Developing treatments for the approximately 7,000 known rare diseases, particularly the subset classified as ultra-rare, presents profound and often insurmountable challenges for traditional pharmaceutical development paradigms. These conditions, affecting patient populations ranging from fewer than 10 to a maximum of 1,000 individuals globally, render the gold standard of randomized clinical trials (RCTs) not only impractical but frequently unethical. The inherent scarcity of patients necessitates a fundamental re-evaluation of how efficacy and safety evidence is generated, demanding innovative and flexible approaches that uphold scientific rigor while acknowledging the unique constraints of these minuscule patient cohorts.
The U.S. Food and Drug Administration (FDA) has, in recent years, demonstrated increasing awareness of these realities, signaling a crucial shift towards embracing alternative evidentiary strategies. This evolving regulatory landscape is epitomized by two interconnected initiatives: the Rare Disease Evidence Principles (RDEP) process and the FDA’s recent draft guidance on the plausible mechanism framework for individualized therapies. These developments underscore a commitment to fostering innovation in evidence generation, particularly for contexts where conventional trial designs are simply not viable.
The Unprecedented Challenge of Ultra-Rare Diseases
Ultra-rare diseases (URDs), often genetic in origin, impose a devastating burden on affected individuals and their families. Patients frequently endure a prolonged "diagnostic odyssey," sometimes spanning years, before receiving an accurate diagnosis. Even then, the vast majority of URDs lack any approved treatment options, leaving patients with limited or no therapeutic recourse. The sheer rarity of these conditions creates a vicious cycle: limited patient numbers deter research and development due to the high costs and perceived low return on investment, perpetuating the lack of available therapies.
Traditional RCTs, designed for larger populations, rely on statistical power derived from hundreds or thousands of participants to detect significant treatment effects and minimize bias. For URDs, recruiting even a handful of eligible patients globally can be an arduous task, often requiring international collaboration and extensive travel. Furthermore, the ethical implications of withholding potentially life-saving treatment from patients in a placebo arm, when so few individuals are affected and often suffer from rapidly progressive conditions, are profound. The logistical and ethical barriers effectively halt the progress of promising therapies before they can even begin to demonstrate their potential. This stark reality has long necessitated a re-evaluation of the "substantial evidence" standard, which traditionally required reports from at least two adequate and well-controlled investigations. However, regulatory frameworks have historically allowed for flexibility, permitting a single pivotal trial supplemented by confirmatory evidence in appropriate circumstances, particularly in oncology and rare diseases where urgency and population size dictate adaptability.
A Paradigm Shift in Regulatory Thinking: FDA’s Evolving Stance
The FDA’s journey towards greater flexibility in rare disease drug development is not a sudden one but rather an evolution shaped by decades of experience and advocacy. The Orphan Drug Act of 1983 was a landmark piece of legislation that provided incentives such as market exclusivity and tax credits to spur the development of treatments for conditions affecting fewer than 200,000 people in the U.S. While highly successful in increasing the number of approved orphan drugs, the Act primarily addressed rare diseases, not the distinct challenges posed by ultra-rare diseases.
Over time, as scientific understanding of genetic diseases advanced and patient advocacy grew, the FDA recognized the need for even greater adaptability. This evolution is reflected in various guidance documents and the agency’s willingness to approve therapies based on innovative trial designs. The introduction of RDEP and the plausible mechanism framework represents a formalization and expansion of this longstanding, risk-based regulatory flexibility within existing regulations. These initiatives acknowledge that while the need for scientific rigor remains paramount, the means of demonstrating substantial evidence of effectiveness must adapt to the unique circumstances of ultra-rare populations.
Introducing the Rare Disease Evidence Principles (RDEP) Process
The FDA introduced the Rare Disease Evidence Principles (RDEP) process specifically to enhance clarity and predictability for sponsors navigating the complex landscape of ultra-rare disease therapy development. It serves as a crucial mechanism for early, focused dialogue between drug developers and regulators regarding evidentiary strategy, thereby formalizing principles previously articulated in various FDA guidances and prior approvals.
