eSource & Direct Data Capture for Clinical Trials

Capture clinical research data electronically at the point of care with TrialKit’s unified eClinical platform. Reduce duplicate data entry, support data quality, and give study teams the tools to collect, manage, and review source data across clinical research sites.

Capture Source Data Where Research Happens

Clinical research teams depend on accurate, timely data, yet traditional source documentation workflows often require information to be recorded on paper or in separate systems before being entered into an electronic data capture (EDC) database. That additional step creates opportunities for transcription errors, delays, and administrative burden.

TrialKit supports eSource and direct data capture (DDC) workflows that allow research personnel to record clinical observations, assessments, and other study data electronically as they occur. With configurable forms, native mobile applications, and integrated data management tools, TrialKit helps sites reduce redundant documentation while giving sponsors and CROs greater visibility into study activity.

Why Choose TrialKit for eSource and Direct Data Capture?

TrialKit combines electronic source data capture with the configuration, validation, and oversight capabilities of a unified eClinical platform. Research teams can support point-of-care documentation while managing data quality, access, and review throughout the study.

Capture Data at the Point of Care

Record clinical observations, vital signs, assessments, and other study information directly into electronic forms. TrialKit’s web and native mobile applications support data entry wherever study activities take place, helping research personnel document information closer to its source.

Reduce Duplicate Data Entry

Minimize manual transcription between source documentation and EDC when original study data are captured directly within TrialKit. This can help reduce administrative work, limit opportunities for transcription errors, and make collected data available for downstream review.

Configure Study-Specific Data Collection

Create electronic forms tailored to protocol requirements, with conditional logic, required fields, automated calculations, and edit checks. Support different types of data collection while maintaining consistent workflows across participating sites.

Support Data Quality at Entry

Use configurable validation rules to identify missing, inconsistent, or out-of-range information during data entry. Automated edit checks and query management help teams address discrepancies and support data quality throughout the study.

Review and Verify Source Data

Manage data review through configurable, role-based workflows, including field-level source data verification (SDV), record review, and electronic signatures. Monitors and data managers can track review progress and address issues within TrialKit.

Maintain Data Traceability

Track data changes, user activity, and review events through electronic audit trails. Role-based permissions help control access to study records, while audit reports provide visibility into the history of collected data.

Source Data Capture and EDC in One Unified Platform

eSource and electronic data capture serve closely related purposes in clinical research.

eSource refers to information originally recorded in electronic form, while direct data capture describes the process of recording study information electronically at the point of collection. EDC systems support the organization, validation, review, and management of clinical trial data.

Traditionally, source documentation and EDC data entry may involve separate systems or processes. TrialKit allows study teams to bring these activities into a unified environment.

For research sites, this means fewer separate data entry steps when TrialKit is used for original source capture, along with familiar tools for completing forms and responding to queries.

For sponsors and CROs, it means access to clinical data, review status, audit trails, and monitoring tools within the same platform.

For data managers and monitors, it means configurable validation and review workflows that support data quality and source verification.

Configure Data Collection Workflows With Floyd

Floyd, TrialKit’s embedded AI model, helps research teams translate protocol requirements into configured study components, reducing the manual work involved in preparing electronic data collection workflows.

Build From Protocol Requirements

Use Floyd to interpret an existing protocol and assist with generating electronic forms, visit schedules, edit checks, and conditional logic. Teams can review and refine configurations to support the requirements of their study.

Test Data Collection Before Deployment

Generate synthetic participant data to evaluate configured forms, test data collection scenarios, and identify potential issues before live study activities begin. TrialKit’s validation tools also support testing form logic and documenting results.

Support Data Review and Analysis

Use Floyd to explore study reports and data, ask questions about results, and investigate patterns that may warrant closer examination. These capabilities complement the platform’s existing reporting and data review tools.

Floyd helps teams prepare, evaluate, and analyze study configurations and data while keeping human review and approval central to the process.

Support Data Collection Across Sites and Study Models

Clinical research doesn’t always take place in a single environment. Study teams may need to capture information during scheduled site visits, at different clinical facilities, or through remote research activities.

TrialKit supports flexible data collection workflows across traditional site-based, hybrid, and decentralized studies.

• Site-Based
• Hybrid
• Decentralized

UNIFIED PLATFORM TrialKit

Brings together complementary data collection capabilities

• EDC

Manage clinical study data, edit checks, queries, and reporting.

• ePRO/eCOA

Collect patient-reported outcomes and other clinical outcome assessments electronically.

• eConsent

Manage electronic informed consent workflows and documentation.

• Wearables and Remote Monitoring

Incorporate data from supported wearable devices and health platforms.

• API Integrations

Support data exchange with external systems and research technology.

• TrialKit Engage

Coordinate participant scheduling and virtual study visits.

These capabilities allow research teams to manage different forms of electronic data collection within a broader study environment.

Built for Sites, Sponsors, and CROs

Research Sites

Reduce repetitive data entry and support clinical documentation with flexible electronic forms, mobile access, and streamlined data review workflows. Give site personnel tools to capture study data during visits and respond to queries within the same platform.

Sponsors and CROs

Maintain visibility into study data and review activities across participating sites. Use centralized reporting, configurable permissions, and monitoring workflows to support oversight as data collection progresses.

Clinical Data Managers and Monitors

Configure validation rules, review records, manage queries, and perform source data verification within TrialKit. Access audit histories and data review information to help identify issues and track their resolution.

Want to Know More About TrialKit eSource?

Reduce unnecessary transcription, support reliable data collection, and give your study teams greater control over how clinical information is captured and reviewed.

See how TrialKit can support eSource and direct data capture within a unified eClinical platform, from study configuration through data review and analysis.