Deciphering the Code of Drug Discovery: Application of Machine Learning in Designing Compound Libraries – KIELTYKA GLADKOWSKI TAKES PART IN MEETING WITH SELVITA AT LifeScience Kraków Cluster
Publication date: October 9, 2024
On Thursday, October 10, KIELTYKA GLADKOWSKI KG LEGAL will take part in the meeting at the Life Science Cluster with SELVITA, on “Deciphering the Code of Drug Discovery: Application of Machine Learning in Designing Compound Libraries”. The meeting will be hosted by the leading Polish biotechnology company Selvita, including a Senior Machine Learning Specialist, responsible fordevelopment of the proprietary TADAM model (Target- Aware Drug Activity Model). This is a deep machine learning model that allows for efficient high-throughput virtual screening. This model has a significant advantage over other existing solutions on the market – it is much faster and more accurate in the analyses performed, and also achieves state-of-the-art results, enabling the creation of combinatorial library subsets targeted to a specific biological target. Studies of such sets significantly increase the probability of identifying the right active compounds, which is crucial for drug development. Additionally, a separate model has been developed to predict the optimal conditions for the amidation and Suzuki reactions. This facilitates the synthesis of the targeted libraries described above using appropriately arranged catalysts, reagents and solvents for optimal performance based on substrates.
