Disease Modeling as a Strategic Driver for Market Access

Key Takeaways

• Disease modeling is a strategic HEOR tool that helps quantify disease burden, assess treatment value, and inform market access decisions.
  Integrated evidence generation strengthens value demonstration by connecting clinical trials, real-world evidence, patient-reported outcomes, and economic modeling.
• Market access depends on real-world implementation. Combining disease modeling with implementation science helps translate evidence into clinical adoption and patient access.
• Rare diseases and gene therapies require advanced modeling approaches to project long-term outcomes, assess societal impact, and inform reimbursement decisions.
• Strategic use of disease modeling across the product life cycle supports value communication, enabling life sciences companies to align evidence generation with the needs of patients, payers, clinicians, and policies.

Table of Contents

1. The Strategic Role of Disease Modeling in Market Access
2. Turning evidence into real-world impact
3. Disease modeling for rare diseases and gene therapies
4. Case study: Modeling the value of gene therapy for sickle cell disease
5. Advancing value demonstration through disease modeling

Health economics and outcomes research (HEOR) is increasingly central to the challenges facing the pharmaceutical and biotechnology industry.

Organizations developing new therapies must navigate several competing demands:

• Advancing innovative technologies that address unmet medical needs
• Demonstrating clinical value while maintaining affordability for healthcare systems
• Generating robust clinical evidence and anticipating real-world outcomes
• Improving patient outcomes and advancing the overall population’s health

Although these tensions are not new, the environment in which they must be managed has evolved rapidly. Advances in precision medicine, cell and gene therapies, artificial intelligence, and large-scale health data are transforming how therapies are developed and evaluated. At the same time, evolving payer expectations and policy environments are reshaping how treatments are assessed and made accessible to patients.

In this context, disease modeling plays a critical role in informing market access and evidence strategy. When applied early and used throughout product development, disease modeling helps life sciences companies understand disease burden, communicate value to stakeholders, and guide evidence strategies for real-world use.

At RTI Health Solutions, we partner with clients to unlock the strategic potential of disease and economic modeling across the product life cycle, integrating modeling with real-world evidence, stakeholder engagement, and implementation science to support sustainable patient access.

The strategic role of disease modeling in market access

Disease modeling is a core HEOR methodology that uses decision-analytic and simulation approaches to characterize disease progression, treatment pathways, and health and economic outcomes over time. By integrating evidence from clinical trials, real-world data, and epidemiological studies, disease models enable researchers and healthcare decision-makers to evaluate questions that clinical trials alone cannot fully address.

These questions often address the burden of disease, the projected impact of therapies on patient outcomes over time, and the broader costs and savings associated with treatment adoption across healthcare systems.

Because market access decisions frequently depend on understanding these longer-term, system-level effects, disease modeling has become a critical tool for informing access strategies. Although commonly associated with cost-effectiveness analysis, the strategic value of disease modeling extends far beyond reimbursement submissions.

When applied early in development, disease modeling can help life sciences organizations:

• identify evidence gaps that may influence payer and health technology assessment (HTA) decision-making
• prioritize evidence generation and research investments
• quantify the long-term clinical and economic value of new therapies
• support value communication with payers and policymakers
• inform pricing and reimbursement strategy

In this way, disease modeling provides a structured framework for aligning evidence generation, value demonstration, and market access strategy across the product life cycle.

Turning evidence into real-world impact

Clinical trials remain the foundation of therapeutic evidence, but healthcare decision-makers increasingly require insights that reflect anticipated real-world use.

Disease modeling enables organizations to integrate multiple evidence sources to evaluate the potential impact of new therapies across healthcare systems. These evidence sources include clinical trials, real-world data, patient-reported outcomes, and observational studies.

These models help organizations:

• project long-term clinical and economic impact
• assess population-level benefits and healthcare resource use
• evaluate uncertainty and alternative scenarios
• inform payer strategy and value communication

Implementation science extends this work by identifying the behavioral, clinical, and system-level factors that influence whether evidence-based therapies are adopted in practice. Understanding these dynamics allows organizations to anticipate barriers to adoption and design strategies that support effective implementation.

Together, these approaches connect evidence generation with real-world adoption, helping organizations maximize patient access and real-world therapeutic impact.

Disease modeling for rare diseases and gene therapies

Evidence generation presents unique challenges for rare diseases and novel advanced treatments, such as cell and gene therapies.

Small patient populations limited natural history data and uncertainty about long-term outcomes can make it difficult for developers to demonstrate value using traditional research approaches. As a result, payers and HTA bodies often require additional evidence to evaluate the long-term clinical and economic impact of these therapies.

Disease modeling provides a structured approach to address these challenges by enabling researchers to:

• characterize the clinical and economic burden of rare diseases
• extrapolate outcomes beyond limited clinical trial data
• assess health system and societal effects, including productivity and caregiver burden

These analyses are increasingly important for informing reimbursement decisions and innovative payment models for high-cost therapies.

Case study: Modeling the value of gene therapy for sickle cell disease

A recent collaboration supporting the development of a potentially curative gene therapy for sickle cell disease (SCD) illustrates the strategic value of disease modeling.

Early disease and economic modeling helped align the development team around key value drivers and evidence gaps, including the need to better understand the complex relationships between SCD complications and the broader clinical and economic burden of severe disease.

These insights informed the development of an integrated evidence plan that included:

• literature reviews examining SCD-related complications, risk factors, and disease progression across the lifespan
• real-world claims analysis on disease burden in patients with severe SCD who are likely to be candidates for gene therapy
• a study examining the spillover effects of SCD on educational outcomes and productivity
• analyses of patient-reported outcome data collected in clinical trials
• development of a comprehensive disease and economic model to estimate the long-term health and economic impact of SCD gene therapy

Throughout the collaboration, our scientists worked with patients, clinicians, key opinion leaders in SCD, and academic research organizations to build a clinically grounded and patient-relevant framework for assessing the effect of curative gene therapy on the risks of complications of SCD.

This integrated approach generated evidence to inform decision-making across the healthcare system—from patients and clinicians evaluating treatment options to payers and policymakers assessing reimbursement and financing strategies.

A complete case study on this effort is available here.

Advancing value demonstration through disease modeling

As therapeutic innovation accelerates, demonstrating the value of new therapies requires more than clinical trial evidence alone.

Disease modeling helps quantify disease burden, project long-term outcomes, and support market access decisions. When integrated with real-world evidence, evidence generation planning, and implementation science, disease modeling strengthens value demonstration and helps address payer and policy expectations.

Across the product life cycle, strategic disease modeling helps organizations evaluate therapeutic impact, address evidence gaps, and support value-based decision-making.

RTI Health Solutions partners with life sciences companies to apply disease modeling in support of product development, evidence strategy, and market access. To learn more, contact our team using the form below.