Why the shift towards real-world evidence will accelerate

Key takeaways:

Introduction

It’s no secret that the timelines in biopharma can be long. While the pace of biological discoveries doesn’t seem to slow down, every (deeply scarred) researcher, operator and investor will tell you that most research can’t be replicated, preclinical success rarely translates to the clinic and late-stage trials have been the decisive blow for many once hopeful biotechs. Yet, for all our healthy skepticism, sometimes novel discoveries from a long time ago and a galaxy far, far away really do translate into breakthrough medicines for patients, as we have begun to see with cell and gene therapies, for example.

If the previous century was one in which wealthy nations conquered many once fatal infections and diseases that plagued large portions of the world, the current will be defined by our ability to increasingly push the standard of care for rare disease, oncology, CNS and autoimmune disorders. One need only look at the list of the top selling drugs over the past decade to see a host of biologic drugs – a trend that will accelerate in the coming decades as IRA legislation caps the NPV on small molecules and novel modalities such as cell and gene therapy, immunotherapies and next-gen antibodies begin to hit the market in droves.

While biologics are an umbrella term for many different modalities, they are generally costlier, require in-patient dosing and are potentially bespoke to individual patients. As drug development continues to skew that way, a lot of these drugs will be hitting the healthcare system and payors, providers and patients will increasingly demand more tailored evidence beyond the clinical trials to justify the cost and inconvenience. To make that case, biopharma companies will need to increasingly rely on real-world evidence (RWE), or clinical evidence derived from actual patient usage and outcomes (also known as real-world data (RWD)) outside the clinical trial setting.

Figure 1: Glossary of terms

TermDefinition
RWE (real-world evidence)The clinical evidence outlining usage, benefits and risks of a treatment based on analysis of RWD
RWD (real-world data)Data relating to patient health or delivery of healthcare that is collected from various sources
RCT (randomized controlled trial)Impact evaluation of random eligible population sample comparing intervention vs. control
Patient registrySystem with data (clinical and other) used to evaluate outcomes for patient populations defined by a disease or exposure to a treatment

Real-world data can be derived from multiple sources, including insurance claims, electronic health records (EHRs), disease registries, wearable devices or even Google searches. It has applications across healthcare, but for this post I will focus on applications relevant for biopharma companies, such as clinical and post-approval studies, indication & modality focus and market access. RWE is not a new concept, but has become more relevant due to recent market dynamics that are covered below.

Importantly, RWE will not replace clinical trials, which should remain the gold standard for assessing the efficacy and safety of a drug. Instead, it should help inform appropriate utilization of approved medicines. After all, it makes sense to continue to track efficacy and side effects once medicines are rolled out to the broader population, as new signals will surely emerge with the larger patient pool than were uncovered in the clinical trial.

So how does real-world evidence typically function for biopharma companies? A drug addressing a high unmet need will receive contingent reimbursement (or approval, in some cases) on the basis that data will be collected from actual patients that take the drug, reflecting a diverse population beyond those included in the clinical trial parameters. Ongoing feedback (efficacy, safety, complications) from these patients and their providers will paint a picture as to how effective the drug actually is, and if that effectiveness differs within the population. This difference can be clinical (i.e. patients with comorbidities had lower efficacy than those without) or molecular (i.e. patients that highly expressed Gene “X” tended to be non-responders) depending on the mechanism through which the RWD is collected. The results, as discussed below, are noteworthy for payors, providers and patients.

Rationale behind the shift to RWE

Evolving modality and disease focus for novel drugs

As noted above, biopharma companies are increasingly focused on deploying novel modalities to address unmet needs within rare disease, oncology, CNS and autoimmune disorders. On the indication side, this may result in the traditional clinical trial structure (a large, heterogenous pivotal trial) being unusable, since patient population sizes are small and it is considered unethical to give placebo to patients with no other options. These drugs are often fast-tracked via separate regulatory pathways that allow single-arm trials to form the basis of approval (although this is evolving), with the understanding that post-marketing studies (i.e. confirmatory Phase 3 trials) will verify efficacy and safety. As a greater proportion of efficacy and safety data generation shifts to the post-marketing setting, RWE will increasingly be used to meet FDA requirements.

