Scaling Digital Clinical Trials: From Innovation to Global Execution

Clinical trials are at an inflection point. As sponsors seek to move from isolated digital pilots to scaled, global execution, the focus must shift toward models that truly benefit patients and sites. This session at the Indegene Digital Summit 2025 explored how the industry can make that leap — by shifting the conversation from individual tools to integrated themes that combine technology, standards, and workforce transformation.

The discussion, led by Ram Yeleswarapu (Indegene) and Avik Pal (CliniOps), framed digital transformation as a journey from proof-of-concept deployments to embedded, portfolio-wide practice. Rather than adding more point solutions for eConsent, remote visits, or ePRO, the speakers made the case for building a backbone that connects data, workflows, and stakeholders around a single source of truth.

Three themes emerged as critical enablers of scale: unified data and process orchestration, human-centered design for global adoption, and a future-ready workforce capable of working alongside intelligent agents.

A central pillar of scalable digital clinical trials is unified data and process orchestration anchored in a single source of truth. Today's environment is dominated by fragmented systems — EDC, CTMS, randomization tools, eConsent platforms, and ePRO apps — loosely stitched together through back-end integrations. This fragmentation leads to clunky handoffs, inconsistent data handling, and potential data integrity issues, particularly when sponsors and CROs bring their own preferred technologies into the same trial.

Avik highlighted the emerging ICH M11 machine-readable protocol standard as a practical way to harmonize biomedical concepts and ensure that all stakeholders and systems are reading from the same sheet. When the protocol becomes a structured digital object — defining endpoints, data points, and visit schedules in a standardized manner — downstream systems, from EDC and eCOA to data repositories, can be configured directly from that source. This reduces translation, re-mapping, and retrospective standardization, and lays the foundation for straight-through data flow into CDISC standards and statistical analysis.

Hybrid decentralized clinical trial models were also framed as a practical extension of decentralized trial guidance for global use. In many geographies, patients may lack smartphones, home internet, or digital literacy — but community health worker models are mature and trusted. By deploying trained health workers or nurses to patients' homes to collect data in a decentralized but supervised manner, trials can remain inclusive without assuming a fully app-based, at-home model.

The second theme emphasized that scaling digital clinical trials requires designing experiences that reduce burden for both patients and sites. While patient centricity is widely discussed, site burden is often underestimated — investigators and coordinators are expected to absorb new tools and processes on top of already heavy clinical responsibilities.

The speakers advocated a human-centered approach grounded in respectful assumptions about capabilities and constraints. In many regions, patients have leapfrogged directly into mobile payments and app-based services, demonstrating comfort with digital systems. At the same time, nurses and physicians may still rely heavily on paper CRFs because that is how their workflows and institutional processes are structured.

One practical design principle is to make digital interfaces feel like a natural continuation of paper. When staff log into an app and see a screen that visually mirrors familiar paper forms — augmented with built-in edit checks and range validations — the adoption curve flattens significantly.

Cultural and linguistic relevance were also highlighted as essential. The speakers pointed to the importance of multilingual support, local-language helpdesks, and sensitivity to cultural taboos and terminology. This combination of familiar design, local language, and culturally attuned UX has enabled very large-scale decentralized clinical trials where nurses visited homebound patients and captured data offline at the point of care. Digital data capture with embedded quality checks reduced average data queries from roughly 100 per patient to just 2 — with downstream benefits for data management, monitoring, and travel.

The third theme focused on what a future-ready clinical workforce looks like in an era of intelligent agentic systems. Drawing an analogy to process automation in manufacturing, the speakers suggested that AI agents will fundamentally reshape clinical operations by taking on repeatable, binary, and input-heavy tasks.

At the site level, change management remains challenging, so technology must feel like an invisible helper rather than a disruptive mandate. If the same coordinator who previously filled out paper CRFs can enter data on a tablet in offline mode — and benefit from real-time edit checks and guidance — the underlying sophistication can remain largely hidden while error rates and rework drop dramatically.

On the sponsor and CRO side, traditional roles are expected to evolve. As ICH M11 machine-readable protocols and standardized digital data flows mature, AI agents can support or automate tasks such as study build, configuration of eCOA and EDC, and routine query handling — with humans shifting into higher-value functions. Data managers, for instance, can act more like data scientists, focusing on signals, outliers, and insights rather than manual reconciliation.

Leadership will also need to revisit how success is measured. Traditional clinical trial metrics may be insufficient in an environment where AI and human contributions are interwoven. Outcome-based clinical trial metrics — such as reductions in data queries, cycle times, and site burden, alongside improvements in quality and patient retention — will become more meaningful indicators of return on investment.

Beyond technology and process, the speakers raised a broader ethical question: what happens to patients when a trial ends, especially in oncology and other serious conditions where investigational therapies show promise? For many participants, exiting a trial can feel like a return to a finite countdown.

The discussion called for a more deliberate convergence of clinical trials and routine care — and a tighter loop between R&D, clinical development, and real-world evidence generation. As digital clinical trial and decentralized clinical trial models mature, there is an opportunity to design ecosystems where trial participation, post-trial care, and real-world data collection form a continuum rather than discrete silos.

In closing, the session reinforced that scaling digital clinical trials globally depends on three mutually reinforcing pillars: an integrated data and technology environment rooted in a single source of truth, human-centered experiences that reduce burden for patients and sites, and a workforce empowered by intelligent agents and new skill sets. By aligning around these themes, sponsors and partners can move from one-off pilots to globally harmonized, standardized digital execution — accelerating access to safe, effective, and affordable therapies for the patients who are waiting. Ultimately, improving clinical trial outcomes begins with building the infrastructure, culture, and capabilities to sustain digital transformation at scale.