EDC In Clinical Trials| EDC In Clinical Research

Clinical trials have evolved significantly over the past few decades, incorporating major technological advances that have modernized and transformed the clinical research process. In the early days of clinical research, data was recorded manually on paper case report forms (CRFs). Researchers relied on faxing documents and postal mail to share data between sites. 

The development of electronic data capture in clinical trials (EDC) systems in the 1990s digitized the data collection and management processes for clinical trials. Researchers could now enter data directly into secure online platforms in real-time. EDC systems automated key processes, provided data validation checks, and enabled remote monitoring of trial sites. This new technology greatly improved accuracy, efficiency, and oversight compared to paper-based methods.

Since those early days, EDC in clinical research systems have continued advancing to provide greater capabilities. Cloud-based systems have replaced on-premise servers, enhancing flexibility, scalability, and real-time accessibility. Integrations with other eClinical systems like CTMS, ePRO, eCOA, and eConsent have enabled more seamless end-to-end trial data flows. Analytics, dashboards, and reporting functionalities have also advanced considerably.

However, the clinical trial landscape itself has grown increasingly complex over the past decade. Trials are becoming more globalized, outcome-focused, personalized, and patient-centric. Virtual and decentralized trials are rising exponentially, accelerated further by the COVID-19 pandemic. As trials transform, technology needs to advance in step. So has EDC been keeping pace with the latest clinical research innovations?

How EDC Systems Have Improved Clinical Trial Processes

EDC platforms have come a long way in enhancing clinical trial execution and solving pain points for sponsors, CROs, sites, and patients. Capabilities that have driven major efficiencies and improvements include:

  • Real-time data accessibility from any location for all stakeholders
  • Custom edit checks and logic to enhance data quality
  • Centralized monitoring to maximize oversight
  • Patient portal integration that enables eConsent and ePROs
  • CTMS and eTMF integration for end-to-end data flows
  • Role-based access and dashboards to enhance collaboration
  • Powerful analytics and reporting of study data
  • Flexible configuration of studies to collect any type of data

Together, these features have reduced monitoring visits, query volumes, cycle times for database lock, and overall study timelines and costs. EDC has essentially digitized, streamlined, and transformed scattershot paper-based processes into unified electronic systems for managing end-to-end trial data.

New Trends in Clinical Trials: Decentralized, Virtual, and Patient-Centric Trials

The clinical trials landscape has been changing significantly in recent years with the emergence of decentralized, virtual, and patient-centric trial models.

Decentralized trials enable patients to participate remotely in studies, rather than having to travel to study sites. Patients can use devices, apps, or sensors to collect study data at home which integrates seamlessly into the core EDC platform. Site staff also rely more on virtual visits.

Virtual trials take the decentralized approach even further so that the entire trial is conducted remotely without any in-person site visits. These studies have become more viable recently thanks to the growth of digital health technologies.

Patient-centric trials place the patient experience at the center of the study design. Methods include more flexible dosing schedules, reduced visits to study sites, patient engagement through apps and wearables, access to health data, and input on outcomes being measured.

The COVID-19 pandemic necessitated remote, digitally-powered trials and unexpectedly accelerated adoption of these new approaches. In fact, decentralized trials surged from under 4% of all trials in 2019 to over 25% in 2021. These patient-friendly, technology-powered designs are becoming the new normal. Many experts predict over 70% of trials will be virtual or decentralized by 2026.

So as clinical trials transform, EDC for clinical research systems need to continuously evolve to enable the complex data capture and trial execution processes these innovative models demand.

How EDC Systems Need to Adapt to New Clinical Trial Models

As virtual, decentralized, and patient-centric trials become more predominant, EDC systems need to advance in several key ways to provide the needed functionality.

First, EDC for clinical research platforms must seamlessly integrate multitudes of patient and site technologies like apps, sensors, and other eClinical systems. This requires exceedingly flexible, open, and highly configurable APIs and connectors.

Next, EDCs will need more sophisticated clinical data management capabilities to wrangle, cleanse, and structure the huge volumes of disparate, real-world data streaming in from patients. This includes machine learning algorithms to enhance analysis.

Additionally, it’s critical for EDC platforms to directly embed patient-facing tools like eConsent, ePROs, and wearable sensor data rather than relying on separate portals. This provides a unified user experience across devices and sources.

Finally, EDCs will need incredibly robust cybersecurity, identity management, and access controls as sensitive data is accessed from myriad endpoints. Patient privacy also must remain sacrosanct within these complex ecosystems.

Many leading EDC vendors have already made significant headway on these next-gen platform requirements. However, continued innovation is vital as trials will only grow more advanced, global, and multi-technology-driven over time. The technology supporting trials must persist in evolving.

The Future of EDC Systems in an Increasingly Digital Clinical Trial Landscape

The future of Electronic Data Capture (EDC) systems in clinical trials is set to be shaped by digital transformation, with a focus on enhancing efficiency, scalability, and patient-centricity. The integration of artificial intelligence (AI) and machine learning (ML) into EDC systems is a promising development, offering faster data gathering and increased productivity, replacing time-consuming paper-based operations. Cloud-based EDC solutions are emerging as game-changers, providing benefits in terms of accessibility, scalability, security, and cooperation


The shift towards decentralized trials and direct data capture is another significant trend. This approach expands the reach of clinical trials by eliminating geographic limitations and allows for the collection of patient data directly from devices and other systems. The increased utilization of data from electronic clinical outcome assessments (eCOA), electronic patient-reported outcomes (ePRO), and wearables/sensors, as well as leveraging electronic medical records (EMRs) and other eSource data, is becoming the new normal. To stay relevant and effective, EDC systems must evolve to accommodate these changes and ensure they are future-proof


Clinical trials and the technology systems supporting them have advanced lightyears since the early paper-based days. EDC platforms have digitized, streamlined, and enhanced how trial data is collected, managed, integrated, analyzed, and shared across global research networks.

However, EDC systems must persist in innovating to keep pace with the rapidly evolving clinical research paradigm. As trials incorporate more decentralized and virtual elements, more real-world data sources, and place patients at the center, EDCs need more agility, analytical power, and interconnectivity.

Leading technology vendors continue extending platform capabilities to empower sponsors to configure trials customized to any indication, patient population, or data requirement imaginable. As EDCs grow more versatile yet compliant, clinical trials will continue benefiting from enhanced productivity, oversight, accessibility, scalability, and cost efficiency well into the future.


Q: How have EDC systems helped improve clinical trial processes?

A: EDC systems have digitized and streamlined clinical trial data flows, reducing errors, costs, and cycle times. Key benefits include real-time data access, edit checks for data quality, central monitoring, system integrations, analytics, and reporting.

Q: What are some key trends reshaping clinical trials today?

A: Decentralized, virtual, and patient-centric trials are making research more flexible, accessible, and focused on patients’ experiences leveraging apps, wearables, and sensors. These models are rising exponentially.

Q: As trials transform, how do EDC systems need to adapt?

A: EDC systems need greater interoperability, real-world data management, patient engagement tools, cybersecurity, and advanced analytics to support decentralized and patient-centric studies.

Q: What does the future look like for EDC systems powering clinical trials?

A: The next generation of EDC will be cloud-based, AI-driven, hyperconnected hubs ingesting, managing, analyzing, and exchanging myriad data types across technologies and endpoints.