Pierre Etienne

A few years ago, many in the life-science industry questioned whether real-world data (RWD) would have any application in drug development. Due to the growing digitalization of healthcare, it is now certain that it has huge potential, especially given the release of 

 concerning the use of electronic health records and medical data for regulatory decision making for drugs and biologics. As the collection and use of RWD naturally evolved during the pandemic, with decentralized clinical trials taking off, it is clear that the industry has only scratched the surface in this area and that RWD is playing a growing role in drug development around the world.

However, real-world data means different things to different people. In general, the term applies to observational data that is collected in a routine clinical care environment, as opposed to data acquired in a more structured setting, like a Phase III clinical trial, where the environment is more controlled. In what is deemed to be the ‘real’ world, treatment is given and monitored in a patient’s natural environment, factoring in the influence of related medications, medical interventions, or concurrent illnesses, as well as the realities of life, such as accidentally missed doses etc. These external factors will heavily influence treatment outcomes and, therefore, the data generated as the output. Therefore, it is reasonable to question just how ‘real’ the data is in this setting, and whether it is, in fact, any more ‘real’ than data from a clinical trial setting.

The difference in the data collected in each of these settings really has nothing to do with how ‘real’ it is; data on a case report form designed by the clinical trial sponsor is just as ‘real’ as a clinical note obtained from a patient’s bedside chart to document their response to treatment in routine care. To better illustrate the possible confusion caused by the use of the term ‘real,’ we shall now look at five variables that are sources of tension between the more “natural” and the more “artificial” data.

 RWD (safety) is systematically collected in pharmacovigilance (PV) programs after the first approved indication is obtained and for as long as the drug is marketed, to supplement Phase III clinical trial safety evidence from registration trials and provide cumulative information on the evolving risk-benefit profile of the new treatment post launch. RWD (safety and efficacy) can also be collected to support label changes for products already approved, for example, use in a new population (different age group, different disease severity, change in dose, or route of administration, or adding a new indication (repurposing of existing medications)). Finally, RWD can also be collected to understand the impact of the new drug x indication on health economics and outcomes. So, despite RWD being a more commonly used term in routine clinical care, these are some obvious examples of how it is collected and used in combination with clinical studies and for regulatory decision making.

 Clinical report forms (CRFs) and their electronic versions (eCRFs) are not typically viewed as RWD, since they are not routinely collected by accountable care organizations (ACOs) and hospitals in general. Electronic health records managed by ACOs are considered RWD for the opposite reason. Data captured from wearables at the edge of the IoT network with experimental protocols cannot yet be considered as routine, even when the wearables are already approved by the regulators for their use in the study, but the situation is changing as a result of their increased adoption in routine care. So, the acceptance of whether data is considered as RWD, or ‘real,’ is not really linked to how ‘real’ it is, but to how routine it is. There is a big difference between the two terms. 

 The pandemic accelerated the adoption of decentralized clinical trials (DCTs), which have replaced traditional clinic visits with remote visits or home visits by mobile health care professionals (HCPs). Here, the “realness” aspect has to do with a reduction in participant burden and keeping one’s daily activities as unchanged as possible. Accordingly, this type of data collection can be viewed as more "natural" but there is a limit to this, as training on mobile applications and internet competence may cause an increase in participant burden or restrict the target population to tech-savvy participants, making the data less ‘real’, or, in other words, less reflective of the total patient population.

4. Departures from routine clinical care:

 Even though prospective real-world evidence (RWE) studies are playing a growing role in healthcare decision-making, it is still unusual for them to be solely and strictly based on routine clinical care. Typically, additional data needs to be collected that increases the burden on participants and HCPs, but to a lesser extent than in conventional randomized clinical trials (RCTs). There is a fine balance between minimizing the burden on patients and HCPs and leveraging patients' willingness to provide informative data. Randomized assignment of treatment alternatives is never done in routine clinical care, so the data could be considered, again, to simply be less representative, rather than real or not real.

