Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

Rewiring Drug Research and Development through Human Data Driven Discovery (HD3)

Version 1 : Received: 12 May 2023 / Approved: 12 May 2023 / Online: 12 May 2023 (12:18:59 CEST)

A peer-reviewed article of this Preprint also exists.

Jackson, D.B.; Racz, R.; Kim, S.; Brock, S.; Burkhart, K. Rewiring Drug Research and Development through Human Data-Driven Discovery (HD3). Pharmaceutics 2023, 15, 1673. Jackson, D.B.; Racz, R.; Kim, S.; Brock, S.; Burkhart, K. Rewiring Drug Research and Development through Human Data-Driven Discovery (HD3). Pharmaceutics 2023, 15, 1673.

Abstract

In an era of unparalleled technical advancement, the pharmaceutical industry is struggling to transform data into increased research and development efficiency, and as a corollary, new drugs for patients. Here, we briefly review some of the commonly discussed issues around this counterintuitive innovation crisis. Looking at both industry and science related factors, we posit that traditional preclinical research is front-loading the development pipeline with data and drug candidates that are unlikely to succeed in patients. Applying a first principles analysis, we highlight the critical culprits and provide suggestions as to how these issues can be rectified through pursuit of a Human Data-driven Discovery (HD3) paradigm. Consistent with other examples of disruptive innovation, we propose that new levels of success are not dependent on new inventions, but rather the strategic integration of existing data and technology assets. In support of these suggestions, we highlight the power of HD3, through recently published proof-of-concept applications in the areas of drug safety analysis and prediction, drug repositioning, rational design of combination therapies and the global response to the Covid19 pandemic. We conclude that innovators must play a key role in expediting the path to a largely human focused, systems-based approach to drug discovery and research.

Keywords

Systems Pharmacology; Polypharmacology; Adverse Events; Drug Discovery; Functional genomics; Disease Modeling; Network analysis; Innovation

Subject

Medicine and Pharmacology, Medicine and Pharmacology

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