Clinical Development Crystal Ball: What to Watch in 2026

The clinical development landscape in 2026 reflects years of converging trends: scientific innovation expanding what's therapeutically possible, complex operational demands, and regulatory and economic pressures demanding both accuracy and efficiency. Sponsors and CROs navigating these dynamics will need measurement strategies and scalable digital infrastructures capable of balancing scientific rigor with commercial demands without compromising data quality.

To develop this outlook, we gathered insights from more than a dozen of our clinical, digital health sciences, technical, and operational subject matter experts. Their perspectives highlight the scientific, methodological, and operational trends influencing endpoint strategy, data quality, and trial execution in 2026, and where thoughtful measurement strategy and technology infrastructure will matter most.

AI-Driven Clinical Operations: From Pilot to Production 

Artificial intelligence is moving from pilot projects into routine use in clinical operations. Purpose-built AI applications are being used across a range of areas including patient recruitment and eligibility screening, pattern recognition in COA data, risk-based quality monitoring, clinical trials operations, and more. It remains to be seen how 2026 will separate any meaningful applications from noise.

Implications for trial execution: Many sponsors remain cautiously optimistic about AI. The question isn't whether to adopt AI broadly; it's identifying where AI genuinely improves data quality, speeds decision-making, or reduces burden without introducing unacceptable risk. Ensuring human oversight and decision making remains central to any AI-assisted workflow.

Watch for AI integration in centralized data review workflows, such as expert rater review of audio/video recordings of site-administered rating assessments. Here, algorithms can flag potential quality issues in real-time, enabling human reviewers to make final determinations. Also watch for increased AI usage in risk-based quality monitoring, where machine learning can identify sites or patients requiring additional oversight before problems compound. The real value will come from organizations that use AI to help bring to human attention specific, well-defined problems with appropriate guardrails rather than chasing broad transformation promises.

Remote Assessment: Expanding Access While Managing New Complexities

Remote assessment capabilities are emerging as a significant opportunity to address multiple operational challenges. By enabling cognitive and functional assessments to be conducted before participants travel to clinical sites, remote technologies can increase trial inclusivity, particularly for traditionally underserved and geographically remote communities, while reducing costly in-person screen failures.

The economics are particularly compelling in Alzheimer’s disease trials, where screen failure rates can exceed 75%, with some studies reporting rates as high as 88% in preclinical populations. When each in-person screening visit represents significant time, travel burden, and expense for both participants and sponsors, the ability to conduct initial assessments remotely offers substantial value. Participants who don’t meet eligibility criteria can be identified earlier in the process, reducing unnecessary site visits while expanding the geographic reach of recruitment efforts.

The measurement challenge: Remote assessment brings clear operational advantages but introduces new quality and validation concerns. Ensuring assessment fidelity outside controlled clinical environments requires robust solutions for data quality verification and standardized administration protocols. Environmental factors that would be controlled at a site, like lighting, noise, distractions, technical reliability, become variables that must be managed through technology and process design.

Companies like Splash Clinical are advancing this approach by integrating remote cognitive screening tools into their patient recruitment platforms, enabling pre-qualification of candidates before site visits. Scottish Brain Sciences similarly uses digital cognitive assessments as part of their trial-ready cohort development, helping connect eligible participants to appropriate studies. These platforms balance accessibility with the rigor regulators and sponsors require, combining validated assessment tools with quality monitoring systems. As these solutions mature, expect to see broader adoption across neuroscience trials and expansion into other therapeutic areas where remote cognitive or functional assessment can reduce participant burden while maintaining data integrity.

The trajectory for 2026 will likely depend on demonstrating regulatory acceptance of remotely collected screening data and solving the practical challenges of standardized administration across diverse settings. Success will require not just technology platforms, but comprehensive training programs, quality assurance frameworks, and clear protocols for when remote assessment is appropriate versus when in-person evaluation remains necessary.

Rare Disease Development Gets Fast-Track Treatment…and New Measurement Challenges 

Regulatory agencies are creating new pathways to accelerate rare disease development. The FDA's Rare Disease Evidence Principles (RDEP) program, for instance, allows single-arm trials plus confirmatory evidence to support approval for ultra-rare conditions affecting fewer than 1,000 patients. Similar initiatives across global regulatory bodies are streamlining timelines and reducing traditional evidentiary burdens.

The measurement challenge: Smaller populations amplify the impact of every data point. Traditional endpoint strategies designed for large trials, where statistical power can absorb some measurement noise, don't work when your pivotal study enrolls 10 patients. Sponsors need assessments that capture meaningful change despite the heterogeneous nature of rare diseases, where clinical presentation, symptom severity, and disease progression can vary dramatically between patients. Many rare disease trials also span wide age ranges and disease stages, compounding the measurement challenge - all without the safety net of large sample sizes.

