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How is the fundamental understanding of quantum mechanics helping to keep medicine from expiring?
Alexandre Tkatchenko is a Professor of Theoretical Chemical Physics and the Head of the Department of Physics and Materials Science at the University of Luxembourg. Alexandre was here in Telluride with his graduate student, Adil Kabylda, for the March 2023 workshop, Intermolecular Interactions: New Challenges for Ab Initio Theory.
Alexandre develops novel quantum mechanical methods and applies them across large space and time scales – this feat became possible only recently due to the confluence of theoretical method developments, artificial intelligence algorithms, powerful software codes, and large computers. These developments push the boundaries of quantum mechanics beyond what its founding fathers (including Einstein, Schrödinger, or Feynman) could imagine.
Utilizing quantum mechanics with tools like machine learning, Alexandre models what will happen at scales beyond the atomic level, from cosmology to biology to pharmacology. While most of his work would be considered fundamental science, his modeling approach was recently adopted by a dozen pharmaceutical companies to improve the formulation of drug therapeutics.
Whenever a pharmaceutical company creates a drug, it is a very complicated design and formulating process to create the final molecule – a mixture of the active drug and other chemical components, that is unstable enough (metastable) so that it can be dissolved and absorbed by the body, but stable enough in its absorbable form that it doesn’t “expire.” Most things in nature want to go from a higher energy state to a lower energy state. The problem with a low-energy state is that it is often not absorbable by the body. A drug expires when it transitions from its metastable state to a stable state. Alexandre’s quantum mechanics modeling approach has been applied very effectively to more efficiently design pharmaceutical drugs that can keep drugs from expiring and remaining in a usable and therapeutically active state.
With such a broadly applicable modeling method, we look forward to hearing about new ways that Alexandre and his team will advance other areas of science and technology.
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