The first-mover advantage can be profound, as it is difficult to convince patients to enroll in subsequent clinical trials for competitor drugs when there is a FDA approved medicine on the market (why risk getting a placebo when you can get the real thing?). As enrollment rates slow and the ability to generate head-to-head (H2H) data is compromised, real-world evidence offers a critical mechanism to verify the drug actually works long-term, in a broad set of actual patients.

Separately, the emergence of curative modalities such as cell and gene therapy require different ways to measure outcomes and ensure that these drugs really do provide the cure they claim via long-term follow-up data. Clinical trials may only measure patient follow-up for a few years, but when a drug costs almost $3M(1) payors are going to demand to see long-term data to verify the steep value proposition.

  1. ~$2.8M = gross price, not inclusive of gross-to-net adjustments, and thus not reflective of what a company actually makes

Figure 2: Highest priced drugs concentrated recently

DrugWAC PriceFDA Approval Date
Roctavian$2-3MPDUFA: March 2023
Skysona$3MSeptember 2022
Zynteglo$2.8MAugust 2022
Zolgensma$2.1MMay 2019

Payor pushback

The shift towards higher priced biologic drugs in niche indications has naturally resulted in payor pushback, as they would ultimately foot the bill. With drug prices setting new records, payors want to ensure that they are getting appropriate value. One common concern is that the profile of patients in the regulatory evidence base (i.e. clinical trials) does not match the much more diverse population that a large payor oversees. In other words, the FDA label is too broad for the individual patients considering the drug. As a result, there is limited to no evidence the drug “works” in these other patient populations. For example, if the clinical trial parameters only included patients up to age 40 with no comorbidities, then what is the evidence the drug works in a 60-year old patient with heart problems, even if they have the same disease the drug is indicated to treat? Small trial sizes, accelerated approvals and massive price tags all converge, and payors respond by demanding real-world evidence the drug works. But how can a biopharma company collect and provide that evidence if the payor doesn’t let patients take the drug? That is where value-based agreements come into play, which we’ll discuss in the next section.

Expansion in measurable data outside the clinical setting

The world is more interconnected than ever, and this has allowed for a number of new ways data can be collected on the effectiveness of a drug. Whether through mobile devices, patient registries or personalized health networks, all stakeholders can get a better sense of how patients are responding, and if that varies in an identifiable way across the population. As healthcare becomes more digitized, it is inevitable that there will be meaningful spillover to the collection and utilization of real-world data in the context of drug development and evaluation.

Figure 3: Types of real-world data

Summary of the different types of real-world data (application of real-world evidence), with icons for each (10 categories total)

  Icon source

Implications of this shift

More value-based agreements with payors

Value-based agreements are the mechanism through which biopharma companies secure patient access to their drug so that they can develop the required RWE to prove long-term efficacy and safety across a broader population. While terms will vary from deal to deal, generally the payor covers the cost of the drug upfront, but receives a partial or full refund from the manufacturer if the drug does not work as intended. The devil is in the details with these agreements, as quantifying desired clinical outcomes and finding agreeable value metrics between payors and manufacturers is often a difficult negotiation. Regardless, these agreements should become more frequent moving forward, particularly for clearly defined patient populations and clinical endpoints, where long-term follow-up is needed to determine efficacy.

✔ Good example: hepatitis C therapies – unambiguous diagnosis & clinical endpoints

X  Bad example: pain therapies – difficult to measure outcomes objectively

An ongoing example of a value-based agreement is BioMarin’s Roctavian for severe hemophilia A which was approved in the EU and has a PDUFA date of March 2023. U.S. pricing is expected to be ~$2-3M gross, or ~$2M net. While that number is astronomical, annual patient costs for recurring prophylactic FVIII therapies such as Hemlibra are >$700K, suggesting ~4 years of curative treatment benefit would save payors money. This doesn’t factor in quality of life benefits given FVIII infusion burden is needed anywhere from 1-4x a week, severely limiting patients’ freedom to travel.

