DRE is a market leader in AI-enabled medical insights with its Software-as-a-Service (“SaaS”) platform that enables stakeholders in the healthcare ecosystem to generate actionable data insights far beyond human capabilities.

Experience the insights

SOLUTIONS

DL-2020w-ui

DOC Label™  is a labeling and regulatory platform which allows users to search, compare and contrast across drug labels

DS-2020ui

DOC Search™  is an artificial intelligence biomedical search engine that comprehensively encompasses all of the global literature

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DOC Analytics™  is a rapid analytical tool that generates direct, network and cohort analysis from AI-search results

Industry Use Cases

R&D

Discover trial design options using full knowledge of historical precedent and awareness of data that lead to optimal drug development and lead to increased success rates of clinical trial endpoints

REGULATORY AND LABELING

360° indication monitoring and competitive intelligence for labelling activities to continuously track regulatory data used in drug labels

REAL WORLD DATA/EVIDENCE

Leverage the universe of medical information for Real-Word Data to enable insights supporting the product lifecycle and integration with your existing data assets

COMMERCIAL

Drive success in product commercialization and brand performance by leveraging data and insights from high-quality sources that integrate directly with your product strategy

HEOR

Agile ability to generate on-the-fly data-driven decisions with robust statistical analysis to evaluate the full-range of evidence value stories

MEDICAL AFFAIRS

Enable comprehensive rapid synthesis of relevant sources that serve