Kevin Williams, EVP and Chief Strategy Officer, Ledger Run  

Next year will finally be the year of the site: As sponsors face growing pressure to attract and retain high-performing research sites, 2026 will likely bring a renewed focus and greater investment in strategies designed to support and empower sites. These efforts will range from reassessing sourcing models (CRO vs. FSP vs. in-house) to adopting more flexible and responsive engagement tools. Unfortunately, many sites remain skeptical of new “support” systems that often add complexity rather than reduce it. A recent Tufts Center for the Study of Drug Development Impact Report found that 70% of global investigative site staff believe trials have become significantly harder to manage over the past five years. So, while sponsors and CROs share a commitment to improving transparency and trial execution, it’s essential that any changes minimize the operational burden on sites. The next wave of advancement will leverage technologies like AI to streamline operations and enhance visibility without disrupting the natural flow of daily site activities.  

Anita Phung, Research Physician, Lindus Health  

In 2026, I’m hopeful that clinical research will begin moving from simply recognizing bias to actively designing it out of studies: Biased data doesn’t just skew results, it quietly feeds into the AI tools we build, widening gaps in care. My hope is that sponsors adopt more equity-focused study designs, improve the way health data is coded and captured and validate AI models across truly diverse patient groups. Taking these steps would help ensure that emerging technologies strengthen care for everyone, not just the populations easiest to study.  

Sean Tobyne, PhD, Vice President of Data Science & Analytics, Linus Health  

Drug discovery teams developing brain-health therapies must increasingly turn to digital health tools as precision biomarkers and AI-driven cognitive assessments reshape how we identify and enroll patients for clinical trials: The industry’s biggest opportunity lies in detecting disease long before symptoms appear, enabling more targeted recruitment and lower trial attrition. Perhaps most importantly, drugs must transition to market with labels supported by digital biomarkers that enable early intervention not symptom management.  

Aaron Galaznik, Chief Medical Officer, MDClone  

One of the most meaningful trends is the rise of privacy-preserving technologies that enable cross-site collaboration and real-world evidence generation with fewer legal and operational barriers: Synthetic data and modern data engineering pipelines allow researchers to safely experiment, replicate analyses, and align on trial readiness. This accelerates discovery while improving the patient and site experience.  

Michelle Longmire, Co-Founder and CEO, Medable  

Clinical development is bottlenecked by manual processes: Clinical Research Associates (CRAs) are overworked, often experiencing burnout. In 2026, Agentic AI will unlock the keys for improved clinical development, starting by alleviating within trial white space and empowering clinical research associates to focus more on sites and the trial operations rather than administrative tasks. To achieve value, agents must be measured against the outcomes they deliver, including end-to-end autonomy. In 2026, we will see agents begin to deliver extremely valuable aspects of the value chain, ultimately enabling full clinical development autonomy with as needed human oversight for key activities.  

Orla Cloak, CEO, Minaris Advanced Therapies  

We’re reaching a point where the next wave of progress in advanced therapies depends on breaking down the silos that have slowed development for years: In 2026, sponsors will be looking for partners who can bring science, manufacturing, and analytics together in a single, connected workflow instead of three separate handoffs. When development, production, and testing are built to evolve together from day one, integration becomes much more than a way to save time. It becomes a new, smarter model for how therapies are created and delivered to patients.  

Lars Hartvig Kristiansen, Vice President of Product Innovation and Strategy, Molecular Devices  

Recent shifts in federal budgets, evolving policy priorities, and regulatory complexities have introduced new challenges for academic researchers with increased uncertainty: It’s never been more important that the life sciences industry partners with academia on projects to truly understand the needs and research that these critical institutions are driving. When close collaboration is done right, private companies are able to gain unique perspectives on future scientific needs and align their product development with future research priorities. In 2026, Molecular Devices continues to deepen its academic partnerships to drive innovation that simplifies complex workflows, such as the industrialization of human-relevant assays. As a result, we will introduce new tools and purpose-built products designed to accelerate transformative breakthroughs in the lab.  

Lidia Bernik, MHS, MBA, President of Curation Solutions, MRO  

In 2026, the real opportunity in clinical research will come from treating clinical data not as a guarded asset but as a shared fuel between healthcare delivery and life sciences: Health systems are sitting on operational and real-world insights that life sciences companies need, and life sciences teams bring the analytical depth that can turn that data into quicker, more informed decisions. When those strengths meet, everyone moves faster. The upside will be significant. Better collaboration means shorter trial timelines, more representative study populations, and a development ecosystem that actually learns from itself.  

Heather Grey, SVP and GM of RWD and Clinical Trials, Omega Healthcare  

In the next era of clinical research, AI won’t replace the human backbone—it will strengthen it: The future of real-world data will belong to those who pair human expertise with intelligent automation to achieve true precision, not just scale. As AI matures, it will turn today’s fragmented data into a living, learning infrastructure, one that delivers usable, auditable, and actionable insights for every site and every patient. Precision medicine will finally accelerate when precision data becomes the norm, not the exception.  