Expect intensified focus on clinician-reported outcomes with demonstrated sensitivity in small samples, electronic data capture to eliminate transcription errors and help minimize missing data, and centralized expert review to reduce inter-rater variability. Success in rare disease trials demands precision at every step: qualified and well-trained raters, validated electronic instruments, and real-time quality monitoring that catches issues before they compound. Given the high cost of rare disease therapies, demonstrating meaningful patient and caregiver benefit, not just clinical endpoints, becomes increasingly important for both regulatory and reimbursement decisions.

GLP-1 Pipeline Explosion: The PRO Measurement Gap 

The GLP-1 receptor agonist pipeline features hundreds of clinical trials globally across all phases, with the majority still focused on weight management and diabetes, but a rapidly growing share in cardiometabolic and other systemic indications. Sponsors are testing these agents in cardiovascular disease, kidney disease, Alzheimer's, addiction, and MASH, while next-generation compounds target even greater efficacy with improved convenience. Beyond these established indications, emerging mechanistic data suggest GLP-1s may have broader therapeutic potential. Early trials in Parkinson's disease showed limited success with first-generation agents, but accumulating evidence of neuroprotective effects has renewed interest – and with it, new measurement questions.

The measurement challenge: Clinical endpoints like HbA1C reduction, weight loss, and cardiovascular events are straightforward to measure. The patient experience across these diverse indications is far more complex. Quality of life, physical functioning, body image, cognitive effects, treatment satisfaction, and daily burden vary dramatically between a MASH trial and an addiction study. If GLP-1s move into neurodegenerative or immune-mediated conditions, sponsors will need PRO strategies that capture outcomes far removed from weight and glucose control, adding another layer of complexity to an already crowded development landscape.

Expect greater emphasis on tailored patient-reported outcome strategies: eating behaviors and psychological well-being for metabolic trials, cognitive function and daily living for Alzheimer's studies, as well as craving and behavioral measures for addiction programs. Electronic diaries and eCOA platforms will need to accommodate frequent, nuanced assessments across vastly different patient populations without creating survey fatigue, requiring thoughtful patient engagement strategies that maintain participation quality. In this crowded and expanding market, demonstrating meaningful improvement in patient-meaningful outcomes, not just biomarker changes, will increasingly differentiate successful programs.

Patient retention challenges: Phase 3 GLP-1 trials must carefully manage retention to ensure study integrity and regulatory success. The extended duration of metabolic and cardiovascular outcome trials, often spanning 1 to 3 years, combined with gastrointestinal side effects like nausea, vomiting, and diarrhea, creates ongoing dropout risk. Among patients using GLP-1 agonists for the first time, 30% discontinued within 3 months and 50% discontinued within a year (Do at al., 2024). Injectable formulations and weight loss plateaus add complexity, particularly as patients assess continued treatment against their initial expectations. Successful retention strategies increasingly rely on proactive engagement through eCOA platforms that include participant's SMART goals, monitor adverse events in real time, personalized support protocols for managing side effects, and clear communication about trial objectives and the importance of completion. For cardiometabolic endpoints requiring extended follow-up, sponsors are implementing flexible visit schedules, telehealth options, and structured patient support programs.

As the GLP-1 pipeline expands into diverse indications from addiction to Alzheimer’s disease, maintaining high retention rates will be critical for demonstrating both efficacy and the safety profiles needed for regulatory approval and real-world adoption.

Psychedelics: Addressing Functional Unblinding in Clinical Trial Design  

Psychedelic-assisted therapies are moving from fringe to mainstream, with multiple compounds in Phase 2 and 3 development for treatment-resistant depression, anxiety, and PTSD.

The measurement challenge: Functional unblinding in psychedelic trials can bias efficacy measurement and complicate interpretation of results. If participants, investigators, or site staff can infer treatment assignment from the psychedelic’s distinctive acute effects, observed improvements may reflect expectancy and placebo-related processes as much as true pharmacologic effects, inflating or distorting measured effect sizes. Our clinical science experts explore this challenge and mitigation strategies in more detail here.

Recognizing the problem, new programs beginning in 2026 are making blinding integrity a fundamental element in their trial design. Sponsors are combining more convincing active placebos and structured expectancy management training with blinded central raters and routine “guess-the-arm” assessments, then using these data in prespecified sensitivity analyses. Endpoint strategies are also broadening beyond legacy symptom scales to include function, quality of life, and more objective or digital measures that are less easily swayed by expectations or rater bias.

For some indications, the FDA's emphasis on patient-focused drug development is pushing sponsors to demonstrate outcomes in meaningful daily functioning such as a patient’s ability to manage finances, maintain social relationships, and perform self-care tasks. For others, the emphasis is on patient-ascribed aspects of clinical meaningfulness. The challenge is incorporating such measures with established clinician-rated outcomes. In 2026, more sponsors may be incorporating functional outcomes and caregiver burden measures alongside traditional scales. Some are also piloting digital measures like activity monitoring or smartphone-based tasks, though these typically serve as exploratory endpoints rather than primary efficacy measures.

