In 2013, the U.S. Food and Drug Administration (FDA) introduced its eSource guidance, which suggests methods of capturing clinical trial data electronically right from the start and moving it to the cloud, as opposed to Electronic Data Capture’s (EDC's) traditional method of capturing data initially on paper and transcribing it into the EDC system. The objective behind introducing the new guideline was to streamline clinical investigations and promote data capture in electronic form to ensure reliability, quality, integrity, and traceability of data. Also, investigator sites were provided with direct access to EDC systems, which eliminated the paper-based processes for greater efficiency and swifter data capture, analysis, and reporting.
What’s in store for pharma in digital future?
The future is moving toward increase in data obtained directly from participating patients because of interoperability between electronic health record (EHR) systems. In July 2018, the USFDA released guidance on the use of EHR Data in clinical investigations. It provides directions on whether and how to use EHRs as source of data in clinical investigations and how to use EHR systems that are interoperable with EDC systems.
There is also a shift in capturing patient data from the traditional method of patient visiting site and site entering information into EDC systems. Now the same data is captured from wearables (involving parameters such as blood glucose, BP, activity charts, gait, speech, cardiac event monitoring amongst many others), use of electronic patient recorded outcome (e-PRO), surveys, and e-Consent without site intervention.
The industry is also looking to conduct virtual trials where there is direct connect between the sponsors and participating subjects at a central remote site and patients can conduct trial procedures, as required by the study protocol, from their homes.
What is driving the shift toward patient-generated data?
The number of smartphone users is predicted to grow from 2.1 billion in 2016 to around 2.5 billion in 2019. Over 36 percent of the world's population is projected to use a smartphone by 2018, up from about 10 percent in 2011. Ease of access to smartphones and internet will help gather data directly from patients. Through smartphones, patients can decide on the right study to enroll, provide electronic consent, share adherence data through smart kits, review study-specific/ drug-related multimedia content, receive a reminder to take medications and perform assessments, communicate to PI site team, and report adverse events.
There has also been a sharp rise in the number of wearable devices used in clinical trials. Based on the data available from Clinicaltrials.gov over 200 studies have been registered since 2016 for evaluation and use of wearables indicating symptoms related to Parkinson’s, stroke, atrial fibrillation, cardiac failure, and osteoarthritis amongst many others. Use of wearables devices provides instant access to patient data for remote monitoring.
With patient-generated data, pharma can:
- Eliminate paper-based processes through digital data acquisition and elimination of source data verification (SDV).
- Ensure higher quality of data, which ensures timely and accurate intervention.
- Have faster access to the patient data, empowering clinicians for faster and informed decision making.
- Correlate objective and subjective parameters to monitor the progress of patient, response to therapy, and adverse events.
- Leverage AI and Cognitive algorithms to bolster analytics and assist in decision-making.
What are the challenges?
Despite the promised benefits of smart devices, the study team may have to address the following roadblocks:
- Training patients to ensure adherence to instructions for device usage, data transmissions, and timely response to surveys and study-specific instructions
- Dealing with non-conversant patients with smartphones and wearable devices
- Operating multiple devices with vendor-specific processes for data collection, storage, analysis, and reporting
- Ensuring integration and correlation of data with other parameters such as patient demogs, history, signs, and symptoms
- Managing cost of devices
- Provisioning devices and ensuring uniform access and no bias in use of devices
- Ensuring data quality at source
Smart steps for using smart devices and wearables
The decision to choose the right wearable device for a clinical trial depends on a number of factors. Here is a high-level guide on potential steps, which can be considered for implementation.
- Start a POC to define outcomes, which also includes endpoints to be assessed, metrics, and key success factors.
- Assess the technology platform for data integration.
- Assess the devices for regulatory approval and adherence to study-specific requirements while ensuring ease of use through the availability of APIs and web services for integration with other systems.
- Assess and analyze the preliminary data and compare it with existing standards to validate outcomes.
- Assess qualitative feedback from all stakeholders for addressing gaps.
- Pick right study to start pilot projects after incorporating results from the POC.
After eSource and wearable devices, the pharma industry is set to leverage artificial intelligence and digital biomarkers to tap patient generated data for enhanced quality of decision making and greater operational efficiencies.