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8:30 am Coffee & Registration

9:00 am Chair’s Opening Remarks

LEVERAGING AI TO DESIGN THE RIGHT CLINICAL TRIAL FOR YOUR DRUG, PRECISELY

Clinical failure is often due to poor trial design. The following 5 sessions look at how you can use AI to find the best outcomes for the patients and the clinical trial itself, looking at methodologies to enroll the appropriate patients for drug studies and assessing the evolving application of AI in the pursuit of precision medicine. From optimizing AI for site selection through to data driven protocol design, targeted patient stratification and identifying the right tools to provide unbiased pipelines.

9:10 am Unlocking the Potential of Machine Learning (ML) in Clinical Development

  • Kyle Holen Head, Development Design Center, AbbVie

Synopsis

  • ML for selecting sites for clinical trials
  • ML to predict patient drop-outs over a range of patient demographics to raise patient retention

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9:40 am Using AI & Data Science to Rapidly Discover Precision Medicines by Analyzing Failed Phase 3 Trial Data

Synopsis

  • This presentation will look at methods in AI and Data Science for segmenting
    patient populations to find successful drugs
  • Using / leveraging AI to enroll trials for precision medicines, and reduce
    enrollment time

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10:10 am Morning Refreshments & Speed Networking

11:10 am Using ML to Develop Personalized Medicine for Psychiatric Patients

  • Qasim Bukhari Postdoctoral Research Associate, Massachusetts Institute of Technology

Synopsis

  • Finding the right patient, for the right medication at the right dose
  • Developing analytical tools for application in neuroscience, both imaging and
    non-imaging data

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11:40 am Use of AI in Computational Pathology for Patient Stratification

  • George Lee Digital Pathology Informatics Lead and Data Scientist, Bristol-Myers Squibb

Synopsis

  • Deep Learning for improving quality of pathology data in clinical trials
  • How we are developing the next generation of machine learning and feature

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12:10 pm Using Probability-Based AI to Augment Clinical Development

Synopsis

  • How is the Healthcare field embracing AI?
  • How to develop a new AI system to attend current challenges?

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12:40 pm Networking lunch

EXECUTING THE INNOVATIONS: WHY, WHEN & HOW TO IMPLEMENT AI INTO YOUR CLINICAL DEVELOPMENT PIPELINES

In these sessions we look at how to innovate in a more open, collaborative, cost effective and timely manner. These sessions look at mapping out the implementation of AI into clinical development, the practical adoption and technical implementation of AI. Critically this section looks at understanding why, when and how to implement AI into your clinical development pipeline: executing the innovations.

1:40 pm Infrastructures, People Structures, & Problem Structures: Managing the Shift to AI

Synopsis

  • Challenges in leveraging AI in pharma
  • Why AI will fundamentally change the paradigms

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2:10 pm Panel Discussion: How Do You Build a Business Case Behind an AI Platform?

  • Ameya Phadke Digital Health & Technology Transactions Lead, Chiesi Pharmaceuticals
  • Michael Frank Director, R&D Strategy, World Wide Research and Development, Pfizer

Synopsis

  • Where does it pay-off and where does it not?
  • When does it make sense to implement AI-ML?

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2:40 pm Combining Blockchain, Machine learning & Process Automation to Optimize the Future of Clinical Development

Synopsis

  • How can blockchain and machine learning deliver real value and speed up drug development?
  • How can we serve our patients better and increase transparency in clinical trials?

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3:10 pm Networking Break

3:40 pm Mastermind Session

Synopsis

This session will allow you to have more intimate discussions with AI and pharma leaders around some of the hottest topics in the field. Discover multiple perspectives on these key issues, so that you can learn from your fellow experts in the audience. Drive your own learning, crowd-source ideas and get inspired.

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4:40 pm Chair’s Closing Remarks

4:50 pm End of Day One