3 Clinical Research Attorneys Talk 2026 Trends

As told to Clinical Leader Executive Editor Abby Proch

The new year is here, and 2025 is fully in the rearview. Around this time, we often hear clinical researchers forecasting the next big thing for the year, and you can catch up on that in these two articles — Researchers Want A Design Shake-Up In 2026 and How Should Scientific Focus Change In 2026 Researchers Weigh In.

Less frequently heard but just as insightful are the perspective of life sciences lawyers, whose external perspective allows them to see trends from outside and as they affect operations across sites, sponsors, and their supporting partners.

Here, these legal experts share what they see happening in the year ahead — and what should remain firmly in the past.

Jiayan Chen, health and life sciences partner, McDermott Will & Schulte

To reduce barriers to clinical research and expedite the enrollment of eligible study subjects, archaic HIPAA regulations regarding the use of health information should be left behind.

Current legal frameworks for the use and sharing of medical records and other data necessary to find study subjects are ambiguous and reflect the days when most health data was on paper. Research stakeholders, including CROs, other study vendors, sites, and providers whose patients may be eligible for studies, face the undesirable choice of either taking on legal risk or implementing burdensome privacy pathways to conduct prescreening and recruitment activities.

In an ideal world, these stakeholders would have clearer guidance under HIPAA so that they can focus on the important task of accelerating clinical research and bringing study opportunities to patients.

Kate Gallin Heffernan, academic and clinical research attorney, Epstein Becker Green

2025 was a year of fast-paced change for science and clinical innovation, with both positive and negative consequences. 2026 brings the opportunity to embrace new trends that work and to say goodbye to those that did not. Trends clinical research should "say goodbye" to in 2026:

• An expectation of the availability of federal funding. If there was one theme for clinical research in 2025, it was a constriction in the federal funding that supports both the upstream early development of funding as well as clinical trials. In 2026, a resurgence of creative partnerships between industry and academia (and healthcare investors) should be explored to ensure continued diversified resources to support scientific innovation.
• Administrative inefficiency. In the new year, clinical research should lean into AI solutions to reduce the need for human capital expenditure on purely administrative and systems operations, both to allow for increased focus by research teams on the strategy and execution of the research, as well as to reduce the cost of trials. Identifying those tools that strike an appropriate balance between introducing efficiency and maintaining appropriate human involvement (the "human in the loop") will be key to the successful deployment of these new technologies.
• Lack of reproducibility and/or scientific integrity. 2025 (and the preceding five years) saw an unprecedented number of allegations of data manipulation (falsification and fabrication) in the published literature, fueled in part by online "integrity sleuths" deploying AI tools to search the literature for image duplications. While the uptick in public allegations certainly does not necessarily establish an uptick in problematic research practices, there has been an ongoing national (and international) conversation about the lack of reproducibility in science, including remediation efforts promoted by the NIH and other international organizations. With the Office of Research Integrity's new regulations on research misconduct becoming applicable on January 1, 2026, the time is ripe for the research community in the United States and abroad to work collectively to elevate the culture of research data integrity and validity.

Robert J. Paradiso, Esq., Lowenstein Sandler LLC  

Clinical trials are complex, expensive, and data‑heavy, with strict eligibility requirements. AI helps by improving protocol design, shortening recruitment, and enabling real‑time analytics on trial data. AI is already changing how clinical trials are designed, enrolled with patients and analyzed, and in 2026, the advantage will go to sponsors who more fully embrace AI by holding themselves accountable with rigorous oversight and validation.

What To Leave Behind In 2025

• Hunch‑driven protocol design. Instead of relying on intuition, sponsors need to use AI to mine prior trials for dosing, sample size, and endpoints in order to avoid costly redesigns and failures.
• Inefficient recruitment. Algorithmic screening against eligibility criteria can expand qualified pools and shorten timelines. It can also help prospective participants to find the matching trials.
• Traditional enrollment. Digital twins (“virtual patients” that reflect personal characteristics in a high degree of specificity) can simulate outcomes to reduce enrollment burden and de‑risk exposure while preserving the integrity of the trial.
• Data bottlenecks. AI can extract key facts from raw clinical documents and support real‑time signal detection to identify endpoint attainment and responsive subpopulations.

What 2026 Should Bring

• Risk‑based AI governance. Oversight and control measures need to be prioritized to ensure that AI does not cause harm throughout the clinical trial process. Regulators expect validation, monitoring, and clear accountability for AI used across the life cycle. Sponsors need to build these controls into their systems to assure data integrity and safety.
• Privacy‑by‑design implementation. Data protection measures need to be a primary component in AI systems and not an optional add on. Sponsors need to assure de‑identification techniques and data minimization across the entire data transfer cycle, e.g., internal teams, CROs, and vendors.
• Transparency. Rather than “black box” models, there needs to be traceable and explainable logic for all clinical decisions made by AI, with human checkpoints for quality assurance and validation.
• Responsible outsourcing. CROs and other providers using AI need to be held to sponsor‑level requirements for bias assessment, validation, security, privacy, and transparency throughout the process. Oversight and enforcement need to be standard practice. 

Sponsors that utilize AI in the design, recruitment, and analysis of clinical trials along with responsible governance, oversight, transparency, and accountability will have an edge in 2026 and beyond.