Randomized Controlled Trials (RCT) have long been the standard for verifying the efficacy and safety of pharmaceutical drugs. However, over the years, payers and health care providers alike have increasingly been seeking a revamp of this research process. As clinical trials are traditionally based on several challenges including ‘Placebo effect’, investigator bias, inconclusive data, etc, and there is a significant likelihood of emergence of skewed results, which may not depict real-life scenarios.
With the advent of Big data processing capabilities, Real World Evidence (RWE) has played a supporting role with respect to RCT. RWE was primarily employed to determine if trial data could be applied at a large scale to actual patient demographic. However, RWE is surpassing RCT, and moving to the forefront, given the multiple benefits that it can help pharma companies realize, including a discovery of new opportunities and the ability to illustrate value through application.
Case for RWE
1. New indication for Shelved molecules:
The ongoing paradigm shift toward value-based, individualized health care makes the case for drug makers to embrace real-world evidence a compelling one. It is imperative for the pharmaceutical industry now to tackle hard-hitting aspects of medicine, including deep-dive research determining the efficacy of a drug administered to different types of patients in varied contexts.
In fact, burgeoning electronic devices like wearables, digital records of health information, such as medical reports and insurance claims are creating an ever-expanding multidimensional database of the real-world evidence. With ‘data lakes’ able to provide multi-dimensional yet personalized view of medicine, one of the key utilization of such Big data analytics is to discover New Indications for Shelved Molecules. While new trials cannot be avoided for regulatory approval, such deep analytics provides insights on ‘what subsection’ of patient population to conduct the new trials on. There are several examples of past shelved molecules which have succeeded in this journey. One such example is California-based biopharma for spectrum for Non-Hodgkin’s Lymphoma which was earlier rejected and later cleared for older patient population over 65 years due to such RWE and ‘Deep analytics’.
2. New indications for already approved Molecules
While randomized control trials are the conventionally accepted approach, regulatory approvals prove to be a roadblock in providing timely interventions for life threatening diseases in oncology, hematology and neurology. Delay in reimbursements and J-codes further cause delays in access to payer coverage resolution.
Real-world evidence supplements RCT by facilitating measures of effectiveness, providing ample, relevant sample sizes over longer periods, and enabling documentation of long-term patient behavior. Given the current resource constraints of health care systems, RWE can leverage care delivery analysis and resource utilization, quantifying actual costs.
Pharmaceutical companies can obtain the go-ahead on new indications of approved drugs sooner than before, by leveraging real-world evidence and minimizing the need for an expensive late stage clinical trial for new indications for already approved drugs. Organizing and recruiting ideal subjects for targeted clinical trials is often a significant challenge for pharma companies. In this context, RWE can prove to be a crucial enabler as it can provide actionable insights regarding patients, as well as help organizations enlist them for trials.
3. RWE in Personalized medicine
As real-world evidence makes headway in personalized health care, the following major trends are emerging with regards to the pharma’s adoption of the same:
- Enabling decisions: Correlating longitudinal clinical data sets with genomic data sets to foster a better understanding of subjects, RWE is quickly evolving as a crucial factor in the decision-making process of pharmaceutical companies.
- Promoting safety Benchmarking Analytics by Predictive Signal detection: Moving beyond reporting, RWE is generating “signals” to alert companies about cautionary data sets.
- Evaluating value: Amid stringent compliance norms set by regulators and Health Technology Assessment (HTA) bodies, RWE is becoming mandatory in formulation of data packages for reimbursement, as well as in assessment of medical intervention efficacy. While merit of the data and assimilation of data from diverse sources pose a challenge, isolated RWE samples still prove to be useful in reimbursement.
Role of Big data technologies in RWE trials:
RWE spans varied and numerous information sources including wearables, EHRs and claims repositories. However, the data is not in a ready-to-consume format, and the industry still needs to ascertain the best ways of exploiting the collected data. Pharma must use technology to effectively organize, analyze and evaluate the rapidly growing volume of information, for robust data quality, integration and accessibility. This where the advance in Big data technologies and ability to create multidimensional data-lakes comes to the rescue.
Real-life success stories
In the context of diabetes treatment, one of the leading research-based, biopharmaceutical firms contrasted the safety of two different treatments to determine the safer alternative. The company employed real-world evidence involving over 200,000 diabetic patients to assess the risk of cardiovascular issues associated with administering Dipeptidyl peptidase-4 (DPP4 inhibitors) as compared to Sulfonylureas.
To ensure accurate results, the research-based, biopharmaceutical firm used multiple groups, applying parameters such as the presence or absence of CVD codes in claims data, demographics, clinical and alternative risk factors noted in patients’ medical records. Moreover, the company assessed the probability of death ratios for every cohort. The RWE-based study enabled the UK-based drug major to establish that the use of DPP-4 inhibitors did not increase risks of heart failure, when contrasted with Sulfonylureas.
Future of Clinical trials using Blockchain?
With the advent of blockchain technologies, the ability to simultaneously update multi-locational, multi-dimensional data in real-time is possible, however its suitability for conducting double-blinded randomized clinical trials, which can be conducted under compliant regulatory environment is yet to be seen. Can blockchain help in reducing time to database Lock and Lab data availability in a secure and compliant format? Can it help to manage data across multiple Trial Administrators spread across the globe in a double-blinded manner? Can right encryption technologies be merged with blockchain technologies to achieve the above? Some unanswered questions all worth exploring!
RWE is not making RCTs obsolete. Instead, the future of clinical trials is likely to be a combination of both approaches. The introduction of laws like America’s Century Cure Act and Europe’s Adaptive Regulatory Pathway create an opportunity for biopharma companies and regulators to discuss how real-world evidence can accelerate drug discovery and approval. And, given the current low levels of patient population engaged with trials, the pace of industry-wide adoption of real-world evidence leveraging the power of ‘big data technologies’ looks set to increase significantly. Is blockchain the cutting edge for R&D technology? This is yet to be answered!
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