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Transforming Musculoskeletal Research With Real-World Evidence

Article
September 1, 2025
RegenMed, in partnership with the Orthopaedic Research and Education Foundation (OREF), has launched M.O.T.I.V.™ — a pioneering initiative to generate structured, peer-reviewed, and clinically meaningful real-world evidence (RWE) datasets across the full spectrum of musculoskeletal (MSK) conditions.
RegenMed and OREF Launch MOTIV™: A Peer-Reviewed Real-World Evidence Library for Musculoskeletal Innovation RegenMed, in partnership with the Orthopaedic Research and Education Foundation (OREF), has launched M.O.T.I.V.™ — a pioneering initiative to generate structured, peer-reviewed, and clinically meaningful real-world evidence (RWE) datasets across the full spectrum of musculoskeletal (MSK) conditions. MSK disorders represent one of the largest global health burdens. Nearly one-third of the world’s population will experience an MSK-related condition in their lifetime, from degenerative joint disease and traumatic injuries to bone cancers and rare genetic disorders such as osteogenesis imperfecta. In the United States alone, MSK care costs are estimated to exceed $980 billion annually, nearly 5% of U.S. GDP. Yet despite this immense cost, outcomes for patients remain inconsistent. Scientific progress is slowed by reliance on traditional clinical trials, which are lengthy, expensive, and selective. Meanwhile, insurers and government payers are placing new emphasis on outcomes tracking — such as Medicare’s penalties for providers who fail to collect long-term results on hip and knee replacements. The Limitations of Today’s Data While “real-world evidence” has become a buzzword in healthcare, the vast majority of available datasets are derived from electronic health records, insurance claims, or proprietary algorithms. These sources, though large, are fragmented, unverifiable, and often lack correlation between diagnosis, treatment protocols, and long-term outcomes. The result is evidence that fails to meet clinical utility standards, limiting its role in advancing precision care, improving health equity, or accelerating innovation. What Makes M.O.T.I.V.™ Different The M.O.T.I.V.™ (Musculoskeletal Outcomes Through Informed Validation) program is designed to overcome these barriers. Each dataset in the library is: • Peer-Reviewed by OREF: Every observational protocol is vetted by leading MSK researchers. • Anatomically & Clinically Specific: Defined by one anatomical region, one pathology, one treatment protocol, and one standardized outcomes assessment. • Validatable to Primary Sources: Built for transparency and trust, avoiding unverifiable big-data manipulation. • Longitudinal & Fit-for-Purpose: Meeting FDA requirements for clinical and regulatory use. • Statistically and Clinically Relevant: Designed to support meaningful insights that improve patient care. By setting a new standard for structured, verifiable real-world data, M.O.T.I.V.™ ensures that research and innovation in orthopaedics are both clinically rigorous and widely accessible. Driving Value-Based Care and Innovation The launch of M.O.T.I.V.™ marks a critical step toward achieving value-based care in musculoskeletal medicine. By creating datasets that are trusted, transparent, and clinically actionable, RegenMed and OREF are empowering: • Providers to benchmark treatments and improve patient outcomes. • Insurers and payers to make evidence-based reimbursement decisions. • Researchers to accelerate the path from lab to bedside. • Patients to benefit from more equitable, data-driven care. This initiative positions RegenMed and OREF at the forefront of a healthcare transformation — one where real-world evidence is no longer an aspiration, but a validated, practical tool for medical advancement
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Circles: A New Model for Real-World Evidence in Life Sciences

Article
August 27, 2025
Big data RWE is convenient but flawed: stale, incomplete, and legally risky. RegenMed Circles provide a better way — clinically relevant, auditable, and continuously growing datasets that power HEOR, medical affairs, regulatory submissions, and AI.
