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AI can make pharma production cheaper and more efficient - researchers
Artificial Intelligence can be used to make drug production more efficient, economical, and sustainable, according to the international research team behind a groundbreaking new collaboration.
Scientists from University College Cork (UCC) with academic and industry leaders from Ireland and the United States are part of a new initiative named ‘InTeleCat’, which aims to accelerate the development of pharmaceuticals.
The team, lead by Dr Ger McGlacken of UCC’s School of Chemistry, is comprised of experts in the fields of catalysis, computational chemistry, and data science.
Dr McGlacken said:
“The optimisation of chemical structures for a desired clinical effect is a very expensive and time-consuming process. In this project we will use high throughput screening and Artificial Intelligence (AI) to dramatically accelerate future pharma campaigns. This is the future of drug optimisation and very much part of the UCC ambition through Future Pharmaceuticals”.
The primary goal of InTeleCat is to leverage Machine Learning (ML) and Artificial Intelligence (AI) to optimise and predict catalytic processes that are critical in the pharmaceutical industry. This initiative aims to significantly reduce the time and cost required to identify the best route to a desired Active Pharmaceutical Ingredient (API) and to predict which APIs are suitable for specific reaction conditions.
The project has been mobilised by funding of $120,000 from the University of Notre Dame through a Naughton Fellowship, supported by the SSPC (The Science Foundation Ireland (SFI) Research Centre for Pharmaceuticals)and represents a significant step forward in the pursuit of innovative and efficient solutions for the pharmaceutical sector.
Scott A. Frank, Associate Vice President, Eli Lilly said: “Eli Lilly is looking forward to collaborating with the McGlacken group at UCC in cooperation with the University of Notre Dame, and the University of California, Los Angeles. This is a very exciting project which will leverage our high throughput experimental capabilities in Indianapolis to carry out thousands of reactions in a single day, building data platforms which will be used with machine learning and AI to sort data. It is our firm position that this is the future of drug development and will accelerate rapid identification of ideal chemical processes”.