The challenge is integrating these diverse data types into coherent, regulator-accepted efficacy narratives. Success requires endpoint strategies that balance innovation with regulatory defensibility, and measurement tools sensitive enough to detect genuine cognitive or functional change without introducing noise that obscures treatment effects.

Pediatric and Rare Disease Trials: The Compounding Challenge 

As pediatric and rare disease trials continue to grow, they bring compounding operational complexities. Small sample sizes, heterogeneous disease presentation, developmental differences across age groups, and the need for parent/caregiver-reported outcomes alongside child self-report create unique measurement challenges that demand specialized expertise.

The measurement challenge: Age-appropriate assessments must maintain psychometric rigor. Measurement strategy must work for a teenager and a six-year-old. Clinician training must incorporate the understanding of child developmental norms. Placebo response runs high, as do hopes. All of this complexity plays out in trials that, for rare conditions, might enroll less than 20 patients globally over two years.

Sponsors are responding with innovative trial designs: adaptive protocols, platform trials, and basket studies that pool data across related conditions. However, measurement science must evolve alongside these approaches. This demands greater focus on fit-for-purpose COA development specifically for pediatric rare disease populations, flexible eCOA solutions that adapt to cognitive and literacy levels, and continued strategic attention to mitigating placebo response in these vulnerable populations.

CRISPR Trials: Measuring What We've Never Measured Before 

Gene-editing therapies are moving into pivotal trials, creating measurement challenges clinical research has never faced. How do you measure the absence of disease when the natural history is well-established but the intervention is entirely novel? What does "cure" look like in sickle cell disease or beta-thalassemia when patients have lived with lifelong symptoms? 

Traditional clinical endpoints weren't designed for therapies that promise transformation rather than management. CRISPR trials will demand creative strategies combining biomarkers, long-term safety monitoring, and patient-reported outcomes that capture life-altering change, not incremental symptom improvement. As the first wave of gene-edited therapies approaches approval, the measurement frameworks developed in 2026 will set precedents for decades of genetic medicine to come. 

Dermatology: Raising the Bar 

Dermatology endpoints are becoming both more stringent and more complex. Regulators increasingly expect EASI-90/PASI-90 (90% improvement) and IGA 0/1 (clear or almost clear) as co-primary endpoints, which are higher thresholds than past standards. These trials now require multiple interconnected assessments to measure body surface area, erythema, lesion thickness, and patient-reported itch, all of which must align logically. When a patient reports severe symptoms but a clinician scores minimal clinical signs, the discordant data can undermine endpoints. 

The measurement challenge: 
Higher efficacy thresholds demand systematic quality control beyond clinical judgment. Dermatology trials increasingly rely on electronic data capture to eliminate transcription errors, and real-time analytics that flag discordant patterns before they compound. Rater training has evolved from generic slide decks to evidence-based programs using real examples of problematic data, emphasizing scale relationships and the impact of scoring inconsistencies on outcomes. 

With the atopic dermatitis market exceeding $20 billion in 2026 and psoriasis surpassing $36 billion, competition is fierce. Longer-acting biologics and new oral treatments will differentiate based on who can demonstrate superior efficacy with data quality that withstands regulatory scrutiny, which means qualified raters, validated electronic instruments, and analytics that catch problems before they compromise endpoints. 

Neurodegenerative Diseases: New Science, New Therapeutic Possibilities

Much of the therapeutic approach to neurodegenerative disease had been symptomatic treatment or treatments to slow disease progression. We now see more that neurodegenerative diseases may be able to be halted and/or repaired. Multiple sclerosis demyelination has been targeted with remyelination concepts: activation of residual oligodendrocytes to lay down new myelin, which we know they can do based on microscopic evaluation of the brains of MS patients which have long revealed evidence of remyelination, and replacement of oligodendrocytes with stem cells. The same is being seen with Parkinson’s disease with differing technologies (i.e. stems cells, gene therapies). Even stroke, which is not neurodegenerative but acute ischemic disease, now includes therapies to limit the damage and, or more importantly, replace and rewire brain cells lost due to stroke. 

What This Means for Your Programs 

The convergence of these trends creates both unprecedented opportunities and significant operational risks. The therapeutic innovation is real. The market potential is real. But success in 2026 will hinge on execution fundamentals: 

• Endpoints that capture what matters to patients and regulators 
• Data quality strategies that catch problems in real-time 
• Rater training that ensures consistency across global sites and diverse modalities 
• eCOA platforms that are sophisticated enough to reduce burden while maintaining rigor 
• Measurement science that matches the sophistication of the therapeutics being tested 

Companies that anticipate these trial execution challenges will be the ones turning promising pipelines into approved therapies. The crystal ball for 2026 isn't just about what's being developed. It's about what can be measured, proven, and brought across the finish line.