Scout, Sabermetrician, and Superforecaster: Deep Learning for Drug Discovery and Development

Register Free: http://www.pharmexec.com/pe_w/discovery

Event Overview:

The approach to drug discovery and development has evolved over the years. It started primarily based on expert experience/opinion (Scout). Now, most drug discovery and development processes heavily rely on historical data and statistics (Sabermetrician), while many people believe the future of drug discovery and development is the accurate prediction from AI-technology (Superforecaster).

In this talk, Head of AI research at IQVIA’s Analytics Center of Excellence Jimeng Sun will present the key ingredients for achieving superforecasting in pharmaceutical applications and provide some examples of our works in deep learning algorithms for drug-target interaction, molecule optimization and trial outcome prediction.

3 Key take-aways

1. The success of deep learning in drug discovery and development depends on high-quality labeled data, effective algorithms, and comprehensive evaluation benchmarks.
2. A flexible encoding-decoding learning framework can support diverse drug discovery tasks such as drug-target interaction, drug property prediction, and drug-drug interaction.
3. Multi-modality data, such as molecules, diseases, and eligibility criteria, can help predict clinical trial success.

In case of any questions, please reach out to Julia Longo at jlongo@mjhlifesciences.com

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Speakers

Jimeng Sun
Global head of AI research at IQVIA, Health Innovation Professor
IQVIA and University of Illinois Urbana-Champaign

Dr. Sun is the global head of AI research at IQVIA and a Health Innovation Professor at the University of Illinois Urbana Champaign. He has published over 300 papers and has 21,947 citations, h-index 75 and i10-index 208. His research includes deep learning for drug discovery, clinical trial optimization, computational phenotyping and clinical predictive modeling. He was recognized as one of the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare by Deep Knowledge Analytics.

Lucas Glass
Vice President, Analytics Center of Excellence
IQVIA

Lucas Glass is the Vice President of the IQVIA Analytics Center of Excellence (ACOE). The ACOE is a team of over 200 data scientists, engineers, and product managers that research, develop, and operationalize machine learning and data science solutions within the R&D space. Lucas has launched over a dozen machine learning offerings within R&D such as site recommender systems, trial matching solutions, enrollment rate algorithms, drug target interactions, drug repurposing, molecular optimization. Lucas’ machine learning research which is dedicated to R&D has been accepted at AAAI, WWW, NIPS, ICML, JAMIA, KDD, and many others.

Lucas started his career in pharmaceutical data science 15 years ago at Center (Galt) working on pharmacovigilance data mining algorithms. Since then, he has worked at the US Department of Justice in healthcare fraud, several small startups, and TTC, llc which was acquired by IMS In 2012.

Lucas holds a BA is Physics from Boston University, a MS in biostatistics from Drexel University, and is a PhD Candidate at Temple University where he is researching deep learning embedding techniques on large scale healthcare data.

Register Free: http://www.pharmexec.com/pe_w/discovery