As 2026 gets underway, biotech and pharma leaders make their predictions for the hottest trends in industry this year. Consistent with the pattern of last couple of years, the focus remains on artificial intelligence (AI). While many companies have shown the promise of AI in drug discovery and diagnostics, these leaders see AI taking on an even larger role in 2026—accelerating manufacturing, clinical trial data analysis, the regulatory path to drug approvals, and more.
AI Will Accelerate the Regulatory Pipeline
Pamela Tenearts is the CMO of Medable.
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Pamela Tenearts, chief medical officer, Medable
The Food and Drug Administration (FDA) and the European Medicines Agency have been moving—thoughtfully but decisively—toward a more aligned, forward-looking set of rules that do more than protect the public: They create room for responsible progress. With the EU AI Act coming into effect in the first half of 2026 and the FDA beginning to deploy generative AI tools to support and accelerate regulatory review, there will be a new regulatory position: guidance that is faster, more data-driven, and anchored in transparency, explainability, and continuous performance monitoring.
Regulators appear to be increasingly prepared to let AI handle routine, low-risk research tasks with minimal friction, while keeping firm human control over decisions that directly shape safety, ethics, and public trust. That is the right hierarchy. If they stay on this course, international coordination and iterative learning between agencies will not just keep up with AI, they will shape it. The result is substantial: more efficient drug development, lower costs, and more timely, representative access to better therapies. The challenge, which we cannot underestimate, is to ensure that the governance, safeguards, and ethical commitments evolve as quickly as the technology they aim to oversee.
AI Will Aid Clinical Trial Data Analysis and Reduce Inefficiencies
Kim Boericke is the CEO of Veristat.
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Kim Boericke, chief executive officer, Veristat
Clinical trials are all about data, and the responsible use of AI in biometrics and data operations represents a major back-office opportunity that will emerge in 2026. By automating data cleaning, anomaly detection, and statistical modeling, AI can increase the speed, insights, and precision of clinical trial data analysis and submission assembly. These efficiencies help shorten development timelines and improve data integrity.
Ultimately, AI will not eliminate the human element but will be the tool that amplifies it. The leaders in this next phase of clinical research will be those who use AI to inform decisions, not replace judgment, ensuring smarter trial design, faster activation, and more reliable data across the clinical lifecycle.
John Chinnici is the CEO of Ledger Run.
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John Chinnici, chief executive officer, Ledger Run
By targeting the administrative bottlenecks that have plagued clinical trials for decades including contracting, budgeting, and payment processing, AI will begin to demonstrate return on investments and accelerate trials significantly. Early estimates show that AI can reduce study startup timelines by 15 to 20 percent on average, saving millions in overhead costs per global trial. AI has proven it doesn’t need to design the next blockbuster molecule to transform the business of clinical research. The future of clinical trials is not just smarter science, but also smarter operations, powered by AI that quietly handles the laborious tasks fast and allow researchers to re-focus on supporting sites and patients.
AI Will Help Device and Product Research Move Faster
Mike Monovoukas is the CEO and cofounder of AcuityMD.
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Mike Monovoukas, chief executive officer and cofounder, AcuityMD
AI won’t just accelerate product innovation; it will reshape how MedTech companies demonstrate clinical and financial value. On-demand analytics will instantly quantify treatment impact, helping manufacturers prove outcomes for both clinicians and chief financial officers. Rather than relying on retrospective studies or data, AI-driven models will provide evidence on demand. For forward-thinking MedTech companies, this will mean faster adoption, confidence that they’re aligned to a buyer’s distinct needs, and a competitive edge built on transparency and measurable results.
Responses have been edited for length and clarity.
