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Real-World Evidence: Unlocking the Full Potential of MSC TherapyMesenchymal Stem Cells (MSCs) represent one of the most versatile and promising tools in regenerative medicine. Their ability to modulate the immune system, reduce inflammation, and orchestrate tissue repair has led to investigations across a wide spectrum of conditions — from osteoarthritis and autoimmune disease to pioneering neurological applications.Yet despite this therapeutic promise, clinical adoption of MSCs has been slowed by a critical barrier: evidence.The Challenge: Evidence Gaps in Regenerative MedicineRandomized controlled trials (RCTs) have long been the gold standard for clinical research. They are designed to minimize bias and deliver clear results in highly controlled settings.But for regenerative therapies, especially cell-based interventions, RCTs often fall short.Short timeframes limit the ability to capture long-term outcomes in chronic or progressive conditions.Strict inclusion criteria mean that many real-world patients — those with comorbidities or complex disease patterns — are excluded.High costs make it difficult to run large-scale, long-duration studies necessary to validate MSC durability.As a result, key questions remain unanswered: Which MSC sources perform best? What dosing regimens deliver sustainable results? How do outcomes differ across patient subgroups?The Solution: Real-World Evidence (RWE)Real-world evidence, derived from data collected during routine clinical practice, offers a transformative way forward. Unlike RCTs, RWE can:Capture outcomes over long time horizons, aligning with the chronic nature of many conditions MSCs target.Reflect the diversity of real clinical populations, not just highly selected trial cohorts.Provide practical insights into dosing, protocols, and durability that matter in day-to-day practice.Regulators, payers, and clinicians alike are increasingly turning to RWE to inform decisions. For regenerative medicine, it is not just complementary to traditional trials — it is essential.How RegenMed Circles Advances MSC EvidenceAt RegenMed, we’ve developed the Circles platform to address the unique challenges of MSC research and care. Circles are physician-led, collaborative frameworks designed to generate validatable, clinically meaningful RWE with minimal burden on providers and patients.Key features include:Structured data capture: Standardized observational protocols ensure clinical depth and comparability.Patient engagement: Tools like Benchmarc™ integrate patient-reported outcomes into the dataset.Collaboration across sites: Physicians pool outcomes data, achieving statistical power and generalizability.Physician ownership: Providers retain control and value from the data they generate.The result is high-quality, auditable datasets that not only advance clinical understanding but also inform regulators, support reimbursement, and accelerate adoption of MSC therapies.Looking AheadThe global MSC market is projected to reach $7.2 billion by 2030, reflecting the immense promise of these therapies. But to fulfill that promise, evidence generation must keep pace with innovation.By combining physician expertise, patient engagement, and rigorous data frameworks, RegenMed Circles is helping to close the evidence gap. Together, we can move MSC therapy from potential to practice — and set the standard for how regenerative medicine proves its value in the real world.Сontact usDownload the White Paper "Circles For Mesenchymal Stem Cell Care And Research", Sept 2025

The Moment For PT Is Here — Now Let’s Make It MeasurablePhysical therapy has moved from a purely post-injury service to a true first-line option for neuromusculoskeletal conditions. Utah’s Senate Bill 196 is emblematic: it explicitly recognizes PT as primary care under insurance law, removing referral friction and signaling confidence in PTs as initial evaluators and managers of back pain, sprains, and joint complaints. The military’s decades-long experience using PTs in primary care roles further demonstrates that this model is safe and reduces downstream utilization.This shift isn’t just philosophical; it’s economic. For common MSK problems, PT often matches surgical outcomes without the costs and risks of invasive care or long-term medication. The “Comparative Economic Value of Physical Therapy” table lists substantial net savings — for example, ~$14k for knee osteoarthritis vs. steroid injections and ~$39k for carpal tunnel syndrome vs. surgery — illustrating how early, non-invasive care changes the cost curve.The profession’s educational foundation supports this evolution. DPT programs blend rigorous biomedical science with extensive clinical rotations, preparing PTs to function as autonomous clinicians and collaborators in complex, multidisciplinary pathways. The result is a workforce ready for first contact care — and ready to generate practice-embedded evidence.The Missing Piece: Trustworthy Real-World Evidence (RWE)Randomized trials remain crucial, but they rarely capture everyday PT practice: diverse patients, real adherence patterns, comorbidities, and