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The real value of eConsent in clinical trials

We've seen support and adoption of eSource in clinical trials from the FDA, EMA and MHRA on various levels because it offers participants, sites and sponsors a way to provide their data electronically, changing the landscape of clinical trials entirely. However, there is still a reluctance to adopt more innovative approaches among sponsors and clinical research organizations (CROs) because sometimes the clinical trial model just isn't compatible with those innovations and other times, they feel it is too complicated to introduce different technologies into clinical trials.

Beginning to use decentralized technologies can be done with a crawl, walk, run approach if committing a fully decentralized clinical trial (DCT) is not possible. Adding eSource in your clinical trial is one way to get started with decentralized technologies and the burdens are outweighed by the value that is presented throughout your study; specifically in these areas:


Most sponsors are implementing several types of data collection in their clinical trials to serve different needs. Patient/Caregiver consent and assent is collected electronically and most suitable for sponsors because it ensures that sites have the correct versions of data and allows for multilingual deployment of multiple consents. Telehealth scheduled visits collect physician outcomes and electronic patient report outcomes (ePROs), surveys and sensors allowing data to be collected directly from the patient. Sponsors can pre-qualify sensors to develop a library of validated sensors prior to a study need allowing them to pilot and collect necessary information as to how the sensors perform with battery life, data integration and ultimately – the patient experience.


With the adoption of technology in clinical trials, it is really transforming how and what training is provided. Virtual learning is an improvement over in-person or paper-based training methods because participants can have access to training for every aspect of their clinical trial. As the population becomes increasingly tech-savvy through the adoption of smartphones and streaming media, the hurdles of learning new systems will get easier year after year. There are processes that make the hurdles that still exist easier. For example, you can mitigate tech barriers by choosing to deploy a single platform rather than disparate systems and assigning a single point of contact for support and training.

Hardware Provisioning

The need for provisioned devices is becoming smaller as the market is saturated with smartphone users, who would prefer to use their own device, which in-turn is lowering the cost of clinical trials and most importantly the patient burden. There may be more of a need in older populations to provide provisioned, locked-down phones but it’s likely that if they’re under 60, they prefer to use their own phone. Providing study data directly using a phone is eSource, therefore it doesn't require source data verification which will improve data quality as it virtually eliminates transcription errors, and the entry of critical study data is tracked in real time offering more benefits if the participant uses their device.

Data Management

The data management role is transforming from being traditionally a role that involves reviewing data looking for transcription errors to orchestrating data of diverse types into a single patient story. Data review changes are necessary to check things like whether all data is in the correct time frame, checking for gaps in the data and identifying data trends within the patient that need to be highlighted in the analysis. When data is collected directly from the source to the final output, it has strong integrity and reduces the need for the type of data review in paper-based clinical trials and having reduced source data verification means that eSource eliminates the need for a verification step, saving time and money while producing high quality data. By design, the adoption of risk-based quality management is used to improve data quality through identifying the study risks and proactively bringing strategies to manage them. A big part of quality management is reviewing the data and metadata for items at risk throughout the study and thresholds are provided around each area to help determine whether a risk is developing or if there is a quality issue.


The analysis phase of a study uses all the data from the patient to decide if the medicine or device is safe and effective. Providing the statisticians digital electronically sourced data directly from the patient eliminates extra steps all of which may cause data integrity issues. The accuracy and quality of the data is the end goal that eSource data collection provides.

Artificial Intelligence and Machine Learning

Deploying a trial model with ePRO, eCOA, and sensor data sources, all on one platform allows for adoption of more robust AI and ML solutions by automatically notifying sites of visit inconsistencies, data anomalies, and compliance issues. These solutions reduce trial duration and increase data quality. A fully integrated study with eCOA, sensors, EDC, and real-world data in a single platform will allow computer algorithms to learn and evolve consistency evaluations, flag anomalies between ePRO and adverse events, and risk-score the reliability of data in real-time as opposed to in retrospect.

As the regulatory agencies increase acceptance of the technologies and the industry uses them more commonly, clinical trials will be more efficient allowing sites to conduct more studies, CROs to service more deliveries, sponsors to introduce more drugs and more patients to benefit from an efficient and cost-effective data collection model. Introducing eConsent into any clinical trial will provide real value to sponsors and CROs. The benefits and value certainly outweigh any burdens that might be faced and modern advancements truly take away some of the burden for patients and caregivers.