The RDEP process is meticulously designed for development programs that satisfy stringent criteria, primarily focusing on diseases with extremely limited patient populations. While the exact criteria were not fully detailed in the original article, common understandings suggest it applies to conditions with a global prevalence often well below the 1,000-patient threshold. The process is distinct from other FDA engagement mechanisms, such as end-of-Phase II or pre-new drug application (NDA)/biologics license application (BLA) meetings, and is not intended to expedite approval timelines. Its true value lies in establishing early alignment on what constitutes acceptable evidence when conventional development approaches are inherently insufficient.
Central to RDEP is the affirmation that substantial evidence for ultra-rare disease therapies can be based on a single adequate and well-controlled clinical investigation, provided it is accompanied by appropriate confirmatory evidence. This approach, building on the FDA’s 2023 guidance recognizing that one trial plus confirmatory data may meet statutory standards, offers a pragmatic pathway forward. Studies conducted under RDEP must still ensure reliable outcome assessment, minimize bias, and be capable of supporting causal inference. Crucially, these do not necessarily need to be RCTs; single-arm trials can be acceptable when rigorously paired with high-quality external controls, such as well-characterized natural history cohorts or other relevant real-world data (RWD) sources. This flexibility is vital for de-risking development decisions and can indirectly contribute to accelerating the availability of therapies for these critical unmet needs.
The Plausible Mechanism Framework: A Scientific Compass for Novel Therapies
Complementing the RDEP process, the FDA’s draft guidance on the plausible mechanism framework provides a scientific blueprint for how diverse evidence types can coalesce to support drug approval. This framework is particularly relevant for individualized therapies and ultra-rare conditions, describing circumstances where clinical benefit, even if observed in a very small number of patients, can justify approval when underpinned by a scientifically plausible mechanism. This mechanism must convincingly link a therapy’s molecular action to the known biological cause of the disease.
Within this framework, evidentiary packages may include a synergistic combination of clinical data, robust mechanistic evidence, and various contextual data sources. The most compelling packages demonstrate internal consistency across these multiple data streams. This can encompass detailed mechanistic and biomarker data elucidating the drug’s target engagement and pharmacodynamics, relevant nonclinical (animal and in vitro) studies, comprehensive natural history data outlining the untreated disease course, and even data generated through expanded access programs or meticulously documented case series.
The draft guidance significantly addresses the pivotal role of natural history data and external controls, especially when RCTs are not feasible – a scenario common for RDEP-eligible programs. A well-characterized natural history of the disease in untreated patients is a core component, providing essential context for interpreting any observed treatment effects. It establishes the baseline against which therapeutic intervention can be measured, offering crucial insights into disease progression, variability, and relevant endpoints. Similarly, external control arms, meticulously derived from robust registries, observational studies, or other high-quality RWD sources, can support causal inference by providing a comparative group when randomization is impractical. Methodological rigor in selecting and matching external controls is paramount to mitigate bias and ensure the validity of comparisons.
Recent approvals vividly illustrate the practical application of these principles. For instance, the approval of ITVISMA® (onasemnogene abeparvovec-brve) for certain spinal muscular atrophy (SMA) patients exemplifies this integrated approach. The primary evidence from a well-controlled study was powerfully supported by confirmatory evidence related to its mechanism of action and efficacy data derived from another therapy containing the same active ingredient. These combined data sources reinforced the plausibility and consistency of the observed treatment effect, providing the "substantial evidence" required for regulatory approval despite the limited patient numbers.
The Indispensable Role of Real-World Evidence (RWE)
Real-world evidence (RWE), derived from real-world data (RWD) collected outside traditional clinical trials, plays an increasingly critical and multifaceted role within the RDEP review process. Its utility begins even before formal development, assisting sponsors in determining whether a disease meets the ultra-rare prevalence threshold for RDEP eligibility. This is especially valuable for conditions that are historically underdiagnosed, inconsistently coded in health records, or clinically heterogeneous, making precise prevalence estimates challenging.
Once RDEP eligibility is confirmed and a development program is underway, RWE continues to be invaluable throughout the entire review lifecycle:
- Natural History Studies: RWE is crucial for characterizing the natural progression of ultra-rare diseases. Patient registries, electronic health records, and claims data can illuminate the typical course of illness, identify relevant clinical endpoints, and understand disease heterogeneity. This baseline knowledge is fundamental for interpreting treatment effects in small interventional studies.
- External Control Arms: As discussed, RWE can provide robust external control arms for single-arm trials, offering a comparator group when randomized placebo-controlled trials are unfeasible. This requires sophisticated analytical techniques to adjust for potential confounders and ensure comparability between the treated group and the RWD-derived control.
