This workshop will explore the main challenges to statistical approaches in improving fairness in genomics and genomic medicine. We will host a series of panel discussions, each focusing on a different aspect of genomic medicine, featuring international experts from across academia and medicine.

The workshop is open to all with an interest in using data-driven approaches to improve fairness in genomics and we greatly welcome participation from a broad range of backgrounds and disciplines.

Workshop aim

The aim of the workshop is to identify the main barriers to

1. Understanding the cascading effects of inequities in genomic data and in the design and development of statistical models
2. Detecting / quantifying unfair biases and the effects on inequities in genomic medicine
3. Improving the equity of statistical approaches and mitigating unfair biases
4. Understanding the limitations of statistical approaches to mitigating unfair biases and addressing inequities.

Confirmed panellists

• Prof Gil McVean (Genomics plc)
• Dr Segun Fatumo (LSHTM)
• Prof Eimear Kenny (Icahn School of Medicine at Mount Sinai)
• Prof Nilanjan Chatterjee (Johns Hopkins)
• Dr Raghib Ali (Cambridge & Our Future Health)
• Prof Allison Kurian (Stanford)
• Prof Nancy Cox (Vanderbilt)
• Prof Anneke Lucassen (Oxford)
• Dr Bogdan Pasaniuc (UCLA)
• Dr Alex Shalek (MIT)
• Prof Nora Franceschini (UNC)

Agenda (tentative)

All times GMT

• 2.00-2.30pm: Introduction to the workshop
• 2.30-3.30pm: Disease mechanisms panel
• 3.30-4.30pm: Disease diagnostics panel
• 4.30-5.30pm: Risk prediction panel
• 5.30-6.00pm: Final discussions + wrap-up

Organisers

The workshop is being run in collaboration between Data Science for Health Equity, the Alan Turing Institute and the Diverse Data initiative at Genomics England. The organising team is:

• Dr Brieuc Lehmann (UCL)
• Prof Chris Holmes (Oxford)
• Prof David Leslie (Alan Turing Institute)
• Prof Nilanjan Chatterjee (Johns Hopkins)

Please direct any enquiries to Brieuc Lehmann at b.lehmann@ucl.ac.uk.