A Practical Guide to AI in Clinical Trials

10-11 June 2019

Get ahead of the curve in AI-enabled clinical innovation

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Course Overview

Bringing a drug to market is an arduous task, with the process taking from between 10 to 15 years while costing billions. Therefore, with claims that AI will be able to transform this process by improving the efficiency and optimization of clinical trials, it is no surprise that it has generated intrigue across life science industries.

This course will, through the investigation of key use cases, provide understanding on these questions and help management level staff make informed decisions regarding its use in their business.

Book by 10 May, Save £200

London: 10-11 June 2019

PRICE: £1195 + VAT

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Why choose this course?

Why is this topic important?

  • Only 6% of trials complete on time in the US (Clinithink, 2017).
  • The median cost of a Phase I trial is $3.4mn, rising to $8.4mn and $21.4mn for Phases II and III (source: FDA, 2017).
  • It takes up to 12 years for a new drug to be commercialised (source: Bayer, 2017).
  • Overall, clinical trials cost the US $51bn per year (AiCure, 2017).

Is it for you?

  • Clinical Trial Manager
  • Clinical Research Consultant
  • Clinical Project Manager
  • Clinical Operations Manager
  • Vendor Relationship Manager
  • Chief Innovation Officer
  • Chief Digital Officer
  • Chief Data Officer
  • Chief Technology Officer
  • Head of Innovation

Programme Modules

  • Overview on AI-enabled clinical innovation
  • Use case: AI for clinical trials phases 1-3, including medical imaging
  • Use case: AI for medical record integration
  • The strategic discussions and decisions needed to realise the potential of AI in the pharmaceutical industry
  • Use case: AI for improved employee efficiency exemplified on pharmacovigilance
  • Use case: How AI is being used in virtual trials
  • A look a current research – What can future developments can we expect in AI for clinical trials?

Learning Outcomes

Key course benefits

  • Dr Chrysanthi Ainali, the course director, is an expert bioinformatician and data science consultant who has worked for years on applying Machine Learning to clinical trial research.
  • The course will provide participants with clear use cases of AI for clinical trial design, patient recruitment and site selection, among others.
  • The course will give participants a comprehensive overview and understanding of the opportunities now available to apply AI and Real World Evidence to many of the problems afflicting trials.

Benefits to the individual

  • Explore: Learn how to navigate the forces in play – forces which enable / add hurdles to the adoption of AI technologies in clinical development. 
  • Strategise: Learn use cases of AI technologies for clinical trial design, patient recruitment, and site selection.
  • Implement: Navigate the unique challenges faced by pharma in implementing AI technologies and solutions. 
  • Innovate: Use Real-World Evidence for more patient-centred outcomes and to utilise RWE and AI for process automation, predictability, improved ROI and time-to-market for new drugs.

Programme Details

Module 1

Overview on AI-enabled clinical innovation

Module 2

Use case: AI for clinical trials phases 1-3, including medical imaging

Module 3

Use case: AI for medical record integration

Module 4

The strategic discussions and decisions needed to realise the potential of AI in the pharmaceutical industry

Module 5

Use case: AI for improved employee efficiency exemplified on pharmacovigilance

Module 6

Use case: How AI is being used in virtual trials

Module 7

A look a current research – What can future developments can we expect in AI for clinical trials?

Dr Christian Spindler

Consultant and former IoT Lead & Data Scientist for PWC

Dr Eddie Guzdar

Medical Head of Neuroscience at Sanofi Genzyme UK & Ireland

Bhupathy Alagiriswamy

Consultant Associate - SR. Clinical Trial Management, Gilead Sciences

Is it for you?

This course has been tailored to provide decision-makers and those interested in the practical use of AI as applied to clinical trials.

Leaders

Who want to understand new techniques in the aggregation and analysis of trial data, enabling new efficiency and increased ROI

Strategists

Who want to avoid disruption in the rapidly expanding eclinical space, and effectively navigate the challenges faced by pharma.

Innovators

Who want to be updated on the most recent developments of AI-enabled clinical innovation to understand how it can be incorporated into their business

Job Titles Include:

  • Clinical Trial Manager
  • Clinical Research Consultant
  • Clinical Project Manager
  • Clinical Operations Manager
  • Vendor Relationship Manager
  • Chief Innovation Officer
  • Chief Digital Officer
  • Chief Data Officer
  • Chief Technology Officer
  • Head of Innovation

Customised In-Company Training

All our programmes are fully customisable and can be delivered at a time and location suitable to your organisation's uniques requirements. Get in touch to discuss how we can build the perfect training solution for your organisation.