Accelerated approval: how real-world data could help end the controversy

To improve evidence generation after accelerated approval, FDA should look to real-world data: a guest commentary

The FDA’s newly strengthened oversight over accelerated approval will help ensure confirmatory trials are started promptly, but to achieve a step-change in the pace of drug development and evaluation, manufacturers need better tools to conduct these trials. Greater use of real-world data in post-approval confirmatory studies could be a key part of the solution.

The accelerated approval pathway has come under scrutiny in the wake of the controversial approval of Aduhelm (aducanumab) to treat Alzheimer’s disease. And although most drugs go on to receive full approval after an accelerated approval, those that are withdrawn spend an average of nine years in the program, versus the four-year average of their fully approved counterparts. This has fueled concern that companies can drag their feet in confirmatory studies to keep lucrative, but ineffective, drugs on the market.

Congress’ recent attempt to shore-up the pathway has strengthened the FDA’s regulatory authority by enabling the agency to require initiation of confirmatory studies prior to accelerated approval, set targets for enrollment, demand twice-yearly progress reports, and slightly simplify procedures for expedited withdrawal.

These reforms don’t address a fundamental problem, however, which is that clinical trials are expensive, slow, and patients are not motivated to participate once a drug is approved and can be obtained outside of a trial.

Real-world evidence (RWE) could help fill this gap, and a provision in the recent reform package creates an opportunity for action.

The reforms require FDA to issue guidance on the use of novel clinical trial designs after accelerated approval. FDA should seize this opportunity to create a policy that encourages the use of pragmatic trials that rely on real-world data (RWD) to fulfill confirmatory study requirements. 

RWE and pragmatic trials not only promise to greatly accelerate the generation of evidence on safety and efficacy after accelerated approval, they can do so without compromising access to these drugs.

Moreover, such a policy would encourage the development of infrastructure to collect RWD, which could have benefits beyond accelerated approval, speeding the pace of innovation across the biomedical technology ecosystem.

Real-world promise

RWD could accelerate generation of several types of evidence after an accelerated approval, while facilitating broad access to the approved therapy.

First, all patients who receive a drug under accelerated approval should be entered into prospective registries, which would primarily be populated by extracting data from their electronic health records (EHRs). This process can be streamlined so that it does not distract from the routine care they receive, or place excessive burdens on patients or clinicians. These registry cohorts would detect safety events, could be used to validate surrogate endpoints, and help inform the design of future trials.

Second, RWD could be used to accelerate pragmatic randomized-controlled trials (RCTs) designed to evaluate efficacy. Traditionally, RWD has been viewed as a source of data for non-experimental, observational study designs, but there is growing recognition that RCTs can be performed using RWD, by extracting certain data elements, such as co-morbidities, medications, laboratory values, among other pieces of information, directly from the EHR.

Trials that rely on RWD, such as the RECOVERY COVID-19 trial, are usually pragmatic trials, in that they aim to include diverse patient populations that are reflective of who is likely to receive a drug or treatment in everyday clinical practice, and they involve few trial-induced changes in clinical care. This allows them to rapidly enroll a large number of patients at relatively low cost. At one point, RECOVERY enrolled one in every six patients entering the hospital with COVID-19 in the U.K., thanks to its reliance on RWD and pragmatic design.

RWD is crucial to pragmatic trials because it reduces resource requirements for data entry and trial administration, making participation easier for medical centers in a wide range of settings, which could reduce racial and geographic disparities in trial enrollment.

By automatically extracting information that would otherwise have to be entered manually, identifying eligible patients, and focusing trials on outcomes that matter most to patients — through collection of electronic patient-reported outcomes via surveys or smartphone applications — these trials could be cheaper and faster to conduct, without compromising the validity of confirmatory results.

Removing barriers to RWE: a case for standards

Despite their promise, real-world trials and registries after accelerated approval face major barriers, as there remains a lack of incentives and infrastructure to collect RWD on a national scale.

FDA has published a framework for the use of RWE in regulatory decisions and recently initiated the advancing RWE program to increase the use of RWE in support of new labelling applications. So far, however, RWE has only been used in a limited set of changes to approved indications.

