How small and emerging biopharma can generate real-world evidence

Getting a drug to market requires robust evidence and planning, no matter your company’s size. And many companies struggle with the same roadblocks, regardless of their market footprint or therapeutic area.

But small and emerging biopharma organizations have additional incentive to get ahead of things. Your organization has the same jobs to get done as larger companies throughout the product lifecycle. Still, there’s a different level of pressure to compete and differentiate your product, often with limited resources.

There are several steps you can take to generate evidence that your stakeholders — the U.S. Food and Drug Administration (FDA), payers, healthcare providers, consumers and policymakers — will need to support their decision making. To demonstrate the clinical, economic and societal value of your product, various health economics and outcomes research (HEOR) studies can help you address your toughest research questions.

What can you understand in existing data right now, and what will you need to understand in the future? Here, we outline 5 specific questions to answer with real-world data (RWD), depending on where you are in your research process.

Aligning each question to the right data sources and study design will lay the groundwork as you approach your phase II and phase III read outs, market approval and other big milestones. And ideally, the resulting outcomes of your research should strengthen your overall product value story.

1. Disease burden: How are patients affected?

Disease burden studies can help you explore how patients are affected by estimating disease incidence and prevalence, describing the typical diagnostic journey including current treatments and management pathways, and evaluating the healthcare and economic burdens associated with the condition.

It can be helpful to quantify these features in RWD because you need an accurate assessment of who is out there, today, living with the condition under study and the resulting economic strain on both patients and the healthcare system writ large. These assessments will also help you define the potentially eligible patient population for your drug in development and inform pre-clinical planning.

2. Unmet need: What gaps in care can your product address?

Capturing unmet need allows you to demonstrate the current gaps in care that your product may address. You’ll want to investigate:

• What other treatments are currently on the market? How effective are they?
• What’s the side effect profile of existing treatments?
• What are the dosing schedules and administration routes — and any related challenges — for existing treatments?

Another important aspect is medication adherence: Are patients taking their medications correctly? Even if patients are adhering to currently available treatments, it doesn’t mean they’re working.

Consider how many patients still have active symptoms and/or poor health outcomes, despite being on therapy. And payers will want to know more about that connection specifically — if adherence produces better outcomes.

These early analyses can identify the key areas where your product could make a significant difference.

Plus, with the rising popularity of value-based arrangements, you’ll want to determine the measurable outcomes that can justify such agreements when you get to those conversations. Based on evidence such as unmet needs, various consulting exercises can be conducted to project outcomes expected in the real-world setting, the anticipated level of clinical effectiveness and the areas where stakeholders might be comfortable taking risks.

3. Comparative effectiveness: Outcomes compared to your competitors?

You’ll want to know how the outcomes of your product stack up against those of your competitors and the current standard of care. By comparing the treatment costs of your product with those of competitors' products, you can identify any economic advantages your drug offers. This information may be crucial for contracting with commercial payers or negotiating prices with the Centers for Medicare & Medicaid Services (CMS).

Head-to-head comparisons can provide valuable insight into the direct effectiveness of competing therapies. But it's important to note that this approach carries risks, as it may not always yield the desired answers. Unless you’re operating off a strong hypothesis that your treatment is superior to others on the market — or required to produce such a comparison for regulatory purposes — other research studies may be more effective.

4. Health economic modeling: What are the budget impacts?

Discussions about health economic modeling should occur before starting your phase III clinical trial, often during phase II. You’ll want to point your phase III trial in the right direction while limiting research to cost-efficient studies, since you don’t know the outcome of your clinical trial just yet. That doesn’t mean you can’t start translating your product’s clinical benefits into tangible and measurable economic outputs.

Modelling exercises — built upon literature review findings or evidence generated by the trials to date — are crucial analytical tools to project the financial implications of introducing a new treatment into the market.