social context. Legacy RWE sources — claims, registry feeds, heterogeneous EHR extracts — are often fragmented, retrospectively assembled, and hard to verify back to the primary source. PT’s own outcomes registry (PTOR) struggled with participation and incentives, reminding us that centralized “after-the-fact” approaches stall without shared value and low-friction workflows.If PT is to win durable reimbursement as a first-contact, value-based service, the field needs RWE that is:Verifiable to origin (auditable to the moment of care and the patient);Clinically rich (functional metrics, PROMs, adherence, and course-of-care details);Interoperable (FHIR-compatible, payer-ready, guideline-ready);Equity-aware (SDOH captured alongside outcomes, not as an afterthought);Governed for trust (patient ownership, transparent consent, and federated analytics).Why Circles Fits PT Like A GloveCircles is RegenMed’s protocol-driven RWE platform designed to meet these exact requirements. In physical therapy, Circles functions as a “learning loop” at the point of care: 1. Protocol-driven capture at the source: Observational Protocols (OPs) specific to MSK conditions structure what’s collected: baseline impairment, functional goals, exercise prescriptions, progression, clinician observations — plus patient-reported outcomes and engagement signals. Data is FHIR-compatible and auditable. 2. Patient ownership + federated governance: Anonymized data remains under patient control, and analytics can operate in a federated model across sites. This avoids the participation and incentive pitfalls that limited prior registries. 3. Equity by design: Circles embeds SDOH and access variables directly into PT-tailored protocols, making disparities measurable and actionable for health systems and payers. 4. AI-ready structure: Because Circles data are standardized and verified, predictive models (e.g., likelihood of recovery plateaus, adherence risk, visit intensity needed) become clinically actionable — unlike models trained on inconsistent, retrospective data.Concrete PT Use Cases Where Circles Pays Off1) First-contact triage and pathway optimization: With Circles-guided protocols, clinics capture functional baselines and early improvement trajectories in visit 1–2, producing verifiable evidence that supports “PT-first” pathways and reduces unnecessary imaging and specialist visits. 2) Value-based contracts that reward real outcomes: Circles harmonizes case-mix variables, visit intensity, and PROM improvement, enabling contracts that pay for progress, not just units.3) Precision rehabilitation and adherence support: Circles integrates with wearables, computer-vision ROM tracking, and VR-based engagement tools. Feeding their signals into Circles converts them into verified evidence on adherence and outcomes.4) Continuous quality improvement across clinics: Multi-site groups can compare protocol fidelity, session mix, and time-to-milestone by diagnosis and therapist — without shipping raw PHI.Implementation Blueprint For PT LeadersStart where the value is obvious.Pick 3–5 high-volume MSK lines (e.g., acute LBP, knee OA, rotator cuff, carpal tunnel, pelvic floor). Turn existing eval templates into Circles OPs with required PROMs, visit cadence, and discharge criteria.Wire data at the moment it’s created.Map clinic workflows so clinicians enter outcomes once, at the point of care. Connect patient apps for home exercise check-ins and symptom tracking.Prove it with a 90-day payer pilot.Negotiate a micro-contract on one condition (e.g., acute LBP). Report monthly from Circles on time-to-meaningful improvement, return-to-work, and total cost vs. usual care.Measure equity, not just averages.Disaggregate outcomes by SDOH variables captured in Circles. Use these insights to justify transportation vouchers, extended hours, or digital check-ins.Make AI work for clinicians. Train interpretable models on Circles data (e.g., probability of dropout, predicted visits to achieve MCID). Surface these as point-of-care nudges clinicians can trust.Why this matters system-wideFor policymakers and payers, Circles provides the verification layer that links “PT-first” policy with real outcomes and spend reductions. For health systems, it operationalizes integrated MSK pathways while producing payer-ready, equity-aware evidence. For PT practices, it turns daily work into durable advantages: better contracts, fewer denials, and a reputation for outcomes that patients feel and actuaries can price. For innovators, it’s the interoperable substrate where sensors, VR, and AI become not just engaging — but provably effective.ConclusionPhysical therapy has earned the right to be a first-contact pillar of modern healthcare. To secure that role at scale, PT needs evidence that is trustworthy, comparable, and rooted in the lived reality of care. Circles delivers exactly that — patient-owned, protocol-driven, FHIR-compatible datasets that make value visible, equity measurable, and innovation verifiable. It doesn’t just generate more data; it produces better evidence — the kind that moves guidelines, reimbursement, and outcomes in the same direction.

