Integrated Evidence

Medidata Integrated Evidence is a real-world data and analytics platform designed for sponsors and CROs engaged in clinical development. It connects historical trial data, real-world insights, and AI-driven modeling to support safer protocol design, stronger comparators, and more efficient development pathways. As therapies grow more complex, Integrated Evidence provides the regulatory-grade, patient-level evidence needed to drive confident decisions across the full development lifecycle.

At its core, Integrated Evidence draws from one of the industry's most comprehensive repositories of regulatory-grade clinical trial data — spanning tens of thousands of trials, millions of patients, data from more than 30 countries, and billions of data points collected annually. Through the Data Collaboration Program, sponsors and CROs grant governed usage rights to de-identified, patient-level data, enabling secure modeling and benchmarking with full privacy protection. AI-driven synthetic data generation further extends this foundation, supporting advanced modeling while preserving data integrity.

Core Data Capabilities

• Cross-sponsor historical trial data providing broad, comparable patient population benchmarks
• Protocol-defined covariates and endpoints captured exactly as specified in study protocols
• Governed data collaboration through the Data Collaboration Program, ensuring client and patient confidentiality
• AI-driven synthetic data modeling using patented algorithms that preserve subject-level privacy while maintaining clinical trial data structure

Solutions Powered by Integrated Evidence

• Medidata Trial Design: Models protocol scenarios using cross-sponsor, regulatory-grade patient-level trial data to improve efficacy prediction and increase the probability of regulatory success. Combines data from over 38,000 trials and 12 million patients with AI-powered analytics to identify high-risk patients and inform safer, evidence-based protocols before costly delays or failures occur.
• Medidata Synthetic Control Arm®: Constructs external control cohorts from regulatory-grade historical patient-level data to reduce enrollment burden while maintaining scientific rigor. Particularly valuable for rare or life-threatening diseases where recruiting a concurrent control group is difficult, enabling benchmarking without additional enrollment.
• Medidata Link: Links trial data to external real-world data sources at the patient level, extending evidence beyond the boundaries of the study itself.
• Simulants: Generates high-fidelity synthetic datasets from regulatory-grade historical trial data to support non-regulatory modeling and protocol refinement. Unlike generic synthetic data, Simulants retain high fidelity and statistical validity, allowing sponsors to refine protocols and identify early efficacy signals with confidence.

Key Use Cases and Clinical Benefits

• De-risking clinical development: Benchmarking cross-sponsor, regulatory-grade historical trials reveals how comparable patient populations performed under standard of care and which eligibility criteria drive response, positioning programs for regulatory success and label expansion.
• Strengthening patient safety: Protocol modeling identifies patients most likely to benefit and supports safer protocol design informed by longitudinal evidence.
• Reducing trial cost: External control cohorts and synthetic data tools reduce the need for large concurrent control arms, lowering enrollment burden and associated costs.

Therapeutic Area Research and Scientific Validation

• CAR-T and Immunotherapy: Longitudinal cross-sponsor trial data identifies predictors of severe cytokine release syndrome (CRS) and CRS/ICANS in CAR-T therapies, informing safer protocol design. Research has been presented at ASCO 2022, ASH 2022, and EHA 2023, and featured in publications such as FierceBiotech.
• Cardiovascular: Historical trial data across major adverse cardiovascular events validates identification algorithms and supports comparative benchmarking under evolving standards of care. Research has been presented at STH 2021, DDW 2022, and ISPOR 2023.
• Synthetic Data: Peer-reviewed generative modeling research demonstrates interpretable techniques that preserve subject-level privacy while maintaining clinical trial data structure for simulation. Findings have been presented at ICML 2023 and NeurIPS 2022.

Training and Support

• Medidata offers a variety of training options for clients and partners, including both self-paced and instructor-led courses available through the Medidata Global Education and Training program.

Integrated Evidence is validated through peer-reviewed research and collaboration across oncology and cardiovascular clinical data scientists, with findings presented at leading scientific conferences including ASCO, ASH, ICML, and NeurIPS. The platform operates within the broader Medidata Platform ecosystem, complementing Study, Patient, and Data experiences alongside Professional Services offerings.