Real-World Evidence in Pharma & Medtech: Why the System is Still Underperforming
Why Smarter, Lifecycle-Driven RWE Strategies Are Overdue
Introduction: RWE Has Momentum—But Not Yet Impact
Across Pharma and Medtech, Real-World Evidence (RWE) is now a strategic priority. From early R&D through post-market surveillance, life sciences organizations are investing in real-world data (RWD) to accelerate trials, support approvals, and demonstrate product value. The global RWE market is projected to grow by over 15% annually through 2030 (Research and Markets).
Yet despite growing investment, the system still underdelivers.
Fragmented data, poor quality standards, compliance fears, and lack of coordination continue to limit RWE’s true impact. While the potential is enormous—faster development, smarter approvals, and more personalized care—the reality is still inefficient, biased, and difficult to scale.
In this article, we explore:
Why most RWE strategies fail to deliver lifecycle impact
The operational and regulatory gaps that limit effectiveness
The consequences of low-quality or siloed real-world data
What’s needed to unlock real value from RWE at scale
1. Poor RWD Quality Undermines RWE at Its Core
The promise of RWE rests on the quality of the data—but most data today isn’t fit for purpose.
Much of the data comes from administrative or billing systems, not built for scientific inquiry.
According to McKinsey, gaps, inconsistencies, and lack of provenance remain widespread across most RWD pipelines.
The result? Incomplete patient journeys, missing outcomes, and datasets that require heavy cleaning before use—if they can be used at all.
➡️ Key insight: Until RWD is curated, standardized, and representative, even the best analytics won’t produce useful RWE.
2. Regulatory Support Is Growing, But Standards Are Rising Too
Regulatory agencies are no longer skeptical of RWE—they’re setting expectations for how it should be done.
The FDA’s final 2023 guidance stresses data traceability, robust study design, and early agency consultation for RWE submissions.
In Europe, DARWIN EU is building a federated RWD network across 130M+ patients.
But alongside opportunity comes higher scrutiny. RWE must now meet regulatory-grade expectations, or risk being dismissed entirely.
➡️ Key insight: Regulatory frameworks are evolving fast. The bar for valid, accepted RWE is higher than ever.
3. Fragmentation, Siloes, and Missing Interoperability
One of the biggest challenges in operationalizing RWE is data fragmentation.
Many organizations hold RWD across multiple business units, unlinked systems, and external vendors.
PwC notes that fragmented RWE operations lead to duplication, inconsistent methodologies, and weak impact across the lifecycle.
In medtech, the problem is even more acute. RWE efforts often run separately from product development, commercialization, and safety teams—undermining shared learning and repeatable value.
➡️ Key insight: Without unified infrastructure and cross-functional collaboration, RWE cannot scale or evolve with the product lifecycle.
4. Underutilized in Pre-Launch, Post-Launch, and Next-Cycle R&D
RWE is often relegated to post-market pharmacovigilance, when it could be informing earlier, more strategic decisions.
According to Accenture, RWE is drastically underused in lifecycle planning, site selection, patient identification, and indication expansion.
Applied Clinical Trials highlights that RWE can reduce trial size by 30–50% and help identify new, real-world label expansions.
Many organizations fail to link RWE learnings to next-cycle development, or to feed insights back into early-stage portfolio design.
➡️ Key insight: RWE is most powerful when it spans the entire lifecycle—not when it’s isolated to post-market reporting.
5. Technology Is Moving Fast—But Use Cases Lag Behind
AI, digital health, and predictive analytics are rapidly reshaping RWE capabilities—but most companies are still behind.
AI-based models can now generate synthetic controls, identify real-world comparators, and accelerate data curation.
But according to McKinsey and Deloitte, most organizations lack the structured data, governance, and validation processes to activate these tools at scale.
➡️ Key insight: The future of RWE is real-time, AI-powered, and patient-centric—but only for those who modernize now.
Conclusion: RWE Must Become a Lifecycle Enabler
RWE has proven its value. But to become truly impactful, it must be:
✔️ Reliable – built on curated, diverse, and structured data
✔️ Interoperable – integrated across systems and lifecycle teams
✔️ Strategic – used to guide decisions from R&D to commercialization
✔️ Compliant – aligned with evolving global regulatory frameworks
At Meplis, we believe RWE should not live in silos. That’s why we’re exploring new models to help industry partners connect lifecycle processes, improve data usability, and unlock the full potential of real-world insights.
🚀 Want to move beyond fragmented RWE efforts and build lifecycle-ready, AI-powered strategies that actually deliver impact?
Contact Meplis to explore how we’re helping Pharma and Medtech companies unify real-world data, improve evidence quality, and enable smarter decisions—from early R&D to post-market success.