Budget impact modeling can help you identify the cost of treating patients with the condition now versus the anticipated cost when your treatment is available for broader use. These studies can estimate changes in healthcare spending and the treatment’s expected value. These models can always be updated with real-world data once your product is available on the market, enhancing their accuracy and relevance for payers as they make coverage and formulary decisions.

Investing in understanding the payer perspective early on will ultimately help increase patient access down the line.

5. Label expansion: How can RWD support new indications?

Maybe your product is already on the market, but you’re seeking approval for a new indication. Before even approaching the FDA, you need to understand the landscape of how the drug is used in real-world clinical context.

Incorporating real-world data into your label expansion efforts enables your team to see who is using the product off label, the outcomes among the off-label users and all indications the product is being prescribed for in the real-world clinical setting.

You’ll want concrete evidence of how your product works in the clinically indicated population relative to the entire population being treated with your therapy. This involves analyzing the medication’s effectiveness and safety in those who are prescribed it for the approved indication compared to those using it for other purposes.

Such insights can provide valuable information on the drug's broader implications and strengthen your case to the FDA for the product’s potential benefits and applications.

Here are 2 examples of real-world evidence studies that demonstrate how small and emerging companies can generate actionable evidence across therapeutic areas.

1. Assess outcomes and utilization to support clinical development

In one study, a biotechnology company developing a treatment for necrotizing soft tissue infections (NSTIs) partnered with Optum researchers to study post-surgical patients with NSTIs. The purpose of the study was to measure the burden of illness associated with NSTI, including economic outcomes that were not available in existing research.

The researchers conducted an analysis combining claims data, medical chart abstraction, National Death Index data and details from the company’s ongoing trial to determine the association between persistent organ dysfunction and longer-term patient outcomes.

The pooled analysis concluded that patients with NSTI and persistent organ dysfunction at 2 weeks after initial NSTI diagnosis had higher resource utilization, worse discharge outcomes and higher mortality within the following 3 months.

These results support measurement of organ dysfunction as a key target in developing therapies to improve the health of NSTI patients. This study added to their overall product narrative, enhancing their results from the clinical trial with real-world information.

2. Characterize clinical and financial burden of illness

In another example, Optum researchers partnered with a biopharmaceutical company to characterize the patient journey for those with dementia-related psychosis (DRP). To better understand unmet needs and inform their research in this therapeutic area, they compared real-world clinical events, healthcare resource utilization and healthcare costs among dementia patients with and without DRP.

The researchers analyzed a retrospective claims data set and found that a higher percentage of patients with DRP had been diagnosed with depression, anxiety and insomnia in the period prior to their DRP diagnosis, compared to patients with a dementia-only diagnosis. And post DRP-diagnosis, patients were more likely to experience clinical events including falls, neurologic effects, sedation and cardiovascular effects. They also had higher rates of outpatient visits, emergency visits, inpatient stays and faced significantly higher care costs.

The study results support the need for treatment options to reduce the clinical and economic burden faced by patients with DRP and suggest potential inputs for future work to identify patients at risk for DRP earlier.

This information may also help the company better understand the patient story and demonstrate value to payers beyond direct treatment costs. For example, the potential downstream economic results of improved outcomes among patients with DRP (such as fewer hospital visits and lower overall health care costs).

As small and emerging biopharma organizations grow their market share and footprint in the industry, it’s crucial to take steps to better understand the patient story, learn the therapeutic landscape and differentiate products in the market.

Defining product development milestones and identifying the evidence you’ll need to generate for each will help your organization move towards a more seamless launch. For example, outline payer story needs as you approach phase II and develop a deeper understanding of the competitive treatment landscape as you advance to phase III.

Whether that involves getting your hands on data and conducting studies in-house or partnering with our seasoned Optum® Life Sciences Value and Evidence Solutions team, you’ll get the insights necessary for any stage of your product’s lifecycle. No matter what route you take, there’s tremendous value to making your company a forward thinking, real-world data-powered organization.