How a unique public-private partnership is transforming target identification through systematic data integration and genetic evidence
Every year, pharmaceutical companies invest billions into research and development, yet only one in ten drugs that enter clinical trials will ultimately receive approval 9 . The majority fail in late-stage development due to insufficient efficacy or safety concerns — problems that often trace back to an incomplete understanding of disease biology at the very beginning of the process.
What if we could use the power of genetics and big data to make better choices about which targets to pursue before ever starting drug development?
This fundamental question sparked the creation of Open Targets, a unique pre-competitive partnership that brings together expertise from academic institutions and pharmaceutical companies. For the past decade, this consortium has worked to systematically improve how we identify and prioritize drug targets, leveraging recent developments in genomics, genetics, and bioinformatics to build an evidence-based foundation for the future of medicine 3 5 .
Open Targets is a public-private partnership that combines the complementary strengths of its member institutions — including Biogen, EMBL's European Bioinformatics Institute (EMBL-EBI), GlaxoSmithKline, and the Wellcome Trust Sanger Institute 5 .
Unlike traditional competitive research models, this consortium operates on a pre-competitive basis, recognizing that improving the fundamental understanding of disease biology benefits all stakeholders in the healthcare ecosystem.
Academic and industry partners working together to solve fundamental challenges in target identification.
At the heart of Open Targets is its flagship informatics resource — the Open Targets Platform (https://platform.opentargets.org). This freely available, open-source tool aggregates and integrates data from over 20 public sources to help scientists identify and prioritize potential drug targets for further investigation 2 9 .
Starting with a specific gene or protein (like 'PDE4D') to find associated diseases (such as asthma).
Starting with a particular disease to identify potentially druggable targets 5 .
Early in its development, Open Targets focused primarily on establishing associations between targets and diseases. However, the consortium recognized that a simple association isn't sufficient to build a drug discovery program upon.
"When choosing a target as the foundation of a drug discovery programme, the association must be evaluated in the context of treatment of the disease to specify how and where the candidate drug will work to alleviate or cure the condition. In other words, a drug discovery programme should be based on a full therapeutic hypothesis" 3 .
This insight led to the development of a comprehensive framework for constructing complete therapeutic hypotheses:
Modulation of target T, with drug modality M, with direction of effect E, in cell type C, in cell state Cs, in tissue Ti, will be beneficial for Disease D, for patients of subtype S, and/or disease stage Ds. 3
This systematic approach considers not just whether a target is associated with a disease, but precisely how, where, and when it should be modulated to achieve therapeutic benefit while minimizing safety concerns.
Genetic evidence has emerged as a particularly powerful component for building confidence in potential drug targets. A 2024 analysis found that drug development programs with supporting genetic information are more likely to proceed successfully through clinical development 6 . In fact, the study indicates that genetic evidence halves the odds of early clinical trial stoppage due to efficacy or safety concerns 6 .
Open Targets has expanded its genetic evidence considerably in recent years, incorporating:
from genome-wide association studies (GWAS)
through gene-level burden tests
in cancer from resources like the Cancer Gene Census
from clinically curated resources
| Data Source | Type of Evidence | Key Insights |
|---|---|---|
| GWAS Catalog | Common genetic variants associated with diseases | Identifies genomic regions linked to disease risk |
| Gene Burden | Rare variant collapsing analyses | Reveals effects of rare protein-altering variants |
| ClinVar | Clinically interpreted genetic variants | Provides clinical significance of variants |
| Genomics England PanelApp | Expert-curated gene-disease relationships | Captures diagnostic-grade gene-disease associations |
In 2024, Open Targets researchers published a crucial study in Nature Genetics that explored the relationship between genetic evidence and clinical trial outcomes 6 . The research team recognized that clinical trial failures represent valuable learning opportunities, but accessing information about failed trials is challenging due to publication biases toward successful results.
The research team developed an innovative approach that combined natural language processing with genetic evidence evaluation:
Created a machine learning model to classify free-text stoppage reasons from 28,842 clinical trials into 17 categories 6
For each trial, evaluated the strength of genetic evidence linking the drug target to the disease using 13 sources available in the Open Targets Platform 6
Analyzed whether trials stopping for negative reasons (safety or efficacy concerns) had different levels of genetic support compared to successful trials
Using machine learning to classify stoppage reasons from unstructured data
The findings were striking: clinical trials that stopped for negative reasons were significantly less supported by genetic evidence 6 . In fact, the presence of genetic evidence halved the odds of early trial stoppage 6 .
| Trial Characteristic | With Genetic Support | Without Genetic Support |
|---|---|---|
| Odds of early stoppage | Halved | Doubled |
| Stoppage due to efficacy | Less likely | More likely |
| Stoppage due to safety | Less likely | More likely |
| Likelihood of approval | Higher | Lower |
"Together with this new research, genetic support is clearly both predictive of clinical trial progression and protective of early trial stoppage. This is strong support for Open Targets' founding aim to use the information generated by genetic sequencing and genomics studies to systematically improve the selection of targets for drug development" — David Ochoa, Open Targets Platform Coordinator 6 .
The Open Targets ecosystem provides researchers with a comprehensive set of tools and resources to support systematic drug target identification and prioritization.
| Tool/Resource | Function | Application in Research |
|---|---|---|
| Open Targets Platform | Centralized evidence portal | Aggregates genetic, genomic, and chemical data for target-disease associations |
| Open Targets Genetics | Genetic association portal | Focuses specifically on genetic evidence for target-disease links |
| MCP Server | AI integration tool | Allows seamless connection between AI applications and Open Targets data |
| Evidence Validation | Manual curation processes | Ensures quality and accuracy of automated data integrations |
| Research Chemicals | 1,3-Dibromo-2-(4-bromophenoxy)benzene | Bench Chemicals |
| Research Chemicals | Potassium glycerophosphate trihydrate | Bench Chemicals |
| Research Chemicals | Trichloro(trimethylamine)boron | Bench Chemicals |
| Research Chemicals | Zolamine hydrochloride | Bench Chemicals |
| Research Chemicals | 2,4,6-Triphenylpyrylium perchlorate | Bench Chemicals |
As Open Targets moves forward, the focus is shifting toward even more precise therapeutic hypotheses. The consortium is working to incorporate additional layers of context, including:
To understand target expression in specific cell types and states
To account for disease progression and stage-specific interventions
To consider targets in the context of their interacting partners
"The fundamental tenet of pharmacology is that a drug can be identified that specifically interacts with a target molecule to modulate a physiological process and thus alter the course of a disease" 5 .
By providing transparent access to integrated evidence and tools, Open Targets empowers researchers across academia and industry to build stronger foundations for their drug discovery programs. In doing so, this decade-long partnership continues to work toward a future where more medicines reach patients by making the difficult journey of drug development just a little bit easier and a lot more predictable.