Drug Discovery Disrupted: Quantum Physics Meets Machine Learning
Whenever a disease is identified, a new journey into the “chemical space” starts seeking a medicine that could become useful in contending diseases. The journey takes approximately 15 years and costs $2.6bn, and starts with a process to filter millions of molecules to identify the promising hundreds with high potential to become medicines. Around 99% of selected leads fail later in the process due to inaccurate prediction of behaviour and the limited pool from which they were sampled. We are at GTN Ltd addressing the main bottlenecks in drug development by new innovations marring ideas from machine learning and quantum physics.
Prof. Noor Shaker is a co-founder and CEO at GTN Ltd. Before starting GTN, she was an assistant professor at Aalborg University in Copenhagen working on different aspects of machine learning with special interest in generative models. She is the main author of the book “Procedural Content Generation in Games” which covers many of the generative methods. She has more than 50 publications and 1000+ citations. She serves as the chair of the IEEE games technical committee and she is an active member in the games research society participating in organizing conferences, workshops and tasks forces. She has won a number of awards for her research including the IEEE Transactions on Computational Intelligence and AI in Games Outstanding Paper Award. At GTN, she is working with leading researchers on a novel, patent-pending, technology to drug discovery bringing ideas from quantum physics and machine learning.