Real-world Data (RWD) and Real-world Evidence (RWE)

We translate your evidence question into a scientifically defensible study design—selecting the right data sources,endpoints, populations, and comparators before a single record is pulled.

We source and harmonize EHR data, insurance claims, patient registries,genomic databases, wearable outputs, and PRO instruments, thus delivering clean, linked datasets ready for analysis.

We design and execute observational studies and CER programs that generate causal, publication-quality evidence, while controlling for confounding using propensity scoring, instrumental variables, and causal inference frameworks.

We quantify disease burden, treatment costs, and quality-of-life impact across patient populations, producing the HEOR models that underpin payer submissions and value dossiers.

Our evidence synthesis teams conduct systematic literature reviews, meta-analyses, and network meta-analyses, consolidating the evidence base that supports regulatory filings and HTA submissions.

We deploy AI-powered signal detection and longitudinal safety monitoring across RWD sources, identifying adverse events, drug interactions, and risk patterns that clinical trials cannot capture at scale.

We map treatment pathways, care gaps, and unmet needs across geographies and demographics – generating the epidemiological intelligence that guides portfolio decisions and label expansions.

We architect and deliver submission-ready evidence dossiers for FDA, EMA, NICE, and other regulatory and HTA bodies – ensuring every analysis meets the evidentiary bar for label claims and reimbursement decisions.

Predictive models for disease progression, treatment response, and outcome stratification transform raw RWD into forward-looking intelligence, enabling smarter trial design, indication expansion, and risk management.

Understanding HCP segmentation, HCP behaviour, target market identification, and competitive analysis.