Transforming Healthcare Data into Decision-Ready Evidence
Clinician-Led Real-World Evidence (RWE) & AI Solutions
Winner: Global Scrip® Award — Best Use of Real-World Evidence
Recognized by industry peers in London for best-in-class methodology.
What We Do
Six specialized services to power your research, from data to decisions.
Medical Coding & Phenotype Definition
Expert code lists across ICD-10, SNOMED CT, CPT, LOINC, RxNorm, and more — clinically curated for global observational studies.
Learn More→Algorithm Development & Validation
Transparent, reproducible algorithms to identify conditions and outcomes in claims and EHR data, validated to regulatory standards.
Learn More→Data Labeling & Annotation for AI & RWE
Clinician-led labeling of phenotypes, outcomes, treatments, and patient journeys — ground truth for reliable AI and defensible evidence.
Learn More→Study Design, Analytics & Scientific Communication
End-to-end support from protocol design through advanced analytics to peer-reviewed publication and regulatory-ready evidence packages.
Learn More→Patient Profile Curation
Detailed longitudinal patient profiles built from claims, EHR, and registry data with full audit-ready traceability.
Learn More→External Control Arms & Digital Twins
Digital patient representations, synthetic data, and external control arms to optimize trials and support regulatory decisions.
Learn More→The Architecture of Evidence
Clinician Oversight at Every Step
High
Sensitivity
High
Specificity
✓
PPV Validated
Our algorithms combine clinically informed phenotypes with advanced analytics and AI-driven validation. Every code list and algorithm is reviewed by practicing clinicians and epidemiologists.
See our full approachValidated by the Scientific Community
KarMMa-RW: comparison of idecabtagene vicleucel with real-world outcomes in relapsed and refractory multiple myeloma
This ECA was used as a case study in the EMA 2025 Workshop
Comparison of lisocabtagene maraleucel vs. conventional therapy in relapsed/refractory large B-cell lymphoma using a real-world synthetic control arm
This ECA was used as a case study #3 in the EMA 2025 Workshop
Identifying relapsing-remitting multiple sclerosis (RRMS) in United States integrated delivery network healthcare claims and electronic health record (EHR) data
Le HV, Truong C, Kamauu A, et al.
DOI: 10.1016/j.jval.2018.06.014Real-World Treatment Patterns and Clinical Outcomes in Patients With Extensive-Stage Small Cell Lung Cancer Treated With First-Line Platinum-Based Chemotherapy and ≥ 2 Subsequent Lines of Therapy in the United States
Sankar K, Unni S, Eberl M, et al.
DOI: 10.1007/s12325-025-03408-zA Multidisciplinary Team of Experts
Clinicians & Epidemiologists
Clinical domain expertise driving every code list, algorithm, and study design.
Biostatisticians & Data Scientists
Advanced analytics, causal inference, and AI-ready data pipelines.
Claims, Registry & EHR Specialists
Deep knowledge of real-world data sources and their strengths and limitations.
Delivering accurate medical coding, robust study design, and reproducible real-world evidence that meets regulatory and HTA standards.
Partner with Precision
Clinician-Led
Medical accuracy at the source.
Methodological Rigor
Validated algorithms and transparent logic.
Audit-Ready
Documentation prepared for regulatory scrutiny.