Among the many casualties of COVID-19 lockdowns have been clinical trials for drugs and other medical treatments. A May 2020 survey showed that 69% of ongoing trials were affected by COVID, while the initiation of new trials dropped 78%. With many trial participants unable or reluctant to visit clinics, some new treatments have failed to reach the market, causing life sciences companies to lose the tens of millions of dollars they have invested in these products, and — most importantly — preventing those products from helping patients.
Decentralized clinical trials (DCTs) allow for the collection of required data from patients’ homes rather than from sites. They also require more involvement from trial participants, their caregivers and visiting professionals than from the site staff. DCTs present an opportunity to not only continue lifesaving clinical trials during this and future pandemics, but also to transform the trial experience more broadly –reducing the time, cost and effort of clinical trials and speeding the delivery of new treatments to market.
For sponsors, the first step toward DCTs is using a framework to assess which trials are best suited to leverage a decentralized approach. They should then identify the new digital capabilities and processes needed to meet three vital requirements:
1 Access to Care
Patients need the same expert advice, information and answers to their questions and concerns when participating at home as they would at a trial site. Providing this in an at-home trial requires applications that make it easy for participants to share information with caregivers and provide those caregivers with a complete understanding of the patient’s condition, capabilities and needs.
Consider, for example, integrating existing telemedicine systems with the videoconferencing and data gathering systems used for clinical trials. The fewer data-entry applications and devices a patient uses, the lower their burden and the more likely they will stay in the trial and provide accurate, timely data. Faster and near real-time integration of this data lets caregivers spend less time gathering information and more time understanding the patient’s condition, providing “warm care” that focuses on the patient’s needs instead of just objective clinical outcomes.
Integrating this patient data and the accompanying applications may require the use of cloud-based SaaS applications, data storage and application programming interfaces (APIs). Its analysis may require the use of cloud-based analytic tools and potentially artificial intelligence and other technologies to better assist in risk-based monitoring and decision making.