The biggest gap in what is asked versus what is achievable is that many researchers are trying to identify comprehensive datasets that span multiple payers and patient profiles. While many data vendors are trying to incorporate more diverse data sources (e.g., registries, EHR, multi-payer claims datasets), some of the disease states/indications do not have a singular source of all-encompassing data. As a result, studies need to be performed from various data sources that are combined into a working thesis. Our company is adapting by continuing to stay on the forefront data offerings and investigating how these sources can compliment or be implemented into our current data access.

- Peter Kardel, Vice President, ADVI Health

As evidentiary expectations rise, the biggest gap I see is not just between desired precision and the messiness of real‑world data, but between evidence generation and action. Regulators, HTA bodies, and payers increasingly expect RWD to do more than “just” describe cohorts or outcomes. They want and expect RWD to meaningfully inform decisions and guide continual improvement in practice. This challenge is especially acute in oncology. Disease heterogeneity, rapidly evolving standards of care, biomarker‑driven pathways, and small patient populations make static, one‑time analyses insufficient. Decision‑makers want granular, longitudinal evidence that reflects how care is actually delivered and how outcomes evolve, but many data sources are still fragmented and poorly suited to understand this intensely dynamic clinical landscape. Our response has been to reimagine real-world evidence as key input to a learning health care cycle, not a downstream deliverable. That means investing in research‑grade data products that preserve clinical context, support longitudinal follow‑up, and allow insights to flow back into practice. Embedding evidence generation at the point of care helps ensure study questions are clinically relevant and that findings can meaningfully influence decisions by providers, payers, and policymakers. As expectations rise, advantage will belong to organizations that move beyond evidence for submission toward evidence for action, designed to learn, adapt, and improve care in real time.

– Jessica Paulus, Vice President, Real-World Research, Ontada

As evidence expectations rise across regulators, HTA bodies, and payers, the most visible gap is not the availability of data, but the transparency, causal inference, and fit-for-use of real‑world data (RWD) needed to meet those expectations. Decision makers are increasingly using RWE alongside randomized trials, recognizing its value in informing decisions by reflecting routine clinical practice, broader patient populations, and outcomes observed in real‑world settings. At the same time, RWD encompass a wide spectrum of information generated across the patient journey, from electronic health records and registries to claims, wearables, and patient‑reported outcomes, which means they are often non‑standardized, distributed across multiple sources, not always easily linked, and susceptible to inconsistencies if not carefully managed. This has created an important opportunity for HEOR and RWE teams to strengthen how evidence is generated and applied. Our strategy has evolved to focus earlier and more deliberately on building higher‑quality data foundations, rather than relying solely on downstream advanced analytical approaches to address bias, confounding, and uncertainty. We are prioritizing high-quality data integration, clearer documentation of data provenance, and early alignment on the clinical variables that truly matter for decisions. We are also embracing AI‑enabled approaches to improve data extraction, harmonization, and cleaning, which are helping to reduce burden while improving consistency and reliability. By investing upstream in data quality and transparency, we are better positioned to generate RWE that is credible, decision‑relevant, and impactful, allowing RWE to more effectively support regulatory submissions, HTA assessments, and payer decision‑making as expectations continue to rise.

– Zhaohui Su, Vice President, Biostatistics, Ontada

The gap between what’s being asked and what’s achievable has never felt wider — and it’s widening fastest at the intersection of early access and post-launch evidence requirements. HTA bodies like NICE and G-BA typically expect comparative effectiveness data at submission that, frankly, doesn’t yet exist, particularly in rare diseases and precision oncology. Payers want long-term outcomes; sponsors have 18 months of trial follow-up.What we’re advising clients to do is reframe the conversation early. Rather than treating evidence gaps as a deficit to defend, the most effective strategies we’ve seen position them as a structured uncertainty management plan — one that builds in fit-for-purpose RWE commitments, patient registry linkages, and conditional access frameworks from day one of the value dossier, not as an afterthought. We’re also seeing a shift in how natural history data is being used. In disease areas where RCTs are near-impossible, well-curated external control arms built from claims, EHR, and disease registry data are increasingly accepted — but only when the methodology is transparently pre-specified and robustly validated. The era of submitting RWE without a clear analytical protocol is over.By utilising all of our specialist teams and expertise we can adapt fastest by integrating HEOR, medical affairs, and RWE functions early in development — not waiting until a Phase III readout to shoehorn evidence into an access story.

