Regulatory Support for eSource

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What is eSource?

eSource, broadly, is the idea that data entered into an electronic platform, like an EDC or an EHR, can be considered the source data for the purposes of reconstructing and evaluating the safety and efficacy of a clinical trial.


Regulatory Support for the use of eSource in Clinical Trials

The FDA has laid out well defined guidelines regarding what is considered eSource data, and how it should be safely managed to achieve regulatory compliance in their 2013 guidance document. Despite the use of eSource being firmly procedurally established for almost a decade, we still regularly encounter clients that are unsure of how to begin implementing eSource into their trials, or are unsure that eSource practices are both supported and encouraged by the FDA. To this end, here is a brief primer on the key points of the 2013 guidance document, and an illustration of how robust EDC systems fully support the operational requirements introduced by the decision to leverage eSource data.


Types of Source Data Capture

1. Direct data entry into the eCRF

a. Special care and consideration should be given to what the actual source document is. Any time transcription is involved, be it from laboratory data or from a radiologist’s assessment of a CT scan, these are the source documents in these cases. Only when the first point of data capture is the individual recording information in the eCRF is this eSource.

b. Even in the case of true eSource data, supporting documentation should be maintained. The FDA may request “…evidence of testing, or the use of medications to corroborate a diagnosis.”

Direct Data Entry, Demographics Form, eCRF, eSource

2. Automatic Transmission of Data From Devices or Instruments Directly to the eCRF

a. In the event that the device transmits the data directly to an EDC, the EDC would be considered the source record, if it is originally transmitted to an EHR, in this case the EHR would be considered the source record.

3. Transcription of Data From Paper or Electronic Sources to the eCRF

a. Any time data is transcribed into an electronic system from a paper source, these documents must be retained for review by the FDA.

4. Direct Transmission of Data From the Electronic Health Record to the eCRF

a. In this case the EHR is considered the source data. The relevant patient data source data in the EHR should be available for review by the FDA. Similarly, sponsor and/or monitor access to this source data should not differ from their ability to access paper records in a more traditional trial.

5. Transmission of Data From Patient-Reported Outcome (PRO) Instruments to the eCRF

a. If a subject uses a device to transmit data directly to an eCRF, the eCRF can be considered the source data. If the data is transmitted to some other service provider database, that database is considered the source, and needs to be available for similar levels of review as paper source documents.


The FDA sets forth additional guidelines regarding the measures that should be taken to ensure data integrity and to allow for the thorough reconstruction and review of events in the study. Modern EDC platforms resolve most of these requirements simply by virtue of their core functions:

1. Data Element Identifiers

a. This is the requirement that all data level activity in the system be attributable to the specific user and time data was entered or changed. This is handled by compliant audit trails in a proper EDC.

2. Modifications and Corrections

a. Modifications to existing eCRF data must only be performed by clinical investigators or delegated staff. Changes to data cannot obscure historic data, and must be attributable to a date/time, user, and applicable reason for change. EDC handles this by capturing reason for change in edit checks, and again makes the entire process traceable through detailed audit logs.

eSource, Direct Data Entry

3. Use of Electronic Prompts, Flags, and Data Quality Checks in the eCRF

a. This describes the requirement that automated edit checks be designed to promote data quality at the time of entry. In this process it is important that clinical investigators have the ability to record comments regarding these potential data quality issues as they arise. Again this is a simple core functionality of EDC, the ability to record commentary as edit checks are triggered in an eCRF.

4. Data Review

a. The data review requirements set forth by the FDA describe the need for investigator signatures for each eCRF prior to submission. In the event that data is changed for any reason on the eCRF this requires the document to be resigned. Data that is exempt from signature due to blinding or other strictures of the protocol must be thoroughly documented, typically in a data management plan. Any CFR Part 11 compliant EDC will have a robust eSignature mechanism available within the platform.

5. Retention of Records by Clinical Investigator(s)

a. Investigators should retain control of the eCRF records, either as completed and signed eCRFs or as certified copies of such, and be able to provide access to the FDA or other regulatory authorities.

6. Data Access

a. Access to eCRF data should be available to only authorized personnel, both before, and after an eCRF is completed and signed, to allow for early detection of issues. These personnel need to be clearly identified, with documented training, and secure access to the platform. In the context of an EDC, this is supported by the ability to maintain training records certifying completion, and user access logs for reporting purposes.


If you’ve read this far, I encourage you to take a look at the original guidance document from the FDA. Eliminating or reducing processes in your trials that involve paper documentation can represent profound efficiencies in the space of data management and monitoring. If you’d like to speak with us about how we can support paperless or hybrid trials shoot us a message today or let us know your questions.

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Why eSource: The Advantages of Abandoning Paper Records

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Central Monitoring: First Steps to a Risk-Based Approach