Client: A leading pharmaceutical company.

Objective: To create a fully functional Artificial Intelligence clinical platform that can identify personalized drug targets (including neo-antigens) and validate them. These can be used in precision medicine or to select and stratify patients in clinical trials.

Solution and outcome: Access and curate a clinical database from open and proprietary sources. Aggregated and normalized data were employed in the curation of an extensive library containing chemical, genetic, and structural information on cancer antigens per cancer type and patients’ genomic and proteomic makeup. AI was used to identify and predict integrated response levels from human immune system cells/proteins. Results were presented on an interactive dashboard with a proprietary scoring system.