– Mike Blackney, Partner, Global Value and Access, FIECON, a Herspiegel Company

The role of real-world evidence in regulatory, pricing, and coverage decisions has been rapidly evolving, with it influencing decisions most when it directly reduces material uncertainty within the framework governing that decision. Although its use has increased, and best practice guidance has developed, regulators have made clear that RWD is not a backstop for failed trials. Rather, RWD has the greatest influence where randomization is infeasible or unethical or when used as contextualization of trial findings. However, recent FDA critiques of externally controlled studies in rare diseases underscore lingering uncertainty about regulatory acceptability and RWD’s evolving role. Payers increasingly expect performance-linked reimbursement tied to routine care outcomes. Europe has embedded this through managed entry and coverage with evidence programs, e.g. NICE’s Managed Access and Cancer Drugs Fund, AIFA registries, and agreements in Germany, Belgium, and Sweden, that trigger price renegotiations or indication adjustments based on observed outcomes. In the US, commercial and Medicaid plans are scaling outcomes-based contracts; CMS uses RWE in national coverage decisions and coverage with evidence development and has signalled openness to RWE in IRA negotiations. Decision-makers need assurance that RWD is fit-for-purpose for the decision at hand. This includes the use of timely, relevant, preferably local, data sources; accurate identification of appropriate patients, comparable to trial populations when applicable, and clinically meaningful outcomes; and the application of robust, prespecified methods. RWE fails when bias, confounding, or missingness, erodes trust. Early engagement is advised to surface and address concerns across decision-makers and align on endpoints and analyses.

– Collaboratively answered by Darrin Benjumea, Director, Access & Pricing and Katherine Donegan, Director, Pharmacoepidemiology & Safety, from Genesis Research Group

Real-world data is now virtually everywhere, but it only moves the needle when it’s fit for purpose, or when evidentiary standards align with decision needs. While the concept of data being “fit for purpose” was first introduced nearly a decade ago with the 21st Century Cures Act, actually aligning RWD with a given decisional context remains elusive. For example, some organizations have procured massive datasets thinking “bigger is better,” only to realize that size alone doesn’t guarantee utility or ideal support for the specific context. Furthermore, one dataset rarely fits all use cases. Missing outcomes, biased samples, or endpoints that don’t align with decision needs can quickly undermine credibility. Regulatory submissions and coverage decisions for new therapies can and should demand the highest standards of transparency, reproducibility, comparator selection, and endpoint validation. These decisions directly affect patient safety and public spending, and the evidentiary bar should reflect that responsibility. But not every decision requires regulatory-grade evidence. Faster, more directional RWD analyses can be highly valuable for internal life sciences decisions – shaping clinical development strategy, refining target populations, optimizing trial design, and contextualizing emerging results. In sum, the teams that get value from RWD don’t start with the data. They start with the decision, and then make the data earn their role.

– Jessica Paulus, Vice President, Real-World Research, Ontada

RWD has the greatest impact on pricing, access, and coverage decisions when it is used to address a clearly defined, decision‑relevant uncertainty that randomized trials could not fully resolve. This includes confirming real‑world treatment effectiveness or safety signals post‑launch, demonstrating use in broader or previously under‑represented populations, informing treatment sequencing, and validating utilization or adherence assumptions that meaningfully influence budget impact. In these settings, particularly in oncology, rare diseases, and highly managed therapeutic areas, RWD has supported earlier access, strengthened coverage decisions while long‑term endpoints continue to mature, and enabled more informed reassessment of access restrictions over time. Payers increasingly value RWD as a way to understand how therapies perform in routine practice and how closely real‑world use aligns with assumptions made at launch. Ultimately, what determines whether RWD truly “moves the needle” is not its availability, but fit‑for‑use data, thoughtful study design, and strong collaboration across stakeholders. RWD is most influential when it is prospectively planned, executed with methodological rigor and transparency, aligned to a clearly articulated decision question, and explicitly connected to payer value drivers such as clinical relevance, utilization, and cost. When generated in this way, RWD becomes a valuable input into these discussions; when produced reactively or without a clear decision context, its impact is understandably more limited.

