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Pre-Conference Workshop Day – Tuesday, 25 July

We believe a variety of conversations is key to getting the most out of your conference educational experience. Our workshop day provides the perfect counterpart to our two day main event. Embrace a more in-depth, intimate and probing experience to dig a little deeper into some of the applications and challenges of implementing AI across R&D. This workshop day includes group discussions, proactive debates, case study detail, and hackathon-style collaboration.


Workshop A

Time: 09.00am – 11.30am

AI for Precision Medicine: Harnessing AI Technology to Provide More Granular and Valuable Insights on Patients and Healthcare

The whole industry is investing in the precision medicine approach as the healthcare paradigm shifts towards value and outcomes. More so than ever, developing a biomarker approach, stratifying responder populations and gaining insight into patient responses is essential.

  • Unlocking novel insights on patients to improve drug efficacy and success
  • Understanding patient populations: What can AI tell us that traditional stratifying approaches are yet to uncover?
  • Algorithmic responsibility: Who holds accountability for the downstream effects of AI based decision making?
  • An eye downstream: Understanding how AI can revolutionize personalized medicine and patient care
  • Discussing the application of machine learning in patient stratification, genomic analysis, population investigation and real world data
  • How to best action smart learning algorithms to comb over a wealth of genetic data and find patterns and insights that are significant for human health

Workshop Leader:

Zeeshan Syed.pngZeeshan Syed

Director, Clinical Inference & Algorithms Program

Stanford Health Care


Workshop B

Time: 12.00pm – 2.30pm

A Fundamental Guide to the Application of AI in Clinical Trials to Reduce Failure Rates 

The clinical landscape is littered with safety and efficacy failures across the board. With so much invested to drive candidates through the clinical pipeline, current failure rates are simply unsustainable. This intimate and informal workshop session will take a deeper look at how AI technology can be applied across clinical trials to expedite trial time and ultimately improve approval rates.

  • Discussing trial optimization and how AI can improve failure rates in clinical trials
  • Applying AI to clinical trial design and the analysis of clinical trial data
  • Investigating the role of machine learning in patient stratification prediction, population and genomic analysis
  • Machine learning for analysis of genomic and imaging data
  • What insights can AI give us into clinical outcomes
  • Harnessing AI to validate the predictiveness of diagnostic testing in the clinic
  • Manipulating clinical data with machine learning analytics to derive exclusion criteria for efficient and cost effective patient selection
  • Understanding how AI can be used to mine data for clinical trial site selection to improve enrollment, retention and ease of access for relevant patient cohorts

Workshop Leader:

Jason RainesJason Raines

Head, Biometrics Data Sciences & Operations



Workshop C

Time: 3.00pm – 5.30pm

A Fundamental Guide to the Application of AI in Drug Discovery to Uncover the Next Wave of Successful Future Candidates

This interactive workshop session will delve deeper into the multiple applications of AI algorithms in drug design and discovery. With so much at stake later down the R&D pipeline, it is essential that only the best candidates are identified to progress through the pre-clinical and clinical landscapes.

  • How do you support discovery using AI?
  • Training neural networks to predict molecular structures
  • Improving the scaling of drug discovery efforts by utilizing AI technology
  • Discussing the application of AI for target and compound selection
  • Predictive analytics for drug discovery target validation
  • Discussing sophisticated predictive machine learning methods to improve the speed and efficiency of  drug discovery process
  • Developing computational AI methods for screening
  • Harnessing AI platforms to correlate label drug use and medical events to identify suitable molecules for drug repurposing

Workshop Leader:
Alex ZhavoronkovAlex Zhavoronkov


Insilico Medicine

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