Harnessing public domain data to discover and validate therapeutic targets

ABSTRACT

Introduction: Discovering, developing and validating new disease treatments is a challenging and time-consuming endeavor. Successful drug discovery hinges on selecting the best drug targets with relevance to human disease and evidence that modulating them will be beneficial for patients. Open data initiatives are increasingly placing such knowledge into the public domain.

Areas covered: In this review, the authors discuss emerging resources such as Open Targets which integrate key information to prioritize target-disease connections. Researchers can use it, along with other resources, to select potential new therapeutic targets to initiate drug discovery projects. They also discuss public resources such as DrugBank and ChEMBL that offer potential tools to interrogate these targets.

Expert opinion: In our opinion, publically available resources are democratizing and connecting information, enabling disease experts to access and prioritize targets of interest in ways that were not possible a few years ago. Moreover, there are several modalities in addition to small molecule perturbation to modulate a target’s activity. Drug discovery scientists can now utilize these new resources to simultaneously evaluate a much larger number of targets than previously possible.

KEYWORDS:

• Bioinformatics
• computational biology
• drug discovery
• public domain data
• target identification
• target validation

Article highlights

• Open data initiatives are placing vastly more information related to drug discovery in the public domain

• Open Targets platform brings together target-disease information from genetics, somatic mutations, drugs, pathways, expression, text mining and animal models to assist target discovery

• Detailed information from Open Targets and from many other sources should be considered when evaluating a target

• Druggability, the existence of tool compounds, and other ways to modulate the target are important considerations

• Assays and models relevant to the disease, while not completely predictive of clinical trial success, have an important role to play in target validation

This box summarizes key points contained in the article.

Acknowledgments

The authors appreciate the insightful comments and suggestions provided Mark Hurle and Gautier Koscielny, and by the anonymous reviewers.

Declaration of interest

P Agarwal, WC Reisdorf and P Sanseau are all employees of GlaxoSmithKline (GSK) while N Chhugani was an intern at GSK in 2016. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Additional information

Funding

The authors are supported by GlaxoSmithKline.