The Three ‘D’s of DCT
There's been much discussion about Decentralized Clinical Trials (DCT) within the clinical research community. As a technologist and problem solver, I listen to these discussions with great interest. Conversations with Aman Khera, vice president of Regulatory Strategy for Worldwide Clinical Trials and emTRUTH® Healthcare Advisory Board member, have been particularly illuminating. We thought the community might find some of our conversations helpful.
The de facto definition of DCT, as an acronym, has been Decentralized Clinical Trials.
As we dug deeper into what people mean when discussing DCT, we found that they are often talking about three different Ds – Decentralized, Distributed, and Digitized.
What’s the Difference
From a technology perspective -- decentralized, distributed, and digitized -- each has a different meaning.
“Decentralized” means delegation of power from a central authority to a distributed localized one as we have in a system where state governments have their own power and decision-making authority. Decentralized systems have peer-to-peer nodes where each node has equal authority to another.
“Distributed” means a network system where tasks and resources are spread across more than one node (e.g., a computer or clinical trial site) to accomplish a single or similar goal, with communication among these nodes back to a central authority. Google is an example of distributed searching. Web crawling and indexing are spread across a network of computers with algorithms that determine which relevant search results to show.
Decentralized is a subset of distributed systems, meaning all decentralized systems are distributed, but not all distributed systems are decentralized.
“Digitized” means data and information are represented as 0s and 1s in a computer. The first step of many organizations undergoing digital transformation is replacing or converting non-digital artifacts (e.g., paper) and processes (e.g., manual) into something that can be electronically handled for greater efficiency, value, or innovation.
The diagram illustrates that decentralized, distributed, and digitized are not mutually exclusive.
Examples of 3 Ds in Clinical Trials
There are many examples of digitization in clinical trials. Transitioning from paper-based forms and processes, while very helpful, is not new nor leading edge. Many other industries already do this and are ahead of healthcare in general, and clinical trials specifically, in terms of their progress. In the realm of clinical trials, efforts are underway to convert consent forms to online forms and capture clinician/patient input via a web or mobile app, an electronic version of forms used today.
Many organizations that are executing DCT are doing distributed clinical trials. Maybe this is what people are calling a hybrid model. An example of a distributed task in a clinical trial would be when dosages are administered at a doctor’s office, following specific directions from the pharmaceutical organization conducting the trial, and the data is reported back to a central authority. Also included are some simple at-home testing, biometric wearables like the Apple watch, and tracking and traceability of a drug being tested. Results are all sent back to pharma or someone acting on their behalf, who is centrally controlling these activities.
Today, truly decentralized activities are rare. The most common example of decentralized elements in a clinical trial is the use of IoT (Internet of Things) devices. For example, some medical devices are starting to decentralize some clinical trial tasks like at-home biometric or biomarker monitors that independently measure and report data as part of a clinical trial. And can also autonomously alert if certain critical thresholds are soon to be reached or exceeded (i.e., devices are independently doing something with the data collected).
Another near-term decentralized task is using smart contracts to automatically execute steps in a smart contract if a set of conditions are met. Many blockchain systems, like cryptocurrencies, use smart contracts to govern autonomy in a decentralized system. Smart contracts are simply blocks of code that say execute these instructions when certain conditions are met. For example, share anonymized demographics with a pharma company only if informed consent is fully executed or create a user account for a mobile app that measures their own self-assessment (e.g., how am I feeling today) once a patient is enrolled in a trial. Because smart contracts automatically execute once a set of criteria is met, it is important to treat these pieces of code as mission-critical, meaning they should follow development standards and testing for critical software.
There are many examples of unintended consequences from cryptocurrency because of poorly written smart contracts. Some of the most significant and widely reported exploits in crypto have resulted from poor "smart" contracts. Because the liability of compromised health data is so substantial, a thoughtful process around any automation involving this data is critical. Not just in protecting privacy and system security but in the ethical use of confidential patient data.
Why the 3 Ds Matter
Understanding the differences between these three Ds is essential because it will help inform your strategy and implementation of DCT. Most everyone has limited resources (e.g., time, money, people). Successful deployment of DCT requires thoughtful planning and a systematic approach to what needs to be done and when, including dependencies on pre-requisites.
For example, digitization can span the spectrum of just scanning paper forms to full workflow automation, data extraction, and traceability to transform your current paper-based data and manual process for informed consent. This spectrum of execution has significantly different costs and resource needs depending on the gap between where you are today to where you want to be.
What’s your organization’s roadmap for DCT?
Look for our next co-authored article on Blockchain for DCT. Reach out at any time if you have questions – info@emTRUTH.com.
About the Authors
Irene Woerner is CEO and Co-Founder of emTRUTH. Irene and Ron Kong (CTO and Co-Founder) chose to focus their foundational technologies in healthcare because of the meaningful impact it can have in improving outcomes while managing costs.
Aman Khera, Global Head of Regulatory Strategy at Worldwide Clinical Trials, has been providing global strategic direction in regulatory affairs for more than two decades. She has built her career on maintaining fastidious patient care with the pragmatism needed to help clients achieve effective regulatory strategies. Aman is available to consult with companies of all sizes, as well as their funding entities, to support their goals – with the primary aim of serving humanity as a whole.
emTRUTH® unlocks the power of healthcare data. We do this by making it quick and easy for healthcare users (who are not IT experts) to securely combine and share data on demand while they, and their patients, retain full ownership and control of their data. The company's technology offers fast and secure horizontal or vertical data integration and interoperability of any type of data. With one API. From anywhere. Using any standard. To any app. In days, not months. For less. For more information, visit www.emtruth.com.