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The USFDA defines real-world data (RWD) as ‘the data relating to patient health status and/or the healthcare delivery that is routinely collected from a variety of sources’, and real-world evidence (RWE) as ‘the clinical evidence regarding the usage and potential risks/benefits of a medical product obtained from analysis of RWD.’[1] RWD includes data from electronic health records (EHRs), administrative and medical claim databases, pharmacy data; data from product, patient, and disease registries, patient-generated data (including in-home use settings, social media data, patient forums, etc), and data gathered from other sources that can inform on health status.[1]

RWD has been extensively used for pharmacovigilance in the form of phase 4 post-marketing surveillance studies. Lately, it is being realised that RWE and RWD can play additional role in the drug approval cycle. For example, the approval of Avelumab for the treatment of metastatic Merkel cell carcinoma (MCC) in March 2017 utilised electronic health record (EHR) data as historical control data for efficacy. Likewise, the approval of Lutetium Lu 177 dotatate for the treatment of certain neuroendocrine tumors in 2018 by the USFDA made extensive use of safety and efficacy data from the ERASMUS study, which was an expanded access study.[2]

RWD has also been used for market access and to make reimbursement decisions in several countries. For example, in France, RWD collected during temporary authorization for use of a drug can be used to assess the price and level of reimbursement through health technology assessment (HTA). In the UK, RWD collected during early access to medicine scheme can be used as dossier of market access. In fact, the UK NHS has performed cost-effectiveness studies based on RWE and established a scheme to collect RWD for pharmacovigilance purposes. RWD are also used for pay-for-performance schemes in the USA.[3]

Despite the raising importance of RWD in improving market access, a constant critique of RWD is that, since RWD is collected from routine healthcare, there is no set objective for RWD collection, unlike randomized controlled trials (RCTs) which generally have an objective and hypothesis. In other words, since RWE studies are secondary analysis of existing data that are collected unplanned (i.e., without a specific objective), they are susceptible to bias; this is not that prominent an issue for pre-planned studies of prospectively collected data (such as RCTs). Thus, there are high chances that RWE studies are more susceptible to results-driven design modifications than RCTs, thus bringing a question about transparency of RWD and the resulting RWE.[4]

Data transparency improves the ability of decision-makers to assess the quality and validity of an RWE study by giving a deeper understanding of why and how the research was conducted and whether the results reflect pre-established questions and methods. It also facilitates the replication of results and an understanding of why findings of apparently similar studies differ. In line with these concepts, attempts are being made to improve RWD transparency, with an intention to strengthen the confidence that different stakeholders have on RWD, thereby further boost its usage for different aspects, including enhancing market access of drugs.[4]

One such method for improving data transparency is by promoting registries for RWE studies. Though existing registries register and ClinicalTrials.gov) collect many features that are required for improving data transparency, they focus on primary data, and are not specific for RWD.[4] In 2017, International society for Pharmacoeconomics and Outcomes Research (ISPOR) and International Society for Pharmacoepidemiology (ISPE) formed a joint task force to identify good practices for addressing the concerns and to enhance confidence in evidence derived from RWE studies. The ISPOR-ISPE Special Task force recommends the researchers should declare the hypothesis to be tested, post study protocols and analysis publicly; and during publication attestation of any conformation or deviation from the initial study protocol.[4] In lines with the same, the ISPOR RWE registry was formally launched in October 2021, and represents a fit-for-purpose platform for registering RWE study designs prior to data collection, with an intention to facilitate RWD transparency and to elevate the trust in the study results; the RWE registry can be accessed at https://osf.io/registries/rwe/discover.

Another method to improve RWD transparency is the concept of tokenization of healthcare data, by which different sources of patient-level RWD (for example; claims, EHR, registries, molecular biomarkers, and laboratories) can be linked to provide a complete, non-duplicate, and comprehensive understanding of the patient’s health. By providing an option to cross-check same patient data from different sources, tokenization can help improve the confidence in RWD from different sources.[5]

RWD play enormous role in research and development process, they also help in estimating the risks and benefits of any treatment in real world scenarios. Enhancing RWD with transparency can go a long way in increasing its usage for market access.

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References

1. Framework for FDA’s real-world evidence program. Dec 2018. Available from: https://www.fda.gov/media/120060/download
2. Feinberg BA, Gajra A, Zettler ME, et al. Use of real-world evidence to support FDA approval of oncology drugs. Value Health. 2020 Oct;23(10):1358-1365. 
3. Pulini AA, Caetano GM, Clautiaux H, et al. Impact of real-world data on market authorization, reimbursement decision & price negotiation. Ther Innov Regul Sci. 2021;55(1):228-238.
4. Orsini LS, Berger M, Crown W, et al. Improving transparency to build trust in real-world secondary data studies for hypothesis testing-why, what, and how: recommendations and a road map from the real-world evidence transparency initiative. Value Health. 2020 Sep;23(9):1128-1136. 
5. Dagenais S, Russo L, Madsen A, et al. Use of real-world evidence to drive drug development strategy and inform clinical trial design. Clin Pharmacol Ther. 2022;111(1):77-89.