Sebastien Coppe, CEO, One2Treat  

Multidimensional analyses will redefine what it means to design a patient-centric clinical trial: Sponsors will move beyond single endpoint thinking and adopt integrated frameworks that weigh efficacy, safety, quality of life, and patient-defined priorities in one coherent evidence model. This shift will be driven by tools that capture patient input early and translate those insights into structured, multi-attribute evaluations of treatment value. Regulators and payers will increasingly expect these richer outcome profiles, pushing companies to demonstrate not only whether a therapy works, but how it affects the lived experience of patients across several meaningful dimensions. Trials built on multidimensional analysis will be more relevant to patients, more compelling to decision makers, and more predictive of real-world performance. By the end of 2026, this approach will emerge as a defining marker of modern, patient-focused drug development.  

Vibhor Gupta, Founder and CEO, Pangaea Data  

For clinicians, it is essential to ensure that patients receive the most appropriate care, based on established guidelines, scientifically validated evidence, and the clinician’s assessment of each patient’s journey and trajectory: Determining the most suitable next step—whether a diagnostic test, therapy, clinical trial, monitoring, or a combination of these—is therefore a core part of clinical practice. However, such assessments are limited by time, as well as the complexities of patient data, guidelines, trial protocols and available knowledge. AI driven approaches have successfully demonstrated the ability to process information from across these dimensions, helping clinicians make appropriate decisions within their limited time, without adding additional burden on them or the patients.  

As we go into 2026, we will see increased adoption of such AI approaches, which will help pharmaceutical companies move away from ad-hoc transactional approaches limited to one clinical trial at a time (which have struggled to succeed as they compete with existing priorities and resources at health systems). These approaches will enable collaboration with clinicians and IT teams at health systems in a more strategic manner, with a longer-term and stable view, leading to success in terms of patients benefiting from relevant trials and treatments.  

Raviv Pryluk, Co-founder and CEO, PhaseV  

Embrace AI now or be left behind: Clinical sponsors are already using AI to optimize site selection, enable real-time trial monitoring, and run millions of virtual design simulations in minutes, all to maximize success rates and efficiency. In just a few years, the industry will be divided into two camps: those who embraced AI will be celebrating progress, while those who didn’t will look back and ask, “Why on earth did we wait so long?” The transition to AI is no longer optional, it is the defining generational shift for pharma advancement.  

Graham Clark, CEO, Phastar  

Change is constant in the CRO industry: The macro-economic environment continues to put pressure on Sponsors to deliver pipelines faster and in a more cost-effective way. New technologies are transforming study conduct, AI is accelerating workflows, smaller biopharma and biotech companies are taking a larger share of the pipeline, and complex therapeutics are becoming increasingly common. Together, these shifts are reshaping what sponsors expect from their CRO partners. Max scale is becoming less of a defining feature, with specialism and agility becoming paramount. Sponsors now seek strategic partners with the specialized expertise needed to help them harness emerging technologies effectively. They want flexible service models built for a more complex clinical trial environment, along with real-time, user-friendly data tools that enable faster, more informed, decision-making. At the same time, sponsors need to rethink how they cultivate strong, innovation-driven partnerships with specialist CROs that can deliver both quality and agility. In 2026 and beyond, “good enough” will no longer be adequate. Flexible, agile, and fully aligned partners will be key to delivering the expertise and insight sponsors need.   

Gen Li, Founder and President, Phesi  

2026: The year digital twins finally hit the mainstream: After years of experimentation, 2026 will mark the year digital twins move from pilot to practice in clinical development. Throughout 2025, sponsors have increasingly explored how digital twin technology can optimise protocol and trial design, reduce costly amendments, and accelerate timelines. Yet uncertainty around regulation for digital trial arms has slowed broader adoption. That’s now changing. Regulators including the FDA are expanding their AI frameworks, finalizing risk-based guidance and credibility assessments to ensure tools are safe and effective in clinical development. This will create new opportunities to integrate digital twins into trial design and execution. To unlock the full value of digital twins, sponsors must earn regulatory trust through rigorous validation, ethical data governance, and clear documentation. Continued collaboration and feedback loops between regulators, sponsors and technology partners will be essential to ensure digital twins deliver on what matters most: faster, more patient-centric and more equitable clinical trials. 

Gilad Almogy, Founder and CEO, Ultima Genomics  

Unlike physics, which has the language of math, cells and biology do not have a language today due to their immense complexity: This is where AI and machine learning can have an impact. As we move into 2026, we expect hypothesis generation on how cells behave to shift from equation-first theorizing to foundational data-set generation that can better test and inform hypotheses and fuel investment into model and algorithm development, data pipelines, and data generation standards.  