– Zhaohui Su, Vice President, Biostatistics, Ontada

Real‑world data (RWD) has become increasingly available, but its actual impact on pricing, access, and coverage decisions remains uneven. RWD can meaningfully influence decisions when it addresses core uncertainties and fits within formal reassessment or managed‑entry frameworks. For example, HTA bodies such as NICE and CDA-AMC use RWD in structured post‑marketing reassessments to refine or confirm reimbursement, especially through mechanisms like the Cancer Drugs Fund and post‑registration studies in France. These systems allow therapies launched with limited evidence to demonstrate real‑world value and transition to routine access, potentially reaching patients earlier. RWD has also been pivotal in outcomes‑based reimbursement, particularly for high‑cost and complex therapies. European payers use RWD to validate long‑term outcomes, link price to real‑world performance, and reduce financial uncertainty—enabling continued coverage under performance‑linked agreements. In rare diseases and gene therapies, where RCTs may be infeasible, some HTA agencies have even shown willingness to accept RWE as the primary basis for recommendations when methodologically robust. RWD often fails to influence decisions when data quality, transparency, or methodology are insufficient. Payers consistently cite these limitations as major barriers, and many agencies still view RWE as supplementary rather than determinative except in specific contexts. Ultimately, RWD “moves the needle” when it is high‑quality, methodologically credible, timely, and directly aligned to the uncertainties payers must resolve—particularly in high‑cost, high‑uncertainty, or evidence‑limited settings.

– Esther Nzenza, Senior Partner, Global Value and Access, Decisive Consulting, a Herspiegel Company

Although real-world data (RWD) is more abundant than ever, its influence on pricing, coverage, and access decisions varies widely. In our experience, RWD meaningfully changes decisions when it addresses specific uncertainties that trials cannot answer, such as treatment persistence, outcomes in broader patient populations, or comparative effectiveness in routine practice. However, RWD often fails to influence decisions when analyses are methodologically weak or poorly aligned with the policy or payer question. Decision-makers remain cautious about biases in observational data, including confounding, missing clinical variables, and inconsistent coding. If these limitations are not transparently addressed, the credibility of the analysis—and its impact—declines. Timing and integration also matter. RWD is most effective when it is part of a broader evidence strategy, paired with clinical data, economic modeling, or expert consensus. Ultimately, three factors determine whether RWD moves the needle: methodological credibility, relevance to the decision being made, and integration with complementary evidence sources. When those elements align, RWD can meaningfully shape discussions on value, pricing, and access.

– Ashis Das, Senior Director, Strategic Analytics and Value Economics at ADVI Health

Affordability pressures continue to challenge healthcare systems and manufacturers, now intensified by a surge in policy changes that has created unprecedented complexity. Companies face a dual tension: the need to act while uncertainty persists about how new policies will unfold, resulting in delayed decisions and slower commercialization. In the European Union, Joint Clinical Assessment (JCA) is prompting earlier preparation and cross-functional alignment. However, success will depend on the quality of early strategic planning, as a gap remains between JCA outputs and country-specific requirements, including economic and budget-impact evidence. In the U.S., the proposed Most Favored Nation (MFN) policy is contributing to delayed decision-making around international pricing strategies. Manufacturers are assessing potential exposure and revenue implications as they balance price, volume, and tariff considerations across markets. At the national level, policy changes—such as updated value assessment approaches and revised cost-effectiveness thresholds from the National Institute for Health and Care Excellence (NICE) in England—are complicating launch planning. Together, these dynamics have created a period of interdependent global uncertainty, increasing demand for clear, pragmatic strategies. While recent years have seen increasingly complex and innovative pricing models, the most effective approaches in 2026 emphasize three principles: start early, think locally, and focus on value. Early planning enables manufacturers to identify the evidence most likely to influence access decisions and to model alternative pricing strategies. A granular, market-specific perspective clarifies launch sequencing, pricing processes, and cross-country reference risks. Identifying patient subgroups with the greatest unmet need—where clinical and economic value are strongest—provides a robust foundation for broader expansion.

