Predictive Candidate Prioritisation Before Costly Validation

Companies developing new ingredients or compounds often need to decide which candidates should move into costly safety, efficacy or non-animal validation workflows. Making the wrong choice means spending time and budget on candidates unlikely to progress.

We are interested in developing predictive models that help prioritise candidates before those experiments begin, using each organisation’s existing experimental data.

We are looking for ingredient developers, cosmetics companies, CROs and research groups with historical screening and outcome data who are interested in a collaborative R&D pilot, potentially supported through regional or European funding calls.