SAFEPATH integrates cheminformatics and bioinformatics to understand the mechanisms behind drug toxicity. In preclinical and clinical studies, safety assessments typically reveal what went wrong—such as liver failure or cardiac arrest—but fail to explain why these issues occurred or how they might be mitigated.

SAFEPATH combines advanced machine learning models with a multimodal data approach to enable a deep understanding of toxicity mechanisms, offering actionable insights to facilitate drug turnaround.

In this white paper, our Co-founder and Chief Data Science Officer Dr. Layla Hosseini-Gerami explains how our innovative platform works.