 For regulators, data quality and assurance requirements for RWE studies should be in line with standard expectations for conventional RCTs. Randomized treatment assignment remains their preferred design, as it avoids physicians’ treatment allocation bias. Marketing and sales groups, however, which are the largest consumers of HEOR (Health Economics and Outcomes Research) studies, do not have to adhere to those standards. So again, the ‘realness’ of the data could be questioned by both of these audiences.

In conclusion, the reality is that almost any data generated could be called ‘real’—especially when you take into account that the opposite of real is fake—whether it is collected in a randomized clinical trial or in a routine care environment. However, it would usually sit on a scale of ‘realness' depending on its origination, use, and the five variables discussed here. So, in my opinion, the term real is a little misleading in the phrases RWD and RWE, as are the current limitations on when they are commonly used. All data is real, just how real is a matter of context and individual interpretation.

There is an unavoidable trade-off between minimizing sources of bias and introducing design features that depart from routine clinical care, thus impacting how ‘real’ data might be perceived to be. The result is that RWE is very rarely based on RWD that have not been subjected to some degree of scientific “adulteration” to facilitate the interpretation of the results.

Articles

Addressing sources of tension on differentiating types of data.

Just How ‘Real’ is Real-World Data?

Even before the COVID pandemic, most clinical trials already had decentralized components such as blood draws completed at locations other than the designated trial site. However, the pandemic created an opportunity for a new decentralized component, telemedicine, with remote visits. Inexpensive telecommunication platforms, immensely popular in ordinary life, became very successful in routine healthcare, as evidenced by the massive increase in telemedicine claims during the pandemic. Telehealth claim lines increased 2980% in the US from September 2019 to September 2020, according to FAIR Health's Monthly Telehealth Regional Tracker.

Telemedicine use in research also increased during the same period in hybrid decentralized and fully decentralized clinical trials (DCTs). DCTs used software and devices to manage nearly all aspects of consent data collection, patient engagement, authentication, and data verification. These changes were made possible by regulatory bodies including the FDA, EMA, and MHRA, which provided guidance to investigators to maintain patient safety, data quality and trial integrity. The other component of DCTs is the contribution of mobile/local healthcare providers (HCPs) to their execution. HCPs may offer a way for prospective trial participants to take part in many trials regardless of trial duration; frequency of visits; disease state; distance to the investigative site; and travel plans.

In this article, we highlight a technological advance in portable imaging that could further increase the scope of DCTs, but is it really feasible to keep adding technical responsibilities to the role of mobile/local healthcare providers working in a decentralized trial environment?

Not all clinical trials benefit from DCTs

Phase I studies that require frequent interventions, such as dose modifications remain best suited for traditional settings. Until now, the same could be said of studies that require serial imaging of deep structures and/or serial tissue biopsies. This restriction might go away with the development of portable devices that can provide precise images of deep structures that lend themselves to clinical grading.

As per the Clinical Trials Transformation Initiative (CTTI) recommendation, the “activities that mobile HCPs may be able to perform include clinical assessments, blood draws, IMP or treatment administration, participant education, and in-home compliance checks.”The recommendation does not include acquisition of imaging data but there is no reason why this should be excluded as long as “responsibilities are delegated consistent with state laws and the protocol and only to qualified personnel.”

Technological advance in portable imaging

According to a resident in anesthesiology in a rural public hospital in Brazil, he uses a hand-held ultrasound probe, to do regional blocks.

 Portable ultrasound probes are already used in some decentralized settings. For instance, some emergency paramedical personnel do scans during transportation of severely wounded patients to a level 1 trauma center. This technology could be used, with the proper precautions, including validation, training, supervision etc. by a HCP visiting a participant in a clinical trial, where the outcome is based on imaging of a particular organ. Cancer progression, vascular changes, evolution of inflammatory processes could, in principle, be monitored remotely from the home of the participant. The interpretation of the image does not have to be done by the HCP, as this would cause all kinds of legal risks and IRB disapprovals. Instead, the HCP could communicate via a secure transmission protocol (zero trust) with a licensed radiologist who, incidentally, could work from home too, as many have done during the pandemic.

The future role of HCPs in clinical trials

One problem with the addition of an ultrasound imaging skill to the list of helpful activities that a HCP could perform to facilitate the execution of a DCT is that the list is already long without it. In addition to the list proposed by CTTI mentioned earlier, there are several other skills to consider:

Spokesperson: being the face of the trial, the ambassador of the investigative site, the CRO and the sponsor.

