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Expanded use of RWE (Real World Evidence)

Expanded use of RWE (Real World Evidence)

With a laser-like emphasis on results and value, healthcare is fast moving to a new world of patient choice. Indeed, healthcare systems that have historically emphasized medical treatments based on episodic interactions with patients are now realizing the need to fully comprehend external variables and provide ongoing care.

Exogenous factors like genomics, conduct and social and ecological impacts assume a basic part in conveying results and an incentive for patients and wellbeing frameworks; in the meantime, innovation is, at last, permitting the catch and investigation of such genuine information. This paper discusses the expanded use of RWE in the clinical healthcare domain.

What is RWE?

Real-world evidence is clinical data produced by RWD analysis on the use and possible advantages or hazards of a medical product. RWE can be produced by a variety of research designs or analyses, including but not limited to randomized trials, pragmatic trials and observational studies (prospective and/or retrospective).

Use of RWE in Clinical Trials

Clinical trials are typically meant to show if a drug or therapy works in certain circumstances and as a result, they include a lot of inclusion and exclusion criteria. This restricts the number of individuals who are eligible for the clinical study, as well as the generalizability of the trial’s findings to other patients with the same condition.

By providing a detailed picture of the patient journey and treatment experience in the real world, RWE provides context to RCT outcomes. Data from normal hospital or doctor visits, patient registries, claims reports, linked devices, prescription data, observational studies and other primary and secondary patient-level data can all be used to collect these observations. Using real-world data and evidence can assist bridge the gap between the RCT and the genuine effectiveness and safety profile of a product in the real world.

There are, nevertheless, certain methodological considerations to make. Because RWD is gathered in non-controlled environments, the data’s overall quality and completeness may vary; several circumstances may influence who has access to which therapy, how it’s utilized and the underlying risk of clinical outcomes. It’s possible that the data was gathered in an inconsistent manner, that it was duplicated, or that some information was missing. It is frequently supplied by patients themselves, who can provide valuable information about how an illness affects them but are unlikely to use medical words to describe their symptoms. This implies that businesses must have a clear RWE plan in place, as well as proper analysis methodologies, to satisfy regulatory authorities, payers, providers and patients.

When is RWE considered for use?

RWE is increasingly being used in post-launch applications such as pharmacovigilance. RW studies, on the other hand, can be beneficial throughout the medication development and commercialization process. There are basically three stages at which RWE is practiced or can be used:

  • Pre-Launch Stage

Early in the drug development process, RWE studies can be used to detect illness burden on patients and the healthcare system, treatment patterns and disease epidemiology. These insights may be utilized by developers to choose clinical trial objectives and target recruiting efforts, as well as to predict cost-effectiveness for HTA organizations and payers, to demonstrate to physicians how the product will fit into current clinical practice and to assist find undiagnosed individuals.

  • Post-Launch Stage (Pharmacovigilance, phase 4 studies)

RWE studies can be used at this stage to gain conditional approval from regulatory authorities, demonstrate real-world benefits for HTAs and payers and gain leverage in pricing negotiations by understanding real-world treatment patterns and risks of outcomes (which will typically differ from what is seen in clinical trials), as well as gain conditional approval from regulatory authorities, demonstrate real-world benefits for HTAs and payers and gain leverage in pricing negotiations. These data may also be utilized to illustrate treatment benefits to physicians and patients, as well as help, create value messaging.

  • Line Extensions

RWE studies that show efficacy and acceptability in new patient groups can assist make the case for line extensions with regulatory authorities, support the argument for greater access with payers and reassure clinicians that it is acceptable for new populations.

FDA Perspective on RWE

Real-world evidence (RWE) is defined as healthcare data derived from multiple sources outside of typical clinical research settings, such as electronic medical records (EMRs), claims and billing data, product and disease registries and data gathered by personal devices and health apps, according to FDA researchers.

The FDA has welcomed RWE’s beneficial applications, notably its ability to improve hypotheses and study design, as well as expand our understanding of a product’s impacts on populations other than those investigated in clinical trials. Randomization is not included in the FDA’s definition of RWD. The FDA also underlines that the distinction between RWD and data gathered from research-intensive/clinical trials should not be established based on the existence or absence of planned intervention, since both are consistent with RWD. The FDA has also brought up the problem of rising clinical trial expenses without a matching rise in the amount of data generated to support healthcare choices.

The FDA has said that it is critical to understand RWE to create proper expectations for its usage. While carefully controlled clinical trials can offer proof of a product’s efficacy, RWE can supplement this finding by decreasing the findings’ “uncertainty regarding generalizability.” Outside of the confines of a clinical trial, RWE can give statistics on patient compliance.

The FDA regards RWE as having the potential to ‘complement’ data from clinical trials and plays a key role in supporting/strengthening the evidence base for safety and efficacy throughout the drug development life cycle, for many of the reasons indicated above (encompassing both pre-and post-market regulatory decisions). RWE may help with regulatory decisions like label extensions or additional indications for authorized medications, as well as confirmatory studies for drugs approved under the FDA’s accelerated programs. It can also help with Phase IV post-marketing monitoring and surveillance.

Conclusion

Optimizing the use of RWE, especially with data analytic enhancements, for approval of new indications and post-approval requirements can reduce cost and time burdens for pharmaceutical companies, enhancing their profitability.  Moreover, direct and concrete benefits can be experienced by the patients by the accelerated delivery of medical products to those that need them.  Given the highly competitive nature of the industry and the huge hurdles of drug R&D (in cost, time, risk), applying the latest tools to generate RWE will bolster competitive advantages, a path encouraged by the FDA.

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