Clinical trial recommendations using Semantics-Based inductive inference and knowledge graph embeddings.

Objective: Designing a new clinical trial entails many decisions, such as defining a cohort and setting the study objectives to name a few, and therefore can benefit from recommendations based on exhaustive mining of past clinical trial records. This study proposes an approach based on knowledge graph embeddings and semantics-driven inductive inference for generating such recommendations.

Method: The proposed recommendation methodology is based on neural embeddings trained on first-of-its-kind knowledge graph constructed from clinical trials data.

Clinical genomicist workstation.

The use of NextGen Sequencing clinically necessitates the need for informatics tools that support the complete workflow from sample accessioning to data analysis and reporting. To address this need we have developed Clinical Genomicist Workstation (CGW). CGW is a secure, n-tiered application where web browser submits requests to application servers that persist the data in a relational database.