Phlebotomist: this skill is expected to remain a key element of any HCP task description.

IT technologist: the reliable operation of wearable devices often depends on the availability of technical support and troubleshooting but remote/virtual support may not work for all participants. Face-to face interactions with an HCP may be the only solution to permit the use of wearables by those participants who are older, less educated, and do not use the internet or rarely. To ensure that a confusing app or interface doesn’t stymie participation, Bisola Ojikutu (Executive Director of the Boston Public Health Commission) suggests that trial designers include instruction in technological literacy so that all participants can engage equally.

 It is doubtful that such a didactic approach can bridge the “technology divide” unless the participant can rely on a live coach/troubleshooter (from providing batteries to testing transmission methods and internet infrastructure) who has the skill to teach the participant how to use a super simple version of the software used in ePRO or in conjunction with a wearable.

Project manager: coordinating disparate activities between the participants’ homes, the investigative site, the IMP supplier, and the lab.

Social worker: accounting for environmental and social determinants (the “exposome”).

The future training of HCPs working in clinical trials

In addition to the need to be trained on the technical skills listed above, “ideal” mobile HCPs also need to be trained on good clinical practice, trial-specific requirements, human participant protections, and data protection.

Will HCP vendors with experience in clinical trials be able to find candidates and train them on all these components, as well as introducing new requirements, such as ultrasound imaging? That sounds like a big ask. Maybe the solution will be to have more than one HCP visiting the participant’s home, or rejecting technologically challenged participants who cannot rely on a technologically competent caregiver, but this would go against the goal of increased inclusiveness in clinical trials. The industry therefore has a dilemma that needs to be addressed if the true promise of DCTs is to be realized.

Most trialists expect that the popularity of DCTs will increase because decentralized trials have benefits (some proven, some not) that include fewer trial sites and reduced number of IRBs and resubmissions; reduced variability, improved compliance, a potential increase in study safety, outcomes that more closely reflect the real-world environment, and improvement of trial access for participant populations that are currently underrepresented.

An evaluation of the clinical trials landscape by Ken Getz (Tufts Center for the Study of Drug Development) suggests that small trialists, or actual principal investigators filing one 1572 per year are abandoning the field of clinical trials to those investigators that file several 1572s per year.

 This suggests that conducting clinical trials is becoming so complex that only large centers conducting several trials concurrently can afford the investments to support them. Getz predicts a retrenchment and more conservative application of adaptive and innovative practices as we move into a post-pandemic world.

As to the coordinating aspects of decentralized trials, it is worth noting that the traditional role of the coordinator at the investigative site is being transferred (at least in part) to the mobile HCP. As a practical note, we recommend that DCTs that rely on mobile HCPs always be preceded by a feasibility study to minimize the need for protocol adjustments after study start.

M. Apostolaros et al., Legal, regulatory, and practical issues to consider when adopting decentralized clinical trials: Recommendations from the clinical trials transformation initiative. Therapeutic Innovation & Regulatory Science (2020) 54:779–787 

https://doi.org/10.1007/s43441-019-00006-4

EagleView™ Dual-head Wireless Handheld Ultrasound

https://getwellue.com/products/eagleview-dual-head-wireless-handheld-ultrasound

M. Banks. In the wake of COVID-19, Decentralized trials move to center stage. PNAS 2021 Vol.118 No.47 22119097118 

Tracking change in the global investigative site landscape. 

2021 [online] Applied Clinical Trials. Available at: ,

https://www.appliedclinicaltrialsonline.com/view/tracking-change-in-the-global-investigative-site-landscape

Contemplating the Full Measure of Pandemic Response

. 2021 [online] Applied Clinical Trials. Available at: <

https://www.appliedclinicaltrialsonline.com/view/contemplating-the-full-measure-of-pandemic-response

Portable imaging technology presents yet another opportunity for decentralized trials.

Pierre Etienne

Articles

Just How ‘Real’ is Real-World Data?

Role of Healthcare Providers Expands in DCTs