- Endpoint Validation: RWE can help validate clinical endpoints and outcome measures, ensuring they are meaningful to patients and sensitive enough to detect changes in small populations. This might involve assessing the real-world impact of specific symptoms or functional limitations.
- Safety Monitoring: Post-market RWE, gathered through patient registries, adverse event reporting systems, or observational studies, can continue to monitor the long-term safety and effectiveness of approved therapies, particularly for conditions with delayed onset of symptoms or rare adverse events not observable in limited pre-market studies.
- Patient Perspective: RWE can capture the lived experience of patients, including quality-of-life measures, patient-reported outcomes (PROs), and the impact of the disease on daily functioning. This qualitative and quantitative data is vital for demonstrating the clinical meaningfulness of a therapy beyond traditional clinical endpoints.
However, leveraging RWE for ultra-rare diseases also introduces specific challenges. Working with extremely small patient populations necessitates heightened privacy protections and robust data governance to minimize the risk of patient re-identification. Even seemingly anonymized datasets can become vulnerable when demographic and clinical characteristics are unique to a few individuals. Furthermore, the inherent variability in RWD sources—different coding systems, data collection methodologies, and clinical practices across global sites—can lead to inaccurate or inconsistent reporting. The adoption of standardized data models and shared clinical ontologies is therefore crucial. By ensuring consistent definitions for diagnoses, endpoints, and outcomes, aggregated RWD becomes easier to interpret and more reliable for regulatory decision-making, helping to bridge the gap between disparate global data systems.
Strategic Engagement: A Multistakeholder Approach to Success
Despite the increasing flexibility offered by frameworks like RDEP, the success of ultra-rare disease development programs remains heavily reliant on early, continuous, and strategic engagement with all relevant stakeholders.
- Early Regulator Engagement: Prior to initiating a pivotal trial, sponsors should submit an RDEP request under an existing investigational new drug (IND) application, accompanied by a formal meeting request. This proactive dialogue, ideally initiated when early clinical data are available and there is still flexibility to shape study design and evidence strategy, is paramount. Early alignment can clarify whether a program qualifies for RDEP and delineate the specific types and quantity of confirmatory evidence that will be deemed acceptable, helping sponsors avoid costly evidentiary strategies that later prove misaligned with regulatory expectations.
- Payer and Post-Market Needs: Beyond FDA approval, sponsors must anticipate the evidence needs of payers and other post-market stakeholders as early as possible. Payer evidence requirements often extend beyond regulatory efficacy, focusing on real-world effectiveness, cost-effectiveness, long-term outcomes, and comparative value. When pre-approval datasets are inherently small, proactive planning to generate this additional evidence through RWE studies or patient registries becomes even more critical to ensure market access and reimbursement.
- Patient and Advocacy Communities: Engaging with patients and patient advocacy organizations is not merely a courtesy but a strategic imperative. These groups are invaluable resources for understanding the true burden of disease, identifying unmet medical needs, facilitating patient recruitment for studies, and supporting the development of patient-centric endpoints. Their insights can refine evidentiary strategies, ensuring they are grounded in the lived experience of rare disease patients. Moreover, patient advocacy groups play a vital role in clinician education and disease awareness, which is crucial for diagnosis and treatment uptake once a therapy is approved. By leveraging data such as quality-of-life measures, clinical outcome assessments, and patient-reported outcomes, sponsors can ensure their evidentiary strategy meets the expectations of downstream stakeholders while genuinely serving the people who need these ultra-rare disease therapies.
A Complex but Evolving Path Forward
The advent of mechanisms like the RDEP process and the plausible mechanism framework provides greater structure, transparency, and a defined pathway for discussing evidentiary strategies in the challenging landscape of ultra-rare diseases. These initiatives reflect a broader, ongoing evolution in how "substantial evidence of effectiveness" can be demonstrated across drug development, especially when traditional paradigms are not feasible. This evolution is driven by scientific advancements, ethical considerations, and the urgent medical needs of neglected patient populations.
