For RWE methodology leads at academic medical centers, CROs, and pharma RWE groups. Five-method causal sensitivity pentagon as a single API call — AIPW, doubly-robust ATT, instrumental variable, neural counterfactual, Rosenbaum bounds — with reproducibility certificate and target-trial-emulation scaffolding on every study. Replaces the hand-rolled methodologist work behind every observational pharma submission.
The lead biostatistician writes the propensity model in SAS, the doubly-robust adjustment in R, the instrumental-variable check in Stata, and the sensitivity analysis as a footnote — if at all. The reviewer at the FDA reads four scripts in three languages with no cross-validation between methods. The reproducibility certificate is a hash in a SharePoint folder.
"A plan for robustness assessments including deterministic sensitivity analyses, quantitative bias analyses, and net bias evaluation." — PRINCIPLED process guide, Desai, Wang et al., BMJ 2024;384:e076460.
Rosenbound delivers five methods on the same cohort, on the same platform, with the same audit ledger. The methodologist defines the cohort and treatment contrast; the platform runs AIPW, DR-ATT, IV-LATE, the neural counterfactual estimator, and the Rosenbaum-Γ bound. The reproducibility certificate is generated on submit.
Each feature is in production today. Try the full RWE workflow on a synthetic cohort at rosenbound.ai.
AIPW (Robins 1994 + Bang-Robins 2005), DR-ATT with Crump-2009 overlap trim (Hahn 1998), IV-LATE 2SLS with per-prescriber instrument, neural counterfactual estimator (patent-pending), Rosenbaum 2002 Γ-bound. One submit; five estimates with covariate balance per method.
YAML-formatted cohort spec: treatment_value, control_value, outcome_definition, time_windows, index_date, inclusion/exclusion. CSV upload auto-generates a draft DSL; methodologist refines. Version-controlled per study.
Per study: cohort definition hash, cohort data hash, certificate ID, git commit of the platform version, and pinned library versions for every method. The exact re-derivation guarantee regulators ask for, in the UI — not in a SharePoint folder.
Studies protocol-type for Hernán-style target trials: eligibility, treatment strategies, assignment, time-zero, outcome, causal contrast, analysis plan. Explicit guards against immortal-time bias. Aligned with the TARGET reporting statement (Cashin, Hansford, Hernán et al., JAMA 2025).
On every study result: drag the Γ slider, see the bound envelope update in real time, watch the crossing-at-zero point shift. The verdict ("at Γ = 1.06, very sensitive") is generated, not narrated.
Each of the five estimators carries its own page: covariate balance table, feature attribution, propensity distribution, instrument F-statistic for IV-LATE, Γ-curve for Rosenbaum. Where a method doesn't produce a metric, we say so — not fabricate it.
Read OMOP CDM v5.4 standard tables (PERSON, CONDITION_OCCURRENCE, DRUG_EXPOSURE, MEASUREMENT, OBSERVATION_PERIOD), resolve standard concept_ids against an Athena vocabulary load, auto-populate the Cohort DSL. ATLAS cohort import (JSON/SQL via OHDSI WebAPI) in the same release window. Phase-2 deliverable.
One-click submission package: reproducibility certificate + methodology section + sensitivity pentagon figures + hash-chained audit trail, formatted to TRIPOD+AI (Collins et al., BMJ 2024) and the FDA 7-step AI credibility framework.
Upload a cohort, define the contrast, submit. Watch all five methods compute. Drag the Γ-curve. Download the reproducibility certificate. No login, no setup. rosenbound.ai →
The "Considerations for the Use of Real-World Data and Real-World Evidence to Support Regulatory Decision-Making for Drug and Biological Products" (final Aug 31, 2023) directly motivates the five-method pentagon + sensitivity bound as the right shape for an observational submission.
Data-quality, traceability, and provenance expectations from the Jul 25, 2024 final guidance map directly onto Rosenbound's Cognitive Validation Report, cohort hash, and audit ledger.
"Identifying and addressing the presence of confounding and other forms of bias is critical… planned sensitivity analyses." Cited verbatim because that's what the Γ-bound is.
FDA Sentinel Innovation Center's PRINCIPLED process (BMJ 2024) + the TARGET reporting statement for target-trial emulation (JAMA 2025) both shape the studies-protocol UX and the methodology PDF export format.
Watch the product walkthrough at rosenbound.ai — three moments that define the platform: the Cognitive Validation Report refusing incoherent data, the live Γ-bound sensitivity visualization, and the reproducibility certificate generated on every study. The full platform stays gated for Founding Partners.
Watch the preview →
pip install rosenbound
— Official Python SDK for programmatic access: cohort upload, sensitivity-bounded study runs, and reproducibility certificate retrieval. Apache 2.0; Pydantic v2 typed; py.typed for IDE autocomplete + mypy. Platform access gated by Bearer token + RBAC + tenant scoping — the SDK is open, the audit substrate is not.
$100K year 1, $175K years 2–3, $250K/yr year 4+ locked at Founding rate forever. Direct founder Slack, quarterly roadmap input on the OMOP/ATLAS integration sequence, named-reference recognition, co-authorship on benchmarks run against your cohort, waived integration setup.