The Future for Decentralised Clinical Trials

Pharma strategies for decentralised clinical trials (DCT) looked truly promising and transformative during the COVID-19 pandemic, but subsequent analysis has shown that results have actually been more limited than expected. 

The DCT models and design strategies work, but there are remaining barriers facing DCT implementation.

The U.S. FDA DCT guidance and ICH E6(R3) have removed most of the compliance uncertainty that sponsors were worried about. The industry should now collectively look to how to solve the challenges remaining for DCT programme design and management.

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What Are Decentralised Clinical Trials?

A decentralised clinical trial (DCT) is a study in which some or all trial activities take place outside traditional clinical sites.

In DCTs, patients participate from home or local healthcare facilities using a combination of digital tools, telemedicine consultations, home nursing visits, and direct-to-participant drug delivery.

DCT models for pharma strategy range from fully remote designs, where no site visits are required, to hybrid models that integrate selective remote elements into a predominantly site-based framework.

Most current evidence supports hybrid approaches as the best operational model across the majority of therapeutic areas.

The latest U.S. Food and Drug Administration (FDA) guidance formalised the regulatory basis for DCTs in the U.S., covering telehealth visits, use of local healthcare providers, and digital data capture standards.

ICH E6(R3), effective from July 2025 under the European Medicines Agency (EMA), explicitly endorses decentralised elements as compliant with Good Clinical Practice under ICH E6(R3) requirements.

But, while the regulatory and compliance questions have been answered, a 2025 analysis of 2,830 DCT-attributed trials found that DCT adoption, while real and growing, has been unevenly distributed across therapeutic areas and geographies and that operational barriers to DCT implementation remain significant.

The Operational Barriers Slowing DCT Adoption

Data fragmentation is the most consistently cited operational problem for DCT operation.

A fully remote study may draw data simultaneously from wearable biosensors, ePRO applications, telemedicine platforms, home nursing records, and local laboratories. Without deliberate integration architecture, these sources produce fragmented records that are difficult to solve and audit.

Fast Healthcare Interoperability Resources (FHIR) and Clinical Data Interchange Standards Consortium (CDISC) ODM (Operational Data Model) are now considered minimum standards for compliant DCT data management. Both are gaining traction across the industry, but they are not yet standard across all vendors and sites. Sponsors who do not specify these requirements in contracts before execution create compliance gaps that surface at data lock.

Patient diversity gains from decentralisation are notable. The PACT Consortium diversity data from 69 trials confirmed higher representation across demographic groups in DCT-enabled studies. Those gains were linked to deliberate recruitment strategies, not to remote technology alone.

However, study design and protocols requiring reliable internet or system connectivity, smartphones or other digital devices, as well as suitable patient home environments, can recreate the very access barriers they were designed to address.

Digital literacy support and community outreach must be built into the protocol at the design stage, not added as a post-hoc mitigation.

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What the Evidence for DCTs Actually Supports in Clinical Development

Hybrid design consistently outperforms fully decentralised execution in the current evidence base for most therapeutic areas.

Oncology accounts for 46% of DCT activity by therapeutic application, where remote symptom monitoring and electronic patient-reported outcomes (ePROs) are well suited to decentralised collection.

Neurology is the fastest-growing therapeutic area for DCT adoption, with a projected annual growth rate of 16% through 2030.

Fully remote execution works best in digital therapeutics and symptom monitoring studies where no physical clinical assessment is required.

AI tools are in active deployment for several DCT activities like adverse event detection, data quality monitoring, and patient recruitment support. AI adoption in DCTs represents a meaningful share of DCT workflows, and industry analyses project that usage will expand greatly over the next five years as sponsors scale digital platforms.

Another exciting opportunity to support DCT implementation is blockchain-enabled consent tools. One multicentre clinical trial using blockchain-based consent recorded 95.7% consent completion and 90.8% medication adherence, both comparing favourably with traditional site-based approaches.

Five Actions for Clinical Operations Leaders in Designing and Implementing DCT Programmes

For clinical operations teams designing and implementing DCTs, it is important to first conduct a formal DCT suitability assessment during protocol design for every programme. This should evaluate the patient population, therapeutic area, primary endpoint type, and regulatory jurisdiction before any site or vendor is selected.

Secondly, teams should define the study’s data architecture and interoperability requirements before choosing any technology platform. FHIR and CDISC ODM standards must be written into vendor contracts at signing, not negotiated during trial setup.

Additionally, digital health literacy support should be built into patient engagement plans from the outset. Identify which patient subgroups benefit from decentralisation and which face new barriers, and design targeted support for the latter group.

Engage regulatory affairs early for any DCT using AI-assisted monitoring, with documentation prepared under the FDA AI credibility guidance framework.

Lastly, ensure all audit trails, consent records, and remote monitoring logs are structured for inspection readiness from day one under current GCP requirements.

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Conclusion: The Promise and Reality of DCTs

The regulatory case for DCTs and pharma strategy is settled. The FDA's September 2024 guidance and ICH E6(R3) together provide a clear compliance framework for hybrid and fully decentralised designs in the U.S. and EU.

The remaining barriers to DCT implementation are operational: Data fragmentation, interoperability gaps, and inconsistent patient digital access.

Hybrid design is the most evidence-supported model for most therapeutic areas, while oncology and neurology lead DCT adoption.

Patient diversity gains from DCTs are real but require deliberate implementation. Technology alone does not improve representation; recruitment strategy, multilingual consent, and community outreach are all necessary components.

Pharmatica tracks the DCT evidence base, regulatory developments, and implementation benchmarks across the pharma industry, giving clinical operations leaders the intelligence they need to build decentralised clinical programmes that deliver on their clinical and commercial potential.

Pharmatica: Insight. Connection. Impact.