For sponsors operating in the ultra-rare disease space, success will increasingly depend on their ability to adeptly integrate multiple, complementary sources of evidence. This includes carefully designed clinical trial data (even if small), a robust mechanistic rationale, comprehensive natural history studies, and meticulously collected and analyzed real-world evidence. Crucially, this scientific and methodological dexterity must be coupled with close and continuous engagement with regulators, patients, and advocacy communities throughout every stage of development. This collaborative, adaptive, and patient-centered approach is not just a regulatory convenience; it is the essential blueprint for delivering life-changing therapies to those with the greatest unmet medical needs.
References
- Reference 1 (e.g., specific FDA guidance on RDEP)
- Reference 2 (e.g., FDA draft guidance on plausible mechanism framework)
- Reference 3 (e.g., legal requirement for substantial evidence)
- Reference 4 (e.g., FDA guidance on one trial + confirmatory evidence)
- Reference 5 (e.g., further details on natural history data’s role)
- Reference 6 (e.g., ITVISMA® approval documentation)
Julien Heidt is Associate Director, Scientific Strategy, Applied AI Science, AI & Technology Solutions at IQVIA. Heidt is an epidemiologist with IQVIA responsible for leading scientific strategy for applied AI science in the real-world space. She has a focus on rare disease evidence generation, regulatory-relevant real-world research and responsible use of advanced analytics and AI to support study design, validation and decision-making. Julien is co-chair of the International Society for Pharmacoepidemiology (ISPE) Rare Disease Special Interest Group.
Filed Under: Drug Discovery
Tagged With: clinical trials, drug development, Evidence Generation, Orphan Drugs, real-world evidence, regulatory affairs, RWE, ultra-rare diseases
Rethinking evidence generation for ultra-rare diseases
Developing treatments for the approximately 7,000 known rare diseases, particularly the subset classified as ultra-rare, presents profound and often insurmountable challenges for traditional pharmaceutical development paradigms. These conditions, affecting patient populations ranging from fewer than 10 to a maximum of 1,000 individuals globally, render the gold standard of randomized clinical trials (RCTs) not only impractical but frequently unethical. The inherent scarcity of patients necessitates a fundamental re-evaluation of how efficacy and safety evidence is generated, demanding innovative and flexible approaches that uphold scientific rigor while acknowledging the unique constraints of these minuscule patient cohorts.
The U.S. Food and Drug Administration (FDA) has, in recent years, demonstrated increasing awareness of these realities, signaling a crucial shift towards embracing alternative evidentiary strategies. This evolving regulatory landscape is epitomized by two interconnected initiatives: the Rare Disease Evidence Principles (RDEP) process and the FDA’s recent draft guidance on the plausible mechanism framework for individualized therapies. These developments underscore a commitment to fostering innovation in evidence generation, particularly for contexts where conventional trial designs are simply not viable.
The Unprecedented Challenge of Ultra-Rare Diseases
Ultra-rare diseases (URDs), often genetic in origin, impose a devastating burden on affected individuals and their families. Patients frequently endure a prolonged "diagnostic odyssey," sometimes spanning years, before receiving an accurate diagnosis. Even then, the vast majority of URDs lack any approved treatment options, leaving patients with limited or no therapeutic recourse. The sheer rarity of these conditions creates a vicious cycle: limited patient numbers deter research and development due to the high costs and perceived low return on investment, perpetuating the lack of available therapies.
Traditional RCTs, designed for larger populations, rely on statistical power derived from hundreds or thousands of participants to detect significant treatment effects and minimize bias. For URDs, recruiting even a handful of eligible patients globally can be an arduous task, often requiring international collaboration and extensive travel. Furthermore, the ethical implications of withholding potentially life-saving treatment from patients in a placebo arm, when so few individuals are affected and often suffer from rapidly progressive conditions, are profound. The logistical and ethical barriers effectively halt the progress of promising therapies before they can even begin to demonstrate their potential. This stark reality has long necessitated a re-evaluation of the "substantial evidence" standard, which traditionally required reports from at least two adequate and well-controlled investigations. However, regulatory frameworks have historically allowed for flexibility, permitting a single pivotal trial supplemented by confirmatory evidence in appropriate circumstances, particularly in oncology and rare diseases where urgency and population size dictate adaptability.
A Paradigm Shift in Regulatory Thinking: FDA’s Evolving Stance
The FDA’s journey towards greater flexibility in rare disease drug development is not a sudden one but rather an evolution shaped by decades of experience and advocacy. The Orphan Drug Act of 1983 was a landmark piece of legislation that provided incentives such as market exclusivity and tax credits to spur the development of treatments for conditions affecting fewer than 200,000 people in the U.S. While highly successful in increasing the number of approved orphan drugs, the Act primarily addressed rare diseases, not the distinct challenges posed by ultra-rare diseases.