Life sciences companies spend vast sums on real-world evidence, often relying on massive secondary datasets sold by big data aggregators. While these resources are convenient, familiar, and easy to license, they were never designed to address the nuanced questions that matter most to regulators, payers, and clinicians. The industry now faces an inflection point: the need for high-quality, longitudinal, verifiable evidence that is both strategically relevant and future-proof.The Problem With Big Data RWETraditional big data RWE draws primarily from electronic medical records (EMRs) and insurance claims. These datasets capture billing events and limited treatment codes, but they lack longitudinal outcomes, omit critical variables, and often arrive stale. Many areas of great importance — rare diseases, advanced therapies, and complementary interventions — are invisible in these datasets. Moreover, questions of ownership and legality loom large, with mounting costs and growing scrutiny around unauthorized data use. For artificial intelligence (AI) applications, which increasingly shape pharma’s strategy, these foundations are fragile and risky.Circles: A Better Way ForwardRegenMed’s Circles represent a new paradigm. Built on rigorously defined Observational Protocols (OPs), analogous to randomized controlled trial protocols, Circles generate datasets that are:‍Clinically Relevant: Tailored to specific therapeutic questions and aligned with HEOR, medical affairs, and regulatory needs. ‍Verifiable and Auditable: Every data point is timestamped, source-verified, and traceable. ‍Federated and Equitable: Data remains under local ownership, ensuring broader participation and inclusion of underrepresented populations. ‍Living and Continuously Growing: Unlike static datasets that depreciate, Circles appreciate over time as new cases and longitudinal outcomes are added. ‍AI-Ready: Standardized and proprietary, Circles provide a defensible foundation for training machine learning models without legal ambiguity. Benefits Across The Life CycleCircles provide critical advantages across the product lifecycle: Health Economics and Outcomes Research (HEOR): Strengthened cost-effectiveness models and payer negotiations through longitudinal, auditable outcomes data. Medical Affairs: Enhanced engagement with KOLs, support for outcomes-based contracts, and scientifically credible evidence generation. Post-Market Surveillance: High-quality longitudinal monitoring suitable for regulatory submissions and compliance with safety commitments. Rare Disease Research: Aggregation of small patient cohorts across institutions into statistically meaningful studies. Innovation Enablement: High-quality training datasets for AI, validation for digital health tools, and fuel for translational research. Future Proofing: Alignment with evolving regulatory standards, payer expectations, and AI-driven healthcare ecosystems. Comparative AdvantageWhile big data RWE will not vanish, Circles decisively outperform it in areas where big data structurally fails: rare diseases, post-market safety, outcomes-based reimbursement, and AI model training. Circles datasets are fresher, more complete, and strategically aligned with regulatory and payer needs. Unlike static licensed datasets, they grow in value, establishing a sustainable evidence ecosystem.Practical ImplementationCircles are not disruptive to adopt. They fit into existing budget categories (post-marketing, Phase IV, HEOR, rare disease) and can typically be launched in 4–6 weeks at costs lower than a single-year dataset license. Federated architecture ensures compliance and scalability across geographies, while AI-assisted coding workflows streamline data harmonization.ConclusionThe limitations of big data RWE are becoming more apparent as healthcare shifts toward value-based care, AI-driven analytics, and patient-centered outcomes. Circles are not merely a tactical supplement but a strategic imperative. By delivering clinically relevant, auditable, and continuously growing datasets, they provide life sciences companies with a credible, cost-efficient, and future-proof foundation for evidence generation. Early adopters will not only reap immediate advantages but also lead the industry into the next era of real-world evidence.Contact us to learn more.
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Validatable Real‑World Evidence for Pediatric Musculoskeletal Care: How Circles Closes the Gap

Article
August 20, 2025
Discover how real-world evidence is transforming pediatric musculoskeletal care—improving diagnosis, long-term outcomes, and family experiences. Learn how innovative data approaches like Circles are closing gaps in research and guiding better decisions for children's health.
Pediatric musculoskeletal (MSK) conditions span everyday sprains and overuse injuries to scoliosis, juvenile idiopathic arthritis (JIA), congenital deformities, infections, tumors, and rare neuromuscular disorders. What unites them is the need for decisions that respect growth and development, where early recognition, longitudinal follow‑up, and patient‑family experience matter as much as imaging and lab values. Yet the evidence gaps are real: randomized controlled trials (RCTs) in children are often constrained by ethics, logistics, and small cohorts. The result is uncertainty about long‑term outcomes, conservative (non‑drug) care, and the total burden borne by families.Why The Gaps Persist‍Diagnostic complexity: Children present differently from adults, may not verbalize pain, and “red flags” are subtle. Limb or joint pain can even herald systemic disease. Infections like osteomyelitis may not appear on X‑rays for one to two weeks, and septic arthritis carries a narrow window to prevent permanent damage—where “time is joint.”Developmental variability: Conditions appear at different ages and evolve over growth. Examples include scoliosis (≈3% of adolescents), clubfoot and developmental dysplasia of the hip (~1 in 1,000 births each), and slipped capital femoral epiphysis (~0.5 in 1,000 early adolescents). Care pathways must adapt to growth spurts and changing biomechanics.