– Richard Tolley, Principal, Global Value & Access, FIECON, a Herspiegel Company

TrumpRx is limited in its reach today with around 40 drugs, but it’s growing, and it marks the start to disruption of the pharmacy benefit. Not all products make sense for a direct-to-patient cash-pay program, like expensive rare disease drugs or physician-administered drugs. But the fact that any patients are better off under cash-pay model like this is notable and highlights the flaws with the way PBMs and health plans are setting patients’ out-of-pocket costs.

– Lindsay Bealor Greenleaf, Head of Policy, Research, and Analysis, ADVI Health

TrumpRx is an important signal in the evolution of U.S. drug distribution, but currently better characterized as a targeted disruptor rather than a broader transformation of pricing and coverage structures. The MFN-based, direct-to-consumer cash model challenges the traditional PBM-driven rebate system by introducing transparent pricing outside the insurance framework. For uninsured patients, individuals in high-deductible health plans, and certain chronic therapy categories, this can be meaningfully disruptive. It simplifies the purchasing experience, reduces reliance on opaque rebate mechanics, and places competitive pressure on list-price dynamics that have long defined the market. However, disruption of pricing does not always mean restructuring coverage architecture. The majority of Americans access medications through employer-sponsored insurance or government programs, where formularies, utilization management, rebates, and specialty pharmacy infrastructure shape both access and economics. TrumpRx does not yet integrate into mainstream benefit designs, nor does it replace the clinical and operational services embedded in specialty pharmacy models. Complex specialty therapies require intensive monitoring, prior authorization support, REMS compliance, benefits investigation, and sophisticated cold-chain logistics. Specialty pharmacies function as care-management platforms in addition to dispensers. A consumer-facing, cash-pay channel is not currently designed to replicate that ecosystem at scale. There are also system-level considerations where bypassing insurance can fragment patient data and reduce care coordination. TrumpRx is an alternative distribution model that may influence traditional PBM pricing dynamics. Its long-term relevance will depend on sustained manufacturer engagement and successful incorporation into payer benefit structures. Ongoing market adoption and stakeholder alignment will determine its future role.

– Priya Jain, Executive Director, Strategic Market Access, US MA Commercial Strategy, PPD Evidera Health Economics and Market Access at Thermo Fisher Scientific

TrumpRx’s MFN-linked direct-to-consumer (DTC) cash model is strategically interesting, but in 2026, it is likely a targeted channel rather than a systemic disruptor. Most prescriptions flow through insurance and PBM formularies. Around 6.6 billion prescriptions are dispensed annually, while only 1–2% move through cash-oriented DTC platforms such as Amazon Pharmacy or GoodRx. These channels are dominated by low-cost generics and represent under 1% of total spend. The attraction is net-price certainty and channel diversification. DTC could bypass PBM rebates and potentially delivering similar or better net prices for medicines already carrying large rebates, while capturing patients who abandon prescriptions due to high deductibles. Three product segments are most likely to benefit: High-volume, rebate-heavy primary-care medicines (e.g., cardiometabolic therapies), particularly those facing aggressive PBM rebate competition or formulary exclusion. Specialty niches where patients already pay largely out-of-pocket, such as fertility and IVF medicines, where transparent bundled drug pricing could simplify access and reduce price variability. Therapies with inconsistent insurance coverage, notably GLP-1 obesity treatments, where a large self-pay population already exists due to formulary restrictions. However, manufacturer participation will depend on the strategic pricing risk. Companies may resist MFN-linked cash pricing if it materially lowers U.S. net revenue or creates future reference risk, particularly if the cash price could later be leveraged in broader negotiations with CMS or other payers. By contrast, high-cost biologics, infused therapies, and rare-disease drugs remain dependent on insurance reimbursement and are unlikely to shift to a cash model. The most realistic outcome is hybrid disruption: TrumpRx won’t replace the PBM system, but it could create a transparent pricing benchmark that pressures the existing rebate-driven market with all the benefits and risks that it presents.

– Nic Gwatkin, Partner, Global Value and Access, Decisive Consulting, a Herspiegel Company