Over time, as scientific understanding of genetic diseases advanced and patient advocacy grew, the FDA recognized the need for even greater adaptability. This evolution is reflected in various guidance documents and the agency’s willingness to approve therapies based on innovative trial designs. The introduction of RDEP and the plausible mechanism framework represents a formalization and expansion of this longstanding, risk-based regulatory flexibility within existing regulations. These initiatives acknowledge that while the need for scientific rigor remains paramount, the means of demonstrating substantial evidence of effectiveness must adapt to the unique circumstances of ultra-rare populations.
Introducing the Rare Disease Evidence Principles (RDEP) Process
The FDA introduced the Rare Disease Evidence Principles (RDEP) process specifically to enhance clarity and predictability for sponsors navigating the complex landscape of ultra-rare disease therapy development. It serves as a crucial mechanism for early, focused dialogue between drug developers and regulators regarding evidentiary strategy, thereby formalizing principles previously articulated in various FDA guidances and prior approvals.
The RDEP process is meticulously designed for development programs that satisfy stringent criteria, primarily focusing on diseases with extremely limited patient populations. While the exact criteria were not fully detailed in the original article, common understandings suggest it applies to conditions with a global prevalence often well below the 1,000-patient threshold. The process is distinct from other FDA engagement mechanisms, such as end-of-Phase II or pre-new drug application (NDA)/biologics license application (BLA) meetings, and is not intended to expedite approval timelines. Its true value lies in establishing early alignment on what constitutes acceptable evidence when conventional development approaches are inherently insufficient.
Central to RDEP is the affirmation that substantial evidence for ultra-rare disease therapies can be based on a single adequate and well-controlled clinical investigation, provided it is accompanied by appropriate confirmatory evidence. This approach, building on the FDA’s 2023 guidance recognizing that one trial plus confirmatory data may meet statutory standards, offers a pragmatic pathway forward. Studies conducted under RDEP must still ensure reliable outcome assessment, minimize bias, and be capable of supporting causal inference. Crucially, these do not necessarily need to be RCTs; single-arm trials can be acceptable when rigorously paired with high-quality external controls, such as well-characterized natural history cohorts or other relevant real-world data (RWD) sources. This flexibility is vital for de-risking development decisions and can indirectly contribute to accelerating the availability of therapies for these critical unmet needs.
The Plausible Mechanism Framework: A Scientific Compass for Novel Therapies
Complementing the RDEP process, the FDA’s draft guidance on the plausible mechanism framework provides a scientific blueprint for how diverse evidence types can coalesce to support drug approval. This framework is particularly relevant for individualized therapies and ultra-rare conditions, describing circumstances where clinical benefit, even if observed in a very small number of patients, can justify approval when underpinned by a scientifically plausible mechanism. This mechanism must convincingly link a therapy’s molecular action to the known biological cause of the disease.
Within this framework, evidentiary packages may include a synergistic combination of clinical data, robust mechanistic evidence, and various contextual data sources. The most compelling packages demonstrate internal consistency across these multiple data streams. This can encompass detailed mechanistic and biomarker data elucidating the drug’s target engagement and pharmacodynamics, relevant nonclinical (animal and in vitro) studies, comprehensive natural history data outlining the untreated disease course, and even data generated through expanded access programs or meticulously documented case series.
The draft guidance significantly addresses the pivotal role of natural history data and external controls, especially when RCTs are not feasible – a scenario common for RDEP-eligible programs. A well-characterized natural history of the disease in untreated patients is a core component, providing essential context for interpreting any observed treatment effects. It establishes the baseline against which therapeutic intervention can be measured, offering crucial insights into disease progression, variability, and relevant endpoints. Similarly, external control arms, meticulously derived from robust registries, observational studies, or other high-quality RWD sources, can support causal inference by providing a comparative group when randomization is impractical. Methodological rigor in selecting and matching external controls is paramount to mitigate bias and ensure the validity of comparisons.