‍Long trajectories and lived burden: Many pediatric MSK conditions unfold over years. Pharmacologic options for JIA, for instance, have substantial costs and require sustained monitoring; bracing and physical therapy demand adherence that’s hard to measure outside research settings. Families shoulder indirect costs (missed work, travel, lodging) alongside clinical challenges.Traditional research limits: RCTs remain vital for efficacy questions but under‑represent children and rarely capture multi‑year real‑world outcomes or quality‑of‑life effects.Why Real‑World Evidence (RWE) NowReal‑world data (RWD) from electronic health records, registries, claims, digital health, and patient‑generated sources can fill gaps by observing diverse children over time in routine care. With 99% of U.S. hospitals and about 90% of office‑based clinicians using EHRs, the substrate exists to answer pediatric questions faster, at lower cost, and at scale. RWE complements — not replaces — RCTs by showing effectiveness, safety, and adherence in heterogeneous settings and by surfacing outcomes that matter to families (function, return‑to‑play, school participation). Methodological rigor still matters: data quality, missingness, confounding, and selection bias must be addressed to make findings decision‑grade.What Makes Circles DifferentCircles is RegenMed’s structured, clinician‑efficient approach to producing validatable RWE. Each Circle starts with a prospectively designed Observational Protocol (OP) focused on a concrete clinical objective for a well‑defined cohort and anatomy/pathology. Data capture flows through the physician‑facing inCytes™ and the patient‑facing Benchmarc™ modules, minimizing administrative burden while elevating patient (and caregiver) engagement. Three elements stand out:‍Closed‑system, high‑fidelity datasets: Circles integrate diagnosis and treatment data with well‑correlated long‑term outcomes, producing datasets that are controlled, unambiguously owned, and free of artifacts. This is crucial when rare cohorts and small N’s can otherwise magnify noise.Built‑in collaboration: Pediatric orthopedics often needs multi‑site aggregation to reach statistical power. Circles are designed for cross‑institutional — and even cross‑national —i nvestigator networks, enabling representative cohorts for rare or complex conditions.A continuous improvement loop: OP → collaborative data generation → ongoing analysis/learning → refined standards of care. Validatable RWE becomes a practical tool for clinical decision support, education, compliance, and funding — linking evidence to everyday practice and sustainability.Where Circles Moves The NeedleEarlier, more accurate diagnoses: By correlating granular histories, exams, imaging, labs, and outcomes across large cohorts, Circles help surface atypical presentations (e.g., leukemia presenting as limb pain) and time‑critical signals (e.g., septic arthritis) that are often missed in fragmented records. Longitudinal clarity for long‑horizon conditions: Multi‑year capture supports conditions whose trajectories span growth, such as scoliosis, JIA, and dystrophies —illuminating real‑world effectiveness and safety of bracing, physical therapy, and biologics.Evidence for interventions where RCTs are impractical: For pediatric devices and off‑label or compassionate uses, Circles generate the quality of RWE needed for label expansions, post‑market surveillance, and pediatric‑specific guidance.‍Non‑pharmacologic care, finally quantified: Circles track adherence (e.g., bracing hours, physical therapy frequency/intensity) and relate it to objective function (range of motion, return‑to‑play) and patient‑reported outcomes, strengthening the case for conservative care and reimbursement.‍Value‑based care and health economics: Benchmarc™ captures the lived experience — pain scales, CHAQ/PedsQL, and caregiver costs (missed work, travel, lodging) — to quantify true “cost of illness” and inform smarter payment models.Regulatory‑grade insight: With structured capture and multi‑site cohorts, Circles’ datasets align with how regulators increasingly use RWE to support new indications, pediatric populations, dosing refinements, and post‑approval requirements.Illustrative Pediatric MSK Use CasesScoliosis: Compare bracing adherence and curve progression with functional and respiratory outcomes; define timing and thresholds for bracing vs. early surgical options (e.g., fusion, tethering). ‍JIA: Track real‑world adherence, safety, and durability of biologics over years; relate disease activity control to school participation and caregiver burden; refine treat‑to‑target protocols. Congenital deformities & rare neuromuscular disease: Aggregate multi‑site cohorts to characterize natural history, assess emerging therapies, and set pragmatic standards of care when single‑center RCTs are infeasible.Sports and overuse injuries: Quantify prevention and rehab protocols, identify risk factors (load, environment, nutrition), and define safer, data‑driven return‑to‑sport criteria.(See the summaries in Table 1 on pediatric MSK challenges, Table 2 on RWE advantages/limitations, and Table 3 on Circles use cases.)What Good Looks Like: From Data To DecisionsThe goal is not more data but better decisions. Circles connects high‑quality, longitudinal datasets to the work clinicians, families, payers, and regulators must do:For clinicians: earlier recognition; clearer care pathways; fewer avoidable surgeries; better rehab; practical decision support at the point of care.For families: visibility into outcomes that matter; reduced time and money burdens; shared‑decision‑making grounded in evidence.For payers and health systems: credible HEOR to pay for what works; reduced waste from non‑adherent or poorly sequenced care.For innovators and regulators: validated post‑market surveillance and faster pediatric label evolution without compromising safety.Pediatric MSK care needs multi‑stakeholder collaboration, standardized data models and interoperability, integration of RWE into point‑of‑care tools, regulatory pathways tuned for children, and authentic patient‑family engagement. Circles was built for that agenda. By turning routine care into validatable evidence — and doing it with minimal burden — Circles helps close the pediatric evidence gap and accelerates better outcomes for kids.Contact us to learn more.
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