of this rapid growth is realized by providing an in-depth
understanding of chemical processes and predictive insight into the
outcome of potential process routes and conditions. This review surveys
the state of the art in these drug development applications in the
pharmaceutical industry. Statistics of computational methods, software,
and other metrics for publications in the last 14 years (2005–2019)
are presented. Predictive applications of quantum chemistry for influencing
experiments in reaction optimization and catalyst design are described.
Important gaps in hardware and software capabilities that need to
be addressed in order for quantum chemistry to become a more practical
and impactful tool in pharmaceutical drug development are discussed.
Perspectives for the future direction of application of QC to pharmaceutical
drug development are proposed.