E4*
VARIOMIS: Deconvoluting Genetic Diversity to De-Risk Drug Discovery
Dr James Stephenson, EMBL-EBI
EMBLEM Technology Transfer GmbH
Challenge
Drugs are commonly designed based on the genetics of a narrow subset of the human population. The result is that many drugs don’t work as well for people in countries not represented in that subset, often in regions with fewer alternatives. Trial failures due to lack of efficacy in some populations mean that fewer drugs get to market, resources are wasted and the cost to patients is increased for successful drugs. Drugs can also be recalled for safety reasons if they have unpredicted effects in some populations. The challenge is therefore to account for global genetic diversity to make safer and more broadly effective drugs.
Technology
Variomis is an AI startup, guiding the development of drugs which reflect the true complexity of the human population. Our software is designed to reduce global healthcare disparities by enabling the development of drugs which are safer and work better, for everyone. For each potential target region, we provide a report on variation likely to occur in human populations. We assess the consequence of this variation on binding, to a range of small molecules. AI derived models are validated and refined on state-of-the-art experimental methods via our lab in the loop. Our diversity effect assessments allow our customers to compare and rank preclinical targets to deprioritise those which may be affected by global genetic diversity.
Commercial Opportunity
We provide an AI-driven platform to guide target prioritisation accounting for global genetic diversity and are seeking collaboration and investment to scale its impact.
Development Status
TRL3
Patent Situation
copyrights and know-how
Further Reading
