BioX Knowledge Discovery Platform
Recommendations on the right drug treatment for the right patient at the right time are prioritized based on safety and efficacy insights. BioXplor's team applies natural language processing and machine learning to extract insights from unstructured and structured data. Patient data is combined with third party safety and efficacy databases together with BioXplor's core knowledge-base which consists of billion's of structured sentences from over 35M unstructured biomedical publications and clinical trials reports. Unstructured data is machine read using over 30 proprietary biomedical ontologies to uncover over 150M entity relationships between drugs, adverse events, diseases, genes, variants, pathways, biological processes, molecular functions, tissues, and cell types, while the entity relationship types include causation, interaction, gene expression, mechanism of action, and much more.