Executive SummaryThe recently published RegenMed White Paper details why AI-generated and other synthetic datasets struggle to meet the scientific, regulatory, and financial standards of high‑stakes healthcare. Synthetic data can help with exploration and internal testing, but its lack of provenance, difficulty capturing edge cases, and tendency to propagate bias make it indefensible for submissions, audits, or patient‑impacting decisions. A durable path forward prioritizes validatable, patient‑consented Real‑World Evidence (RWE) and hybrid models that link multiple verifiable sources. RegenMed’s Circles platform was purpose‑built to deliver this: longitudinal, auditable datasets that preserve an end‑to‑end chain of custody and perform in real clinical settings.What The White Paper FindsFoundational pitfalls of synthetic dataFidelity and generalizability limits: generative models mimic the center of the distribution, missing rare/critical events and temporal nuances; models trained this way can fail in real care.Patient‑safety implications: evidence cited shows models missed a large share of in‑hospital deteriorations — illustrating how abstract training can overlook real‑world signals.Bias reinforcement: if the source data are biased, synthetic replicas can amplify inequities and create self‑reinforcing feedback loops that degrade trust and widen disparities.Audit and regulatory risksProvenance is non‑negotiable for CMS and private payer audits; synthetic records cannot be tied to a beneficiary chart, clinician, timestamp, or EHR source and are therefore rejected as evidence.CMS has expanded RADV scrutiny and sample sizes, increasing clawback exposure when documentation cannot be traced to a patient of record.FDA guidance across drugs and devices emphasizes transparency, bias mitigation, and fit‑for‑purpose validation; it favors high‑quality RWE and requires detailed justification if synthetic data are used.Stakeholder impactsManufacturers: devices without rigorous human‑data validation are more likely to be recalled; relying on synthetic datasets can mask performance gaps until post‑market exposure.Researchers: results trained/tested on synthetic sets may fail to generalize; opaque generation methods complicate peer review and replication.Payers & providers: financial denials, clawbacks, and malpractice exposure grow when algorithms trained on unverifiable or biased data affect clinical or utilization decisions.Evolving legal landscapeStates are enacting heterogeneous AI health policies — ranging from disclosure requirements for provider use of AI, to bans on automated adverse determinations, to restrictions on AI in mental/behavioral healthcare. The patchwork raises compliance cost and risk for national deployments.The path forward: RWE‑first hybrid data strategyThe paper recommends shifting from data generation to data curation: build fit‑for‑purpose, auditable RWE and connect complementary sources (e.g., claims for the longitudinal journey, EHR notes for clinical context, and structured, protocol‑driven datasets capturing outcomes in routine care). Hybrid clinical trials blend traditional RCT rigor with decentralized, continuous real‑world capture — accelerating timelines while improving external validity.How RegenMed Circles Addresses The WeaknessesAudit‑ready provenance: Circles datasets are built from patient‑consented, clinician‑documented encounters with timestamps, site/clinician identifiers, and verifiable source links — supporting payer and regulatory audits.Edge‑case and rare‑event capture: Circles Observational Protocols focus collection on disease‑specific outcomes, complications, and safety signals — surfacing low‑frequency patterns synthetic data tend to erase.‍Bias mitigation by design: multi‑site enrollment across academic centers and community practices, with stratified capture and QA, improves subgroup representation versus single‑source generative modeling.Regulatory fit‑for‑purpose: Circles maintains data lineage, versioning, and documentation that map to FDA expectations for transparency, validation datasets, and reliability in RWE submissions.Payer defensibility: every measurement is traceable to a patient of record, enabling documentation packs for CMS RADV, medical necessity appeals, and value‑based reconciliation.Hybrid enablement: Circles links clean, protocol‑driven outcomes to claims and EHR context, creating a comprehensive, patient‑level evidence graph for analytics and label‑expansion studies.Operational practicality: with inCytes™ for clinicians and Benchmarc™ for patients, Circles integrate into care pathways to collect longitudinal outcomes without burdening staff or disrupting workflows.Illustrative Use CasesAI device validation: a manufacturer stress‑tests an early‑warning algorithm across comorbid subgroups using Circles outcomes linked to EHR and claims; post‑market surveillance continues with the same auditable pipeline.Medicare Advantage risk & quality: a payer evaluates risk adjustment and readmission programs using Circles’ patient‑linked outcomes and documentation packs, reducing denials and surviving RADV scrutiny.Rare‑event research: investigators studying low‑prevalence complications use Circles to enrich cohorts and capture event timing/severity precisely, improving power and external validity compared to synthetic simulations.Implementation Checklist For PartnersDefine the fit‑for‑purpose question and target decisions (regulatory, reimbursement, labeling, clinical).Select/author Observational Protocols that enumerate required outcomes, timepoints, covariates, and safety signals.Establish data lineage: site IDs, user/clinician attribution, timestamps, and immutable source references.Link Circles outcomes to claims and EHR extracts to create a patient‑level evidence graph.Pre‑specify validation plans and bias checks aligned to FDA and payer expectations; document everything.Package audit materials (data dictionaries, lineage, consent artifacts, and chart access pathways) for CMS/private payer reviews.ConclusionIn healthcare, speed without provenance is a liability. Synthetic datasets are useful scaffolding for exploration and internal QA, but they cannot carry the weight of clinical validation, regulatory approval, or financial accountability. Circles provides the auditable RWE backbone — and the hybrid linkages to EHR and claims — needed to translate AI and analytics into safer products, smoother approvals, defensible reimbursement, and better patient outcomes.Download the White Paper, “Weaknesses of AI and Other Synthetic Data in Healthcare,” Sept 2025.