Recent approvals vividly illustrate the practical application of these principles. For instance, the approval of ITVISMA® (onasemnogene abeparvovec-brve) for certain spinal muscular atrophy (SMA) patients exemplifies this integrated approach. The primary evidence from a well-controlled study was powerfully supported by confirmatory evidence related to its mechanism of action and efficacy data derived from another therapy containing the same active ingredient. These combined data sources reinforced the plausibility and consistency of the observed treatment effect, providing the "substantial evidence" required for regulatory approval despite the limited patient numbers.
The Indispensable Role of Real-World Evidence (RWE)
Real-world evidence (RWE), derived from real-world data (RWD) collected outside traditional clinical trials, plays an increasingly critical and multifaceted role within the RDEP review process. Its utility begins even before formal development, assisting sponsors in determining whether a disease meets the ultra-rare prevalence threshold for RDEP eligibility. This is especially valuable for conditions that are historically underdiagnosed, inconsistently coded in health records, or clinically heterogeneous, making precise prevalence estimates challenging.
Once RDEP eligibility is confirmed and a development program is underway, RWE continues to be invaluable throughout the entire review lifecycle:
- Natural History Studies: RWE is crucial for characterizing the natural progression of ultra-rare diseases. Patient registries, electronic health records, and claims data can illuminate the typical course of illness, identify relevant clinical endpoints, and understand disease heterogeneity. This baseline knowledge is fundamental for interpreting treatment effects in small interventional studies.
- External Control Arms: As discussed, RWE can provide robust external control arms for single-arm trials, offering a comparator group when randomized placebo-controlled trials are unfeasible. This requires sophisticated analytical techniques to adjust for potential confounders and ensure comparability between the treated group and the RWD-derived control.
- Endpoint Validation: RWE can help validate clinical endpoints and outcome measures, ensuring they are meaningful to patients and sensitive enough to detect changes in small populations. This might involve assessing the real-world impact of specific symptoms or functional limitations.
- Safety Monitoring: Post-market RWE, gathered through patient registries, adverse event reporting systems, or observational studies, can continue to monitor the long-term safety and effectiveness of approved therapies, particularly for conditions with delayed onset of symptoms or rare adverse events not observable in limited pre-market studies.
- Patient Perspective: RWE can capture the lived experience of patients, including quality-of-life measures, patient-reported outcomes (PROs), and the impact of the disease on daily functioning. This qualitative and quantitative data is vital for demonstrating the clinical meaningfulness of a therapy beyond traditional clinical endpoints.
However, leveraging RWE for ultra-rare diseases also introduces specific challenges. Working with extremely small patient populations necessitates heightened privacy protections and robust data governance to minimize the risk of patient re-identification. Even seemingly anonymized datasets can become vulnerable when demographic and clinical characteristics are unique to a few individuals. Furthermore, the inherent variability in RWD sources—different coding systems, data collection methodologies, and clinical practices across global sites—can lead to inaccurate or inconsistent reporting. The adoption of standardized data models and shared clinical ontologies is therefore crucial. By ensuring consistent definitions for diagnoses, endpoints, and outcomes, aggregated RWD becomes easier to interpret and more reliable for regulatory decision-making, helping to bridge the gap between disparate global data systems.
Strategic Engagement: A Multistakeholder Approach to Success
Despite the increasing flexibility offered by frameworks like RDEP, the success of ultra-rare disease development programs remains heavily reliant on early, continuous, and strategic engagement with all relevant stakeholders.
- Early Regulator Engagement: Prior to initiating a pivotal trial, sponsors should submit an RDEP request under an existing investigational new drug (IND) application, accompanied by a formal meeting request. This proactive dialogue, ideally initiated when early clinical data are available and there is still flexibility to shape study design and evidence strategy, is paramount. Early alignment can clarify whether a program qualifies for RDEP and delineate the specific types and quantity of confirmatory evidence that will be deemed acceptable, helping sponsors avoid costly evidentiary strategies that later prove misaligned with regulatory expectations.
- Payer and Post-Market Needs: Beyond FDA approval, sponsors must anticipate the evidence needs of payers and other post-market stakeholders as early as possible. Payer evidence requirements often extend beyond regulatory efficacy, focusing on real-world effectiveness, cost-effectiveness, long-term outcomes, and comparative value. When pre-approval datasets are inherently small, proactive planning to generate this additional evidence through RWE studies or patient registries becomes even more critical to ensure market access and reimbursement.
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