Identification of pharmacodynamic biomarker hypotheses through literature analysis with IBM Watson.

ABSTRACT:

Background

Pharmacodynamic biomarkers are becoming increasingly valuable for assessing drug activity and target modulation in clinical trials. However, identifying quality biomarkers is challenging due to the increasing volume and heterogeneity of relevant data describing the biological networks that underlie disease mechanisms. A biological pathway network typically includes entities (e.g. genes, proteins and chemicals/drugs) as well as the relationships between these and is typically curated or mined from structured databases and textual co-occurrence data. We propose a hybrid Natural Language Processing and directed relationships-based network analysis approach using IBM Watson for Drug Discovery to rank all human genes and identify potential candidate biomarkers, requiring only

SUBMITTER: Hatz S 

PROVIDER: S-EPMC6453528 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature