Creating Digital Components to Enable New Paradigms in Safety Assessment
At ToxComponents our mission is to improve human health outcomes and eliminate animal testing by providing toxicologists with reusable computational tooling components which can be flexibly combined to enable confident decisions in different safety contexts.
Research Interests
Structuring Digital Knowledge
Creating knowledge graphs centred around mechanistic toxicology and AOPs, to define problem spaces and contextualise NAM evidence.
Gathering Evidence and Building Predictive Models
Using emerging AI approaches to speed up data collection and generate predictive models for integration into safety assessments.
Supporting Decisions
Encoding approaches to help toxicologists interpret, combine and reason between NAM evidence to reach meaningful conclusions.
Reporting Conclusions
Creating digital reports which clearly summarise evidence, present defensible conclusions, with transparent reasoning and reference to evidence sources.
