FDA’s Newest Contribution to the Real-World Evidence Revolution: Innovative Frameworks to Streamline Regulatory Submissions

TLDR: The FDA has released its finalized framework on real-world evidence (RWE) use in regulatory submissions - a move that aligns the U.S. with its global counterparts. With the prior ambiguity regarding effective regulatory submissions resolved, pharma can direct their focus on addressing RWE limitations such as data quality issues, and biases to reap RWE’s likely benefits of significant cost savings and streamlined clinical development.

You’ve heard about RWE ad nauseam, and probably thought it was another marketing punt by pharma, but now it seems that the regulators are finally making it official!

In August 2023, the FDA finally published their long-awaited finalized framework for pharma on the use of RWE and real-world data (RWD) to support the regulatory review of drugs and biologics. This is lagging behind the EMA and China’s NMPA who published their frameworks in June 2023 and January 2020, respectively. Prior to this, RWE was leveraged in regulatory submissions as outlined by draft guidelines at the time, but (a) it was not clear exactly how best to incorporate RWE and navigate regulatory submissions which included it and, (b) it was considered more on a case-by-case basis. Over the years, in response to the regulatory authorities’ growing receptivity of RWE, pharma companies have and continue to invest more in internal RWE talent and technologies to support end-to-end clinical development. By the end of 2020, 90% of new drug approvals in the U.S. included RWE as part of their submissions in some shape or form. However, there was still uncertainty around how pharma can more effectively leverage RWE to achieve greater success. These now finalized frameworks aim to demystify the process, calling for pharma to consult the agency early in the drug development process and help pharma effectively include RWE.

Substantial cost savings and increasing likelihood of approvals – what’s not to love?

One of the most attractive benefits for pharma including RWE as part of regulatory submissions is saving on costs and time in running a clinical trial. In an IQVIA report based on multiple case studies, using RWE can save up to $200M on clinical development costs by improving enrolment by 30% and allowing for better product profile design. By expediting safety monitoring and simplifying trial and data collection, it is estimated that RWE can reduce trial costs by between 5-50%. An example of this is running a single-arm trial with an external control arm from RWE – a strategy BMS used to achieve FDA approval of a new indication for ORENCIA®. The sBLA included results from a prespecified matched cohort from the CIBMTR registry as a control arm.

Multiple FDA approvals have been granted for label extensions based on RWE demonstrating effectiveness, most notably Pfizer’s IBRANCE® to include men with HR+/HER2- advanced or metastatic breast cancer in April 2019 (originally approved for postmenopausal women). The approval was based on data from electronic health records (EHRs) and post-marketing reports of the real-world use of IBRANCE® in men, where the Chief Medical Officer noted that the amount of data collected by RWE greatly exceeded what a clinical trial could have gathered in the same amount of time.

It's not all sunshine and roses…RWE use doesn’t come without some key limitations

With the benefits becoming increasingly realized in the industry, pharma companies must be aware of the limitations associated with RWE. Due to the inherent differences between RWE and randomized control trial (RCT) study designs, results from both types of studies can often contradict each other. For example, an analysis of the ASCO Value Framework concluded that real-world overall survival for cancer therapies is ~16% lower than efficacy estimates based on RCT surrogate endpoints. Differences can be a result of variances in endpoints, poor RWD quality, bias within the RCT or collected RWD leading to incomparable patient populations to name a few:

• Potential for bias confounding in RWD collection: RWD's unstructured collection from diverse sources can introduce biases, potentially distorting treatment study comparisons due to patient population differences.To ensure accurate RWE comparisons for specific indications, studies must feature similar patient profiles and may employ propensity scores based on treatment likelihood predictions, mitigating these biases.
• Limited endpoints in RWE studies compared to RCTs: RWE often relies on broader or less clinically measurable endpoints, making it unsuitable for standalone regulatory submissions but valuable for label expansions in broader patient populations alongside RCT data.
• Uncertain data quality when obtaining RWD from various sources: Data quality can be unreliable and fluctuating, and there is currently no unanimous agreement on what constitutes good quality RWD; therefore, these robust international frameworks are needed to assess the completeness, accuracy, and comparability of the data.

If you haven’t already gotten on board, now’s the opportune time!

With their newly published framework, the FDA now aligns with its global counterparts in providing concrete guidance to pharma on navigating regulatory submissions, such that they can focus their attention on overcoming the intrinsic limitations of RWE. To truly realise the rewards of RWE, pharma must collectively drive universal protocolization and standardize its use across the industry. These frameworks offer pharma access to earlier dialogue to discuss RWE utilization, as well as clearly describe how it can effectively be used and how far its capabilities reach. For example, using RWD as a comparator arm in an external RCT, to drive enrolment of RCTs, and/or to inform endpoint selection. Considering the power of RWE, pharma companies should consider engaging and collaborating with the FDA as early as possible – as doing so may lead to time and cost savings through available frameworks.