Direct-to-Patient (DtP) Clinical Trials – Using RTSM Systems to Overcome Supply Challenges

Overview

With more and more studies focused on disperse patient populations, the industry has been exploring alternative trial designs to improve enrollment and ease the burden on patients to access trial sites. One of these alternative designs is Direct-to-Patient (DtP). DtP trials are a win-win for patients and sponsors. Patients gets better service, travel less, get their treatment where they are and sponsors accelerate trial timelines and reduce cost. The challenge lies in designing it correctly so the integrity of the study remains intact - such as addressing significant impacts on the supply chain, including timing, shelf-life and temperature. The purpose of this white paper is to provide in-depth information on the various DtP approaches while offering insight into best practices when incorporating DtP into the protocol. Additionally, resulting supply chain challenges are explored as well as how Randomisation and Trial Supply Management (RTSM) systems can be leveraged to overcome those challenges.

What is DtP?

In traditional clinical trials, patients travel to and from an investigator site (“brick and mortar site”) for all clinical trial tests and assessments that are generally performed by investigators and their delegated study personnel. DtP, however, is considered a type of Decentralised Clinical Trial (DCT) because trials are conducted at locations outside of the investigator site (e.g., patient’s home, work place, travel destination) and may be executed through the use of mobile/local healthcare providers, wearable/ sensor devices, telemedicine, eConsent, etc. DCTs may involve any phase, but must have at least 1 investigator with a physical location. Some DCTs are completely remote, while others are hybrid (only a portion is conducted remotely). It is important to clarify that DtP trials are not synonymous with virtual or siteless trials. Virtual trials have no investigator and no sites, and are primarily computer modelling studies.