Can AI make clinical trials better?

Clinical trials are characterized by significant inefficiencies, including escalating R&D costs that haven't yielded more drug approvals, widespread timeline overruns, and high failure rates. Artificial intelligence is emerging as a key solution, promising to enhance trial design, patient recruitment, monitoring, and analysis, thereby improving efficiency and success rates. Major players like IQVIA and Tempus AI are actively integrating AI, often partnering with tech giants such as NVIDIA, though Bernstein cautions that AI's ultimate impact in this highly regulated sector remains uncertain despite the clear industry need for cost reduction and efficiency.

Analysis

The clinical trial sector is facing a severe efficiency crisis, characterized by R&D spending growth of 44% between 2012 and 2022 that has not translated into an increase in novel drug approvals. The operational inefficiencies are stark, with an estimated 80% of trials overshooting timelines and Phase 3 trials exhibiting a 54% failure rate, primarily due to insufficient efficacy. Artificial intelligence is being positioned as a transformative solution to these systemic issues, with potential applications across the entire trial lifecycle, from optimizing trial design with real-world data to accelerating patient recruitment using natural language processing. Bernstein has categorized key players into traditional CROs like IQVIA (IQV), Icon (ICLR), and Fortrea (FTRE); health-tech firms; and hybrid diagnostic and AI companies such as Tempus AI (TEM) and Caris Life Sciences (CAI). Strategic partnerships are emerging, notably between IQVIA and NVIDIA (NVDA), underscoring the convergence of healthcare and technology. However, despite heavy investment and the clear need for innovation, significant uncertainty remains. Bernstein analysts caution that AI's ultimate role is not yet determined, potentially becoming either foundational infrastructure or failing to significantly penetrate a highly regulated and historically inefficient industry.

Key Decisions for Investors

• Investors should consider prioritizing companies with distinct AI capabilities and proprietary data moats, such as hybrid players Tempus AI (TEM) and Caris (CAI), over traditional CROs, as they may be better positioned to capitalize on the efficiency trend.