Steve Rosenberg, CEO, uMotif   

As I ponder the next year, it is impossible not to speak of AI: It is all the talk in all parts of our life with major investments in datacenters, hardware, and software to serve both businesses and consumers. But at the end of the day, it is a tool, albeit a very sophisticated and powerful tool, but a tool, nonetheless. At uMotif, we are applying AI to make us more efficient, more consistent, and to deliver the highest quality for our customers. Remembering that we operate in a highly regulated world (thank goodness), we make sure that we are building AI assistants where the human has the last say and is responsible for the trial’s integrity. I believe that AI will have a sweeping impact on the recruitment for trials, the set-up for trials, and the execution of trials, mostly around data management and monitoring. It should improve timelines and efficiencies if used correctly. I also fear that AI will be used for evil.  We have already seen fabricated reports coming out of MAHA (Make America Healthy Again) efforts about childhood diseases that are completely false and can have a significant impact on our country’s health and well-being. These reports cite non-existent references that appear believable.  Will that type of thing have an impact on the diseases that are researched? Just like social media is a great tool for bringing people together in communities, it has also been a place where bad actors have a voice, people are unknowingly influenced, and hatred has spread. As AI takes hold in our business and our lives, it is extremely important that we take care and use the technology for good and resist the bad.  

William Kuan, Health Care and Life Sciences Strategic Advisor, SAS  

Multimodal RWD becomes the rule, not the exception: Leveraging multimodal data is rapidly becoming standard practice in real-world evidence generation, providing a better understanding of patient populations by seamlessly integrating structured electronic medical record data, unstructured clinical progress notes, medical imaging, wearables, patient-reported outcomes, genomics and social determinants of health. The evolution of LLMs will finally solve decades-old interoperability challenges by speeding the data standardization process or even the direct understanding of the heterogeneous data sources.  

Allison Cuff Shimooka, Chief Operating Officer, TransCelerate BioPharma  

Regulatory turbulence will test global markets: “Regulatory uncertainty will intensify in 2026, and it will manifest differently by region. In the U.S., FDA leadership churn and talent flight could slow approvals and guidance. In Europe, ongoing trial outmigration and delays around reforms like the Biotech Act threaten long-term innovations. Companies will need to navigate these dynamics carefully while keeping their focus on delivering therapies to patients.”  

Jim Reilly, Executive Vice President of Global Strategy, Veeva  

Clinical trial data flow will advance recruitment and improve patient access and experience: The flow of clinical data between sites and sponsors will yield faster, more efficient trials. Study information will go straight to physicians to connect their patients with relevant research. New embedded AI will connect trial data between sponsors and sites so that physicians can search treatment and trial options based on a patient’s conditions or test results. This direct-to-physician approach will reduce the industry’s reliance on sites to find study participants to meet recruitment goals sooner and improve patients’ access to clinical trials. With less burden from patient recruitment requirements and modern technology, sites will see the promise of eliminating paper and manual source data verification (SDV) for clinical research associates (CRAs) become a reality. eSource tools will better connect upstream and downstream clinical data sources, first with EHRs so that patient health data can merge more efficiently with trial data. When connected with EDC, source forms will be defined by a trial definition so data can flow faster, and with more clarity, to the sponsor. This data flow will streamline study visits for patients and advance trials for sites and sponsors.  

Patrick Flanagan, CEO, Veristat   

Clinical trials in 2026 will undergo a critical adjustment period as the current administration’s policies reshape the broader life sciences landscape: Tariffs on imported pharmaceuticals and medical components, coupled with rhetoric about bringing trials and manufacturing “back home,” are already prompting sponsors and service providers to re-evaluate their global footprints. While the administration’s intent is to strengthen domestic production and patient participation, these measures introduce new cost pressures and complexities that could ripple through the clinical research ecosystem. The impact may be indirect but meaningful—affecting everything from trial supply chains to site-selection strategies. At the same time, the focus on domestic economic growth and potential incentives for U.S.-based research could create opportunities for CROs, site networks, and sponsors that have invested in U.S. infrastructure or flexible, informed trial capabilities. Companies capable of efficiently recruiting U.S. patients, leveraging digital platforms (including AI), and operating within a U.S. regulatory framework will likely see competitive advantages. Conversely, those heavily reliant offshore operations may face rising costs and delays. The sector’s ability to adapt – balancing resilience and insight with cost efficiency – will determine how disruptive these shifts become. While political cycles may drive temporary uncertainty, the fundamentals of good clinical research remain global. The continued discovery of applicable scientific innovation, diversity of patient populations, pursuit of personalized and rare-disease cohorts, and the need for international regulatory data ensures that cross-border trials will endure. The likely outcome next year is not a wholesale return of trials to the U.S., but rather a recalibration: a more resilient, hybrid model that strengthens domestic participation without sacrificing global reach. For forward-looking CROs and sponsors, this transition offers a chance to build smarter, more flexible, technology enabled trial ecosystems that thrive regardless of political tides.