In this era of evidence-based medicine, clinicians, payers and patients are eager to understand what therapies will truly impact patient outcomes. Gold standard intervention-based trials can’t always answer this question adequately.
Such studies seek to remove confounding factors to establish a direct causal link between therapy and patient outcome. In the real world, there are countless variables that cannot be controlled, including co-morbidities, drug adherence and differences in lifestyle. Ultimately, this can create a knowledge gap between a drug’s efficacy (ie, what is measured in a traditional clinical trial) and its effectiveness (ie, how well it works in practice).
Acknowledging this limitation, drug developers are increasingly interested in utilising real-world evidence (RWE) to complement clinical trials and generate evidence translatable to wider populations. The inclusion of real-world data (RWD) may provide a more complete benefit-risk profile of a treatment for a patient than traditional trial data alone. Regulatory agencies are issuing new frameworks and guidelines for trial designs that include randomised pragmatic trials and studies that employ non-interventional RWE to test safety and effectiveness. Biotechs, which represented more than three-quarters of late-state R&D pipelines in 2018, are well-poised to make significant contributions to advancing use of RWD and RWE.
Understanding the problem
Imagine a patient, Paul, who has type II diabetes, hypertension and arthritis. Paul’s doctor has decided his diabetes isn’t sufficiently controlled, so wants to prescribe a recently approved medication, drug X, to lower his blood glucose levels and improve overall health. But will Paul benefit from drug X? Based on the clinical trial data alone, we don’t know. To prevent confounding factors, people like Paul weren’t enrolled, so we don’t know if the drug works well for those with his co-morbidities, or if those co-morbidities may require a different treatment regimen. Traditional clinical trial approaches do not generate the data needed to address patients like Paul. Typically, information on the safety and effectiveness for patients who do not meet inclusion criteria of a clinical trial is learned after a drug is approved and on the market. This has significant implications to treatment and reimbursement decisions.
New regulations for RWE
RWE is increasingly being used in premarket regulatory decision- making. Although this is a work in progress, several key milestones have been reached. For example, in 2018, the US Food and Drug Administration (FDA) released its Framework for FDA’s Real-World Evidence Programme, which included two key definitions:
* RWE: Clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD
* RWD: Data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources.
These definitions are necessarily broad as RWE can be derived from many different data sources and methods. Insurance and prescription databases may be mined, observational studies can be run using electronic health records, or sponsors can present the natural history of the disease (ie, left untreated, how would the condition progress?) through literature reviews.
Stakeholders have demonstrated particular interest in RWE used in randomised pragmatic clinical trials (PCTs), which combine features of routine clinical practice into trial designs. A primary benefit of this trial design is that it utilises RWD to gather evidence of how a drug works. Accordingly, at the time of approval, more is known about how the drug will perform across a range of patient populations once it is on the market.
The National Institutes of Health (NIH) Collaboratory is actively engaged in efforts to increase understanding of PCTs through demonstration projects. One example is the Nudge Demonstration Project, a study hoping to address poor prescription compliance observed in cardiovascular patients. It hypothesises that behavioural reminders that utilise ubiquitous mobile phone technologies for health promotion and disease self-management might prove useful for facilitating medication adherence. The project uses population- level pharmacy data to deliver nudges via text messaging and an artificial intelligent interactive chat bot, with the goal of improving medication adherence and patient outcomes in three integrated healthcare delivery systems.
Guidelines for evaluation
There are many different sources of RWD, yet no universal approach for applying those sources has been be qualified. However, some key principles for determining the reliability of RWE, based on verification checks and documentation requirements, have been defined. Chief among them are the need for a sufficient number of patients to achieve significant results, staff familiar with routine clinical practice and standardised equipment involved in the execution.
In Europe, regulatory groups have established a number of working groups to define how and when RWE can be applied. One example is the UK’s Academy of Medical Sciences. In 2018, it released Next Steps for Using Real-World Evidence: a summary report of an industry roundtable. Along with definitions, the report details how the Medicines and Healthcare Regulatory Agency (MHRA) views RWE, and how it can be applied beyond existing uses, such as pharmacovigilance – part of an initiative known as the Early Access to Medicines Scheme.
RWE has long been used for post-market activities and in rare diseases. Additional applications for use of RWE in pre-approval decision-making, such as label expansion and external comparator studies, are increasingly being used, though they are not yet routine. Frameworks and guidance from regulators in the US and EU are forthcoming, as demonstration projects and validation studies provide greater understanding of when and how RWE may contribute to the totality of evidence needed for regulatory decisions.
* In the US, the FDA Framework describes its approach to evaluating the use of RWE for review of drugs and biologic products. This ties into the 21st Century Cures Act, which aims to deliver new therapies to patients faster and more efficiently
* In Europe, the European Medicines Agency (EMA) introduced its Medicines Adaptive Pathways for Patients Initiative in 2016 to explore the ethical considerations of taking a non-traditional RWE approach to studying new therapies
*In the UK, the MHRA is looking to expand RWE beyond pharmacovigilance.
Together, these efforts demonstrate that regulatory bodies are embracing the potential of RWE to accelerate drug development. While far from complete, these early guidelines provide the industry with some frameworks to use RWE for indication expansions, external comparator studies, and post-approval safety studies.
The need for collaboration
To advance the use of RWE, regulatory bodies, patient advocacy groups, small biotechs and large pharma must work together.
Regulatory agencies need to evaluate RWE under a variety of circumstances. Criteria established in one context, such as indication expansion, may not be relevant in another context, such as pre-market studies. Feasibility and pilot studies for new use cases, such as new data sources or applications for methods in different therapeutic areas, may be needed.
As regulatory agencies continue exploring ways to optimise RWE, sponsors need to work with the FDA, the EMA, and/ or MHRA to design hybrid studies that combine elements of interventional studies and RWE. The intent is to expand confidence of these evolving methodologies. To this end, the FDA and MHRA are encouraging companies to communicate early in the development of their clinical protocols. This allows regulatory bodies to provide feedback and bring clarity to how and when RWD can be integrated.
With these ongoing efforts of drug companies and regulatory agencies alike, the future looks promising for real-world evidence and, in turn, for medical progress and the outcome of patients like Paul.
By Marni Hall and Nicola Stanislaus
Source: Pharma Times
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