It’s a scenario every Emerging Biopharma (EBP) leader hopes to avoid: Six months after launch, results don’t match expectations. Abandonment rates are higher than projected, and patient persistence is inconsistent. Launch challenges persist due to access barriers, hypercompetition, and the overall cost of promotion. The situation leaves management wondering about the causes. Is it the result of policy dynamics, payer tactics, patient affordability concerns, provider hesitation, or some combination of these factors? By the time routine reports become available, it may be too late for course correction. And for EBPs with limited budgets and small teams, such uncertainty is both frustrating and costly. Leaders need data-driven insights to clarify where patients are dropping off, why abandonment is happening, and what to do about it much sooner than ever before.

The case for a multi-analog approach

When any company is first to market with a rare-disease or first-in-class therapy, there’s no established playbook to follow. Traditional benchmarking doesn’t work when there are no comparable products. A better approach is to use data to identify multiple analogs with similar launch profiles, even if they are from different therapeutic areas. Organizations can rely on each analog to help address a specific strategic question.

For example, one might inform pricing strategy and copay program design, while another reveals adherence and persistence support needs. A third analog can provide insights on distribution channel considerations, and a fourth may show whether patients need high-touch concierge support versus digital-first engagement.

This is just one example of how data can be used strategically to strike the right balance between supporting patients and managing budgets.

Make limited data go further

When designing and delivering patient support, first to market and first-in-class brands need to maximize the value of every available data point. Without years of proprietary data, the ability to de-identify and link patient support program data with broader healthcare datasets becomes critical.

By integrating patient support program information—such as enrollment patterns, benefits verification outcomes, and adherence trends—with IQVIA’s Longitudinal Access and Adherence Data (LAAD) from the broader market, customers gain the ability to benchmark their performance against market trends. This is particularly advantageous for organizations that may not have a deep historical dataset for their own therapy, as it opens up new opportunities to understand their market position and make data-driven decisions.

Additionally, incorporating lab data can help identify undiagnosed patient populations that could benefit from a specific therapy, expanding the reach and impact of patient support initiatives. It’s also valuable to layer in ancillary data points related to social determinants of health, which provide critical insights into transportation barriers, income challenges, access to care, and other external factors. These elements significantly influence whether patients are able to start and remain on therapy, and understanding them can guide more effective interventions. By connecting these varied data sources, the potential to optimize outcomes and drive meaningful value for both patients and organizations is greatly enhanced.

IQVIA took this multi-source approach to help a company focused on a rare eye disease to drive awareness and patient identification. They used lab data to quantify how many undiagnosed patients existed in their target geography. Then they partnered with digital marketing experts to create targeted outreach across TV, social media, and print channels, tailoring each message to reach specific patient segments.

By strategically connecting the dots across different data sources, organizations can access enterprise-level data capabilities without enterprise-level budgets and focus their limited resources where they’ll have the most impact.

Three ways to use data to support better outcomes

When every dollar and decision matters, smaller organizations can tap into data-driven insights to guide patient support investments in three ways.

1. Predict and intervene: Invest where it counts.

   Should an organization invest more in access support, affordability programs, or ongoing adherence initiatives? Guessing incorrectly can lead to costly mistakes. Fortunately, data can reveal exactly where patients drop off in their journey and predict which patients are at highest risk for discontinuation.

   Armed with these insights, organizations can deploy targeted interventions (e.g., nurse outreach, digital nudges, or financial assistance) at precisely the right moment for each patient. Data also helps reveal when payer tactics such as accumulators or maximizers threaten therapy persistence, enabling a proactive response.

   By basing decisions on evidence rather than assumption, an organization can invest where it matters most for a specific patient population - through optimized value.

2. Inform program design: Right-size support that works.

   Every organization is challenged to design programs that effectively support patients while working within budget constraints. Once programs are running, the challenge shifts to monitoring and measuring what’s working (and what isn’t). Data helps to identify undiagnosed patients who need the therapy, target and educate the prescribers most likely to adopt the product, and assess program effectiveness by patient segment. When certain strategies prove underutilized, resources can be reallocated to higher-impact interventions. Data also helps determine the optimal support model (i.e., high-touch concierge service, digital-first engagement, or a hybrid approach) based on actual patient needs and preferences.

   IQVIA data analysis revealed to one ultra-rare disease manufacturer that they were significantly underfunding support for patients on accumulator plans. Although the company had concerns about overspending in this area, their accumulator impact was actually quite small, and patients on these plans were discontinuing therapy at high rates. The data-driven insight suggested a counterintuitive solution: increase funding for accumulator patients to prevent discontinuation.

   Data-driven insights support continuously optimized programs that do more with less through strategic refinement at the appropriate time in order to have a positive impact on patients.

3. Demonstrate value: Prove what’s working.

   With limited budgets under constant scrutiny from investors and board members, EBPs need to prove that patient support programs are delivering results. Data makes it possible to track key metrics like fill rates and time on therapy. With clear KPIs that demonstrate program effectiveness, stakeholders can see the correlation between patient support and commercial success, and management can create compelling business cases for continued or expanded investment.

   With transparent evidence of program effectiveness, management gains confidence to invest in what’s proven to work rather than defending every line item.

Getting governance right

While these data strategies offer significant advantages, they must be implemented within appropriate guardrails and customer governance policies. Indeed, being comparatively small doesn’t exempt an organization from data governance requirements. Without dedicated compliance teams, it can be easy to make mistakes, such as wanting to use patient support program data for purposes not covered by consent or not understanding what data can be shared and under what conditions.

By working with an experienced partner, an EBP gains access to coaching on regulatory considerations, including appropriate data usage, consent requirements, and what it takes to set up compliant data stores. Getting governance right from the start protects patients and the company while enabling insight generation over time.

Strategic focus matters more than budget size

In today’s competitive landscape, organizations that leverage their data to make strategic decisions are able to stretch every dollar further, confidently demonstrating value to both stakeholders and investors. This not only helps build sustainable programs, but also ensures that each investment is purposeful and impactful.

More and more, organizations are opting for partners who can provide integrated capabilities—bringing together data, analytics, and services under one roof. By working with teams like IQVIA, companies benefit from simplified vendor management, streamlined costs, and a solid foundation for long-term success.

The future belongs to organizations that use data not just to launch therapies, but to see patients’ needs through the patient lens by supporting them with intelligent, personalized, and financially sustainable support programs.