The reasons few clinical trials rely on the EHR include the fact that not all sites use the same EHR vendor, data quality is variable, and some important data are not recorded in a structured way.

A recent study found that none of the 50 post-approval studies conducted between 2009 and 2018 could be replicated using EHR or administrative claims data because inclusion, exclusion, or endpoint data could not be ascertained from sources of RWD. Another study by the RCT Duplicate Initiative managed to replicate findings of several RCTs using claims data, but found that such analyses were least reliable when the RCT in question compared the study drug to a placebo. RWE in its current form is not yet suited to replacing most regulatory trials.

This gap could soon be bridged, however. Tools are being developed that can integrate the generation of trial data from the EHR into the routine conduct of clinical care. The OneSource framework, developed in collaboration with the FDA, is one solution to meet these needs. OneSource automates extraction of structured EHR data, such as medications, vital signs, labs, and demographics, and the software is designed to facilitate use of checklists during care to ensure collection of minimum essential data.

The federal government could go a long way toward optimizing this integration process by issuing standards for research applications like OneSource that integrate into the EHR, which would allow vendors to compete on the development of tools that make it easy to collect minimum essential data sets at the point of care. This data could then be used in both observational registries and clinical trials after accelerated approval.

Standards would also be useful in overcoming the fragmentation of the U.S. healthcare system, in which many patients receive care in a variety of different hospital systems, with different EHR systems. This can pose a challenge for clinical trials and registries which require high rates of follow-up.

Recently, the Office of the National Coordinator for Health Informational Technology (ONC) published rules regarding the interoperability of certain EHR data. However, these data standards are not sufficient to meet the needs of clinical trials and registries. ONC should develop standards for the interoperability of data for clinical trials and registries that includes both inpatient and outpatient providers. This would support the collection of consistent, high-quality RWD after accelerated approval, no matter where patients receive care. Beyond collecting data for drug approval, this would enable healthcare delivery organizations to develop learning healthcare systems that generate evidence to support improvements in care.

A win for all stakeholders

Building the generation of RWE into post-accelerated approval reporting requirements could be a key incentive to accelerate the adoption of tools that can generate high-quality RWD. These tools could in turn accelerate the pace of innovation in the U.S. healthcare system and provide a win for all stakeholders.

Manufacturers would benefit because instituting mechanisms that efficiently generate convincing evidence would reduce the cost of trials and generate confidence in their products. Payers would benefit because they would be less likely to pay for costly, ineffective drugs over an extended period. Most importantly, patients would benefit, because they are more likely to receive effective new drugs, and less likely to receive ineffective and/or harmful ones.

In order to get to this win-win-win scenario, ideally there would be a coordinated, smooth handoff of novel agents from the FDA after accelerated approval to CMS making coverage decisions.

This could be accomplished by standardizing the expectations for generation of evidence after accelerated approval. For example, CMS could use its coverage with evidence development policy to require the generation of observational RWD for all drugs that have undergone accelerated approval.

Accelerated approval is a balancing act between the need for novel drugs for devastating conditions such as Alzheimer’s disease and the FDA’s mandate to protect the public from ineffective drugs. Striking this balance would be easier if accelerated approval automatically led to the generation of high-quality evidence on the efficacy and safety of a drug.

We argue that this can be accomplished by encouraging the adoption of pragmatic RWE. Such a move would enable us to get past the controversy surrounding accelerated approval, and allow us to focus on what really matters: accelerating the development of novel therapies by making it easier to determine if they work.

However, until we make it more feasible for this kind of data to be easily generated at the point of care, these innovative approaches will be hamstrung.

Ali Abbasi is a general surgery resident at the University of California San Francisco. Sean Tunis is a principal at Rubix Health and served as CMO at CMS in 2000-05. Laura Esserman is the Alfred A. de Lorimier endowed chair in general surgery at UCSF and directs the university’s breast care center. 

Signed commentaries do not necessarily reflect the views of BioCentury.