Finding the right number of patients with the right characteristics is one of the biggest challenges for clinical trial sponsors. In large part this is due to the fact that randomised clinical trials – the gold standard for conducting clinical research – come with rigid inclusion and exclusion criteria, which render many potential participants ineligible while placing undue burden on those who do qualify. Luckily, clinical trial methodology has evolved since the 20th century and even since a few years ago. Today trials are much more granular, which makes them particularly well-suited for looking into rare diseases and for engaging with hard-to-find, hard-to-enroll, and hard-to-retain patients, such as those living with Alzheimer´s disease, rare cancers, and other rare diseases.

The main paradigm change that enables such granularity is the shift from traditional RCT approaches, which require patients to physically check in at clinical sites, to virtual designs that are better suited to the era of telemedicine, Big Data, and patient-centred healthcare. Two examples of siteless, decentralised trials – which still have to be deployed under the supervision of principal investigators – are home-based RCTs and in silico simulated RCTs.

Home-based RCTs enable patients to report their clinical evolution telematically or by relying on a home health nurse who administers tests and treatments. This type of RCTs are ideal for improving the patient experience, which is key to enrolling and retaining participants. They minimize inconvenience for people with mobility issues by reducing commuting time and effort, and often provide real-time insights that can serve as a behavioural nudge to improve treatment adherence. They also benefit sponsors by increasing the probability of recruiting the needed number of participants with the needed characteristics and of obtaining a more representative sample, since the remote design of the trial reduces geographic and administrative barriers across countries.

In silico simulated RCTs, on the other hand, have no human participants involved. To run them, researchers use historical data from real-life patients to model different scenarios and “health personas” and infer levels of drug efficacy. The use of retrospective medical and clinical data enables the identification of inclusion and exclusion criteria and the enrolment of virtual patients, modelled after real patients´ data footprint. This type of trial design is particularly relevant for drug development in rare diseases, where potential study cohorts and target markets are naturally very small. Thus, in silico RCTs benefit pharmaceutical and biotech companies mainly by reducing the time and costs of R&D.

The key advantage of these emerging trial approaches is that since they are managed remotely or through the cloud, the protocols can be tweaked as more data come in and shed light on the behaviour of the tested drug or intervention in patients. This flexibility, which translates into smarter patient enrolment and lower costs, makes them increasingly attractive to the industry; however, implementing them in practice is still a challenge.

PeakData´s strategic focus on helping companies identify KOLs through both traditional and novel approaches makes us uniquely equipped to help pharma and biotech innovators pivot to decentralised clinical trials. One way we can do so is by leveraging our data collection and analysis tools, used to untap KOL insights that escape the “eye” of conventional searches, to help develop criteria for successful trial design and protocol from the perspective of opinion leaders. We can also use our existing resources and approaches to beta-test the effectiveness of trial design prototypes by measuring the opinions of key stakeholder groups. To learn how a partnership with PeakData can add value to your company´s clinical trial operations, contact us and let´s brainstorm together.