Dr Armin Schneider has 20 years track record in leading roles in Biotech drug discovery and development and MD PhD from the University of Heidelberg, Germany. At Molecular Health, Armin pioneers the utilization of the company’s technology, Dataome® - a mighty clinical-molecular knowledge base of drugs, diseases and outcomes into machine learning applications and predictive algorithms to predict drug outcomes and R&D efficiency. He has authored over 150 publications and owns numerous patent families and has a strong background in neurology, pharmacology, molecular biology, and statistics, and specific interest in questions of applying advanced statistical methodology to drug development.
Day 1 Plenary – Wednesday 4th December 2019 @ 15:30
Predict R&D success. With AI
Around 85% of potential drugs entering Phase I clinical trials are destined to fail. With MH Predict, Molecular Health has recently launched an AI tool that can predict the probability of success of clinical trials. In this talk, Prof. Armin Schneider will introduce Molecular Health’s proprietary prediction software and will discuss its application in a range of different scenarios. MH Predict can be used in the design of clinical trials to optimize key parameters as well as to predict trial success. In addition to analyzing a company’s own trials, the evaluation of clinical trials of competitors is another use case. Portfolio management and asset search and evaluation can also profit from Molecular Health’s software. Finally, MH Predict is able to perform in silico-driven hypothesis assessments, evaluate drug combinations in silico to improve treatment strategies, and identify candidates for drug repurposing Smietana, Katarzyna & Siatkowski, Marcin & Møller, Martin. (2016). Trends in clinical success rates. Nature Reviews Drug Discovery. 15. 10.1038/nrd.2016.85.
last published: 15/Nov/19 09:45 GMT