Dear Friends and Investors,I’m excited to share a brief update on RegenMed’s progress. We’ve had a busy season, advancing partnerships, strengthening our investor position, and extending our reach in both healthcare innovation and academic collaboration. Here are four highlights we’re proud of:Partnering with OREF to Launch MOTIV™Together with the Orthopaedic Research and Education Foundation, we launched MOTIV™, a peer-reviewed library of real-world evidence datasets in musculoskeletal medicine. This is a milestone toward replacing unverifiable “big data” with clinically rigorous, FDA-fit datasets that improve patient outcomes and support value-based care.Sponsoring UW–Madison’s Capstone ProjectWe’re investing in the next generation of innovators by sponsoring a University of Wisconsin Computer Sciences Capstone team. Students will enhance our patient-reported outcomes (ePRO) platform with gamification and UX improvements, mentored by RegenMed leaders. We join sponsors like Epic, Google, and GE HealthCare in supporting this nationally recognized program.Welcoming HyperFlex Medical as a New ClientWe’re proud to add HyperFlex Medical to our growing client base. Their HyperFlex® Bunion Correction System is a minimally invasive, bone-preserving solution for the 23% of adults affected by bunions. With a market projected to grow from $1.47B in 2023 to $2.33B by 2032, this partnership shows how RegenMed Circles support both innovation and scale in high-demand specialties.Launching Our New Investor PageWe’ve launched a dedicated Investor Page, outlining why RegenMed is a Zero-to-One company in a $100B+ healthcare data market. With strong recurring revenues, AI-ready infrastructure, and early investor momentum, we’re building one of the most compelling opportunities in healthcare data today.‍We’re grateful for your continued support as we scale RegenMed’s mission to make real-world healthcare data both trustworthy and transformative. Stay tuned for more updates in the months ahead. Warm regards,‍Michael P. TierneyCEO, RegenMed

RegenMed’s Investor VisionRegenMed is redefining how healthcare generates and uses real-worldevidence (RWE). Our patented Circles platform captures structured, verifiable, and clinically validated data from everyday medical practice — helping payers, providers, and researchers make smarter decisions.We recently launched our new Investor Page, highlighting the unique value propositions that make RegenMed a compelling early-stage investment opportunity.Where We Are Today‍Proven Platform: Circles is already enabling physician-owned datasets that are auditable, unbiased, and regulatorily compliant.‍Growing Traction: Adoption of Circles has accelerated since late 2024, with expanding interest from providers, researchers, and payers.‍Recurring Revenues: A SaaS-driven model with strong grossmargins and scalable network effects.Unlike traditional “big data” solutions, Circles datasets are transparent, clinically relevant, and FDA-fit for purpose.Where We’re GoingRegenMed is building the next layer of healthcare data intelligence:‍AI-Ready Infrastructure: Integrating a recursive AI learning layer that enables natural-language queries across Circles datasets — without the risks of opaque “black box” AI.‍Blockchain & Tokenization: Exploring models for secure, incentivized data ownership that empower both patients and providers.‍Global Growth: Scaling geographically and acrosstherapeutic areas to meet surging demand for trusted real-world evidence.Market OpportunityThe healthcare data opportunity is massive and expanding:‍Healthcare data analytics market: $64B, growing at 21% CAGR.‍Healthcare data market overall: $60B+, growing at 11% CAGR.‍Addressable opportunity for RegenMed: Exceeds $100B as demand for trusted RWE accelerates.This is a sector where quality, verifiable data is fast becoming the single most valuable resource for healthcare payers, regulators, researchers, and innovators.Competitive AdvantagesRegenMed is positioned uniquely because:We own the data — clear provenance and auditable origins.We deliver clinical-grade evidence aligned with FDA and payer standards.We offer low-burden deployment for physicians and patients.We’re already AI-ready — structured datasets support trustworthy insights.Investor Momentum‍Strong Investor Demand: Our last investment window closed ahead of schedule in March 2025.Proven Exits in the Space: Comparable firms such as CorEvitas were acquired for nearly $1B by Thermo Fisher.‍High Engagement: Regular investor webinars (Nov 2024, Dec2024, June 2025) outline both near-term execution and long-term scale.ConclusionRegenMed is a “Zero-to-One” company: defining a breakthrough category, delivering clinical and commercial value, and positioned in a rapidly expanding market.For investors seeking transformative healthcare opportunities, RegenMed offers a patented platform, growing traction, and a $100B+ addressable market — with the potential to reshape how medicine collects, validates, and applies real-world data.Explore more at invest.rgnmed.com.