In this case, BioMarin is offering a full refund if patients do not respond to Roctavian and a partial refund if the response is lower than a pre-specified duration. For example, if the agreed upon minimum duration was 5 years, and a patient only responded for 4 years, then BioMarin would refund ~20% of the total cost to the payor. Interestingly, BioMarin might benefit from a longer pre-specified duration, as the upfront cost can then be framed against the total cost of standard of care for the same period. For example, a 10-year duration means Roctavian is cost-effective against 10x the annual FVII prophylaxis, or >$7M, which could encourage broader patient utilization. Ideally, the benefit from dosing more patients would offset the increased number of patients who don’t respond.

There are several logistical issues with value-based agreements and medicines that require long-term follow-up:

Figure 4: Concerns associated with value-based agreements & potential solutions

ConcernProposed Solution
On average, patients change private insurance every ~3 years and Medicaid every ~6 years, so a payor might not reap the downstream benefits of the massive payment they madeSince this is an industry-wide dynamic, if every payor committed to covering these treatments, then they would benefit from patients who had it paid for elsewhere and are now switching to them at the same rate the inverse is happening
Long-term follow-up of patients that move around the healthcare system (i.e. switch payors, providers, etc.) is difficult and raises questions around pro rata reimbursementThe shift towards value-based care and digitization of healthcare broadly should support patient tracking and communication between multiple insurers and providers
If a patient doesn’t respond to an expensive cell or gene therapy, will they have issues returning back to their previous medicine?Patients should not be punished for trying curative therapies, and payors should avoid putting up roadblocks, especially if they are refunded for the cost of treatment
The size of these payments could strain the budgets of smaller, regional payors if not accurately forecastedManufacturers should structure value-based agreements with smaller payors that do not require them to pay the entire amount upfront
Expensive, curative therapies will often be stage-gated such that patients must step-through cheaper medicines to see if that adequately controls diseaseThere is usually a spectrum of disease (mild to severe) and it is not unreasonable to reserve these drugs for severe patients with no other options; most patients are not eager to try experimental drugs anyways
Payors operate on a 12-month cycle, and thus a shift to a multi-year perspective may be difficultPayors must adapt their business models to changing times. There are encouraging signs, such as Atena’s designated GCIT network

Better realization of precision medicine

Real-world evidence supports the industry’s transition to precision medicine, as providers can use this data to answer specific questions about a drug that is tailored to their patient’s profile. For example, providers could get a report of hundreds, if not thousands of people that look just like the patient they’re treating from a clinical or molecular perspective. By understanding prior treatments of these other patients, their molecular / clinical makeup and the efficacy / safety breakdown, providers can make far more informed decisions about the utility of a drug for their own patients. Interestingly, this was the stated ambition of Tempus by founder Eric Lefkofsky, who recalled asking his wife’s physician “How many other people are like my wife?” and being told that no one could provide that level of detail.

Accelerates value-based care transition

The infrastructure needed to support the timely acquisition of real-world evidence plays into the larger transition towards value-based care. VBC encourages payment based on outcomes rather than volume, but in order for providers to accept this risk-based model, they need to have a deep understanding of the care their patient populations need. To get that understanding, providers need a few things, all of which are accelerated by manufacturers and payors desire to effectively implement real-world evidence:

Essentially, these components will be implemented much faster as two macro trends are converging on them: the shift towards real-world evidence and the shift towards value-based care.

Concluding thoughts

While a clinical trial is still the gold standard for proving the cause and effect of a drug, the evolving treatment and regulatory landscape calls for a more nuanced way to differentiate between individual patient management and population health management. For the latter, we need to be able to draw broad strokes to determine care in a cost-effective manner. Real-world evidence offers a mechanism to ensure patients with unmet need get access to life-changing drugs, while putting up reasonable constraints around who receives these therapies and how payment should be structured. Broader trends to digitize and modernize healthcare care delivery and continued collaboration between industry and regulatory agencies should support the utilization of real-world evidence, with the patient being the biggest beneficiary.