Biomedical subjects

David Ochoa

Publications and source records attributed to David Ochoa.

3 recordsLinked to original sources

PubMed2026

Pathway-driven target prioritisation in drug discovery.

Genome-scale association studies and functional screens routinely implicate hundreds of candidate genes per disease, yet only a few will be clinically validated as drug targets. Choosing which to pursue is a central drug-discovery decision that depends on interpreting each candidate in its biological context. Curated pathway databases provide this context, while enrichment analysis applies it at scale, turning gene-level signals from genome-wide association, transcriptomic, proteomic and CRISPR studies into mechanistic hypotheses for prioritisation. This review examines how pathway-based methods inform target prioritisation, the databases and tools available for this purpose, and why pathway co-membership should be viewed as a starting point for validation rather than as evidence of causal involvement.

CRISPR↗

PubMed2025

Associations on the Fly, a new feature aiming to facilitate exploration of the Open Targets Platform evidence.

MOTIVATION: The Open Targets Platform (https://platform.opentargets.org) is a unique, comprehensive, open-source resource supporting systematic identification and prioritisation of targets for drug discovery. The Platform combines, harmonizes and integrates data from >20 diverse sources to provide target-disease associations, covering evidence derived from genetic associations, somatic mutations, known drugs, differential expression, animal models, pathways and systems biology. An in-house target identification scoring framework weighs the evidence from each data source and type, contributing to an overall score for each of the 7.8M target-disease associations. However, the old infrastructure did not allow user-led dynamic adjustments in the contribution of different evidence types for target prioritisation, a limitation frequently raised by our user community. Furthermore, the previous Platform user interface did not support navigation and exploration of the underlying target-disease evidence on the same page, occasionally making the user journey counterintuitive. RESULTS: Here, we describe 'Associations on the Fly' (AOTF), a new Platform feature-developed with a user-centred vision-that enables the user to formulate more flexible therapeutic hypotheses through dynamic adjustment of the weight of contributing evidence from each source, altering the prioritisation of targets. AVAILABILITY AND IMPLEMENTATION: The codebases that power the Platform-including our pipelines, GraphQL API, and React UI-are all open source and licensed under the APACHE LICENSE, VERSION 2.0. You can find all of our code repositories on GitHub at https://github.com/opentargets and on Zenodo at https://zenodo.org/records/14392214. This tool was implemented using React v18 and its code is accessible here: (https://github.com/opentargets/ot-ui-apps). The tools are accessible through the Open Targets Platform web interface (https://platform.opentargets.org/) and GraphQL API (https://platform-docs.opentargets.org/data-access/graphql-api). Data is available for download here: (https://platform.opentargets.org/downloads) and from the EMBL-EBI FTP: (https://ftp.ebi.ac.uk/pub/databases/opentargets/platform/).

Software↗

PubMed2025

Lit-OTAR framework for extracting biological evidences from literature.

SUMMARY: The lit-OTAR framework, developed through a collaboration between Europe PMC and Open Targets, leverages deep learning to revolutionize drug discovery by extracting evidence from scientific literature for drug target identification and validation. This novel framework combines named entity recognition for identifying gene/protein (target), disease, organism, and chemical/drug within scientific texts, and entity normalization to map these entities to databases like Ensembl, Experimental Factor Ontology, and ChEMBL. Continuously operational, it has processed over 39 million abstracts and 4.5 million full-text articles and preprints to date, identifying more than 48.5 million unique associations that significantly help accelerate the drug discovery process and scientific research >29.9 m distinct target-disease, 11.8 m distinct target-drug, and 8.3 m distinct disease-drug relationships. AVAILABILITY AND IMPLEMENTATION: The results are accessible through Europe PMC's SciLite web app (https://europepmc.org/) and its annotations API (https://europepmc.org/annotationsapi), as well as via the Open Targets Platform (https://platform.opentargets.org/). The daily pipeline is available at https://github.com/ML4LitS/otar-maintenance, and the Open Targets ETL processes are available at https://github.com/opentargets.

Drug Discovery↗