Guides
The right tool for the job: General AI vs clinical trial AI
The clinical trials industry is at an operational inflection point. Despite decades of process refinement, drug development timelines have continued to lengthen, and manual workflows still account for a significant portion of skilled operator time across key trial functions. The emergence of large language model-based AI platforms has introduced a new variable into this equation, with multiple vendors now positioning their technology as a solution to these structural inefficiencies.
Two categories of vendors appear frequently in sponsor and CRO evaluations. The first are general-purpose AI platforms, whose large language model capabilities have become some of the most widely benchmarked in the industry. The second are purpose-built clinical technology platforms with an established operational presence across decentralized and hybrid trial environments.
Both have made substantive investments in life sciences AI in 2026. Their approaches, however, differ significantly in architecture, regulatory readiness, and deployment scope. This analysis examines those differences to help sponsors and CROs assess which type of platform is better suited to their operational requirements.
Back to Basics: Remote patient monitoring
Remote patient monitoring programs and technologies are becoming increasingly popular, backed by growing clinical evidence showing numerous benefits to patients and providers. While remote patient monitoring (RPM) isn’t new, it’s evolving quickly due to the regulatory push to expand access to care during the COVID-19 pandemic. Coupled with the fact that the digital health market is poised to more than double by 2026, providers and patients have a greater ability to track vitals between visits, and both centralized and decentralized clinical trials rely on remote data collection now more than ever. While there is tremendous potential upside, some barriers and risks are inherent in this digital process. Human-centered design and strategic implementation can ensure that RPM in clinical trials is both beneficial and cost effective.