How Patient Centricity And The Internet Of Things Will Develop Clinical TrialsAdd bookmark
Currently, two trends are in focus for the clinical trial supply chain: patient centricity and the usage of the Internet of Things (IoT) in clinical trials. Both components are driven by the need to shorten clinical development timelines, reduce costs and improve data quality. The clinical supply chain can contribute significantly to these objectives.
Patient Centricity in Clinical Trial Supply
The patient experience in clinical trials can be improved by easy-to-handle medication packages, easily accessible information about the patient’s treatments and study procedures, close contact with the patient’s investigator and a reduction in the number of site visits. These developments have come through requests captured in various patient surveys, showing that such an environment would increase a patient’s willingness to participate in clinical trials. As enrollment is a key criterion for the success of clinical trials, the clinical trial supply chain should aim to fulfill as many of the patient’s needs as possible.
To fulfill patient requests, patient engagement mobile apps have emerged. These are used to replace the current e-diaries to capture patient data, and supply information about the clinical trial drug. The mobile apps can also provide instructions for drug handling (supported by videos and pictures) and remind the patient about treatments. With these functions in mind, mobile apps can support compliance while ensuring patients properly administer a drug – as the details are presented more clearly that the text on a package label. Furthermore, wearables like activity trackers (which collect data automatically) and medical devices (which send data automatically to a trial system) can help as well, reducing the need for site visits.
Another possibility to reduce the number of visits for drug dispensing and lab sample taking is the delivery of medication to the patient’s home and arranging for the pick-up of samples (ideally supported by home care). Contract research organizations (CROs), courier companies and technology providers are already supplying these services and the developments to improve the procedures in line with the protection of the patient’s data privacy—which is required according to Good Clinical Practice (GCP) and ethical principles—are ongoing.
IoT in Clinical Trial Supply
The usage of a smartphone is daily experience for all of us, but, at the clinical site, paperwork and data entry into various systems are still common practice. Recently, mobile apps have been connected to interactive response technology (IRT) systems and clinical trial drug packages with readable unique identifiers, improving data quality.
With so much data involved during the clinical trial supply chain, it is critical that it is not only collected, but is done so efficiently and effectively. Consider that unique identifiers include bar codes and sensors in the drug package that collect environmental data such as temperature, shock and pressure. Such packages can be used to track the patient’s drug consumption, which not only gives real data about compliance but provides the opportunity to influence the patient’s behavior through reminders sent out by patient engagement apps.
There are several processes at the site for the arrival of the medication, for dispensing and also drug accountability. When the packages are simply scanned with a mobile app, rather than paperwork or entry into separate systems having to be completed, these steps can flow much more seamlessly. Additionally, an app can detect a mistake at the moment it takes place, not weeks later during monitoring, contributing to the streamlined processes. Beyond creating efficiencies, these methods contribute to safety, ensuring the patient receives the correct drugs.
The entire supply chain can be tracked using the technologies discussed. Active tracking of temperature, location and shock can provide data about the condition of the medication during the journey from the manufacturer to the patient. The data is collected as required by Good Manufacturing Practices (GMP), Good Distribution Practices (GDP) and GCP regulations and can be analyzed to exclude damaged medication before dispensing to the patient. All of this will support the objective for better data quality, reduced efforts in terms of data collection and improved patient safety.
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