The technological blind spot: Why pharma is missing the human element

Area of Science:

• Pharmaceutical industry
• Behavioral science
• Artificial intelligence (AI)

Background:

• Persistent underperformance in the pharmaceutical industry, characterized by high clinical trial dropout rates (30-70%) and significant sales variability (up to 300%).
• Under-management of behavioral factors as a key contributor to the gap between technological investments and expected outcomes in research, development, and commercialization.
• Constraints on artificial intelligence (AI) impact due to barriers like patient nonadherence and low innovation uptake.

Purpose of the Study:

• To propose a behavioral science framework to address underperformance in the pharmaceutical industry.
• To demonstrate how behavioral science complements technological approaches in clinical development and commercial execution.
• To highlight the necessity of integrating behavioral science for realizing the full value of AI-enabled innovation.

Main Methods:

• Development of a three-part behavioral science framework: behavioral diagnosis, cocreation of behavioral solutions, and evidence-based implementation.
• Application of the framework across clinical development and commercial execution phases.
• Analysis of how behavioral interventions address barriers to AI effectiveness.

Main Results:

• The proposed framework offers a structured approach to managing behavioral factors.
• Integration of behavioral science enhances the translation of technological investments into tangible outcomes.
• Behavioral science is shown to be a critical component for overcoming AI limitations.

Conclusions:

• Behavioral science is essential for overcoming persistent challenges in the pharmaceutical sector.
• A systematic behavioral approach is a prerequisite for unlocking the full potential of artificial intelligence (AI) in pharmaceuticals.
• Integrating behavioral science alongside technology is key to improving R&D and commercialization success.