BrainScriptor is an innovative tool based on artificial intelligence (AI) and machine learning (ML) designed to optimize personalized medication prescription in the treatment of depressive and anxiety disorders. Aimed at physicians (psychiatrists, neurologists and clinicians/family doctors) and institutions (hospitals, clinics and pharmaceutical laboratories), BrainScriptor integrates scientific evidence, clinical expertise and patient data to deliver accurate and efficient recommendations. It aims to improve clinical decision making, reduce errors and save time for healthcare professionals.

Role

I led product design for the tool from early discovery through launch — conducting rounds of user research with clinical prescribers, defining the information architecture, and designing the interaction model for how practitioners would review, override, and apply AI recommendations. The work required close collaboration with founders to understand what the model could and couldn't communicate confidently, and with clinical stakeholders to understand what practitioners needed to trust the output.