💊 Pharma Solution

Real-World Research Support: From Design to Evidence Preparation

ReHealth Core supports real-world research with data governance, study design, and causal analysis. Drug or device registration submissions must be conducted independently under the applicable regulations, protocol, and regulatory requirements.

Dynamic patient datasets with intervention trajectories — far more valuable than static historical data. PSM analysis directly applicable to clinical trial design, producing NMPA-compliant real-world evidence.

Get in Touch → RWE Methodology Guide

RWE

Real-world research methodology

PSM

Reusable for clinical trial design

4类

Data delivery modes

合规

PIPL · IRB · Audit Log

Core Challenges

Three Data Barriers in Real-World Research

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Limited Value of Static Data

Traditional medical databases are mostly static historical records, lacking intervention trajectories needed for longitudinal real-world efficacy studies.

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Causal Evidence Hard to Obtain

Regulators increasingly require causal interpretability in real-world evidence, not just correlation. But generating credible causal evidence outside RCTs has high methodological barriers.

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Compliance Barriers

PIPL and Data Security Law impose strict requirements on healthcare data processing, making it difficult and costly for pharma to directly access patient data.

Solution

Data & Analysis Support for Four Research Use Cases

Target Discovery & Biomarker Research

Real-world patient data with SHAP feature attribution for identifying key cardiovascular risk factors and potential targets. Dynamic datasets include pre/post-intervention biomarker trajectories.

SHAPLongitudinalBiomarkers

Patient Stratification Modeling

16-dimensional clinical features and risk scores for fine-grained stratification of target indication populations, identifying patient subgroups most likely to benefit from specific interventions.

16 FeaturesSubgroupsEnrollment Optimization

Clinical Trial Design Optimization

PSM causal analysis framework directly provides historical controls and propensity score models for clinical trials, supporting external control construction for single-arm trials to reduce sample size and shorten timelines.

External ControlSample OptimizationHistorical Control

Research Evidence Preparation

Produce methodology notes, data-quality checks, match-quality assessment, effect estimates, and scope statements for internal real-world research evaluation and study-material preparation. These materials are not a registration conclusion or regulatory recognition; the applicable validation and compliance work must be completed separately.

RWEStudy DesignMethod Documentation

Data Delivery Modes

Four Flexible Data Access Modes

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De-identified CSV Dataset

Customized de-identified patient datasets by indication, sample size, and follow-up duration with intervention trajectories and outcome metrics.

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Secure API Access

Encrypted API for real-time queries of patient risk scores and feature attribution, ideal for integrating ReHealth data into pharma internal analytics platforms.

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Analysis Report

Reports document research methods, quality checks, effect estimates, and scope statements for internal evaluation and study-material preparation; sponsors and their professional advisers determine any submission use and applicability independently.

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Data Sandbox

Analyze data within ReHealth Core's secure computing environment. Data never leaves. Pharma researchers can run their own analysis code in the sandbox.

Data Compliance

Six-Layer Compliance for the Strictest Requirements

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Fully De-identified

All data is de-identified locally before entering the analysis pipeline.

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PIPL Compliant

Compliant with all PIPL data processing requirements.

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IRB Approved

Data collection and use approved by institutional review board.

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DUA Protected

All data licensing governed by formal Data Use Agreements (DUA).

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Re-identification Prohibited

Agreements explicitly prohibit any attempt to re-identify individual data.

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Full Audit Trail

Complete audit logs retained for all data access and analysis operations.

FAQ

Pharma Partnership FAQ

How does ReHealth Core support real-world research?

It can support data governance, study-protocol discussion, match-quality assessment, effect estimates, and scope statements. PSM only helps reduce bias from observed confounding and does not replace prospective validation or applicable regulatory requirements. Any NMPA registration submission must be completed independently for the relevant drug or device.

What advantages do intervention trajectory datasets have over static data?

Static data only supports cross-sectional analysis. Longitudinal data with intervention trajectories enables: ① Real-world efficacy validation; ② Patient subgroup discovery based on intervention response; ③ External control construction for single-arm trial designs.

Which indications does the database currently cover?

Currently focused on cardiovascular-related indications including hypertension, dyslipidemia, type 2 diabetes (as cardiovascular risk factors), and composite cardiovascular disease risk. Coverage expands as more institutions connect.

Ready to Learn More?

Get in Touch →Read RWE Guide