Equality in AI-Driven Drug Discovery

Drug discovery is a high-risk, time-consuming, and costly process. 90% of drug candidates fail, while an average successful drug takes more than 10 years and one billion pounds to reach patients. Many pharmaceutical companies are turning towards drug development for rare diseases, as the cost of developing such orphaned drugs is a third of that for common diseases. However, drugs to treat common diseases are still more profitable and thus more heavily invested, leaving a large gap within the disease target space. Advancements in Artificial Intelligence (AI) and Machine Learning (ML) hold promises to revolutionise drug discovery, making drug discovery a more efficient process with equality across disease targets.


List of speakers and bio:

Dr. Paula Fernandez Guerra

Paula is a Senior Postdoctoral Research Fellow at the University of Southern Denmark. Paula’s research focus is on personalised medicine, specifically on finding adequate therapies for patients with rare metabolic and mitochondrial diseases using the cells from patients and cell models. Paula is also Chairwoman of the Society of Spanish Researchers in Denmark. Previously, Paula has worked as an postdoctoral scientist at the Aarhus University. Paula has also completed her PhD in Aarhus where she researched the cellular characterization of human dermal fibroblasts, focusing on mitochondria and Maple Syrup Urine Disease.

Dr. Hagen Triendl

Hagen is a Director of AI Research at Exscientia where he leads the AI Technology: Machine Learning (ML) team which focuses on designing new ML models to automate small molecule drug discovery. Previously, Hagen has worked at GSK where he led the development of an ML platform for predicting genetic markers from histopathology images. Prior to that, Hagen was the Head of Research at GTN - a biotech startup in London. Hagen is a theoretical physicist by training and completed a PhD in Hamburg before taking on several research positions in Paris, at CERN, and at Imperial College London.


Registration link: https://www.eventbrite.com/e/equality-in-ai-driven-drug-discovery-tickets-628608082697