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

Area of Science:

• Pharmaceutical Research
• Drug Discovery
• Biotechnology

Background:

• The pharmaceutical industry struggles to translate data into R&D efficiency, leading to a drug development innovation crisis.
• Traditional preclinical research often introduces drug candidates with low probabilities of patient success into the development pipeline.

Purpose of the Study:

• To review common issues in pharmaceutical R&D efficiency and propose solutions.
• To introduce the Human Data-driven Discovery (HD³) paradigm as a strategy to overcome the innovation crisis.

Main Methods:

• Analysis of industry- and science-related factors contributing to R&D inefficiency.
• First principles analysis to identify critical issues in preclinical research.
• Review of proof-of-concept applications for the HD³ paradigm.

Main Results:

• Preclinical research is identified as a bottleneck, front-loading the pipeline with non-viable candidates.
• The HD³ paradigm offers a strategic integration of existing data and technology for improved outcomes.
• HD³ applications demonstrate success in drug safety, repositioning, combination therapy design, and pandemic response.

Conclusions:

• Rectifying the innovation crisis requires a shift from traditional preclinical models.
• Adopting a Human Data-driven Discovery (HD³) approach is crucial for enhancing drug discovery.
• Innovators must lead the transition to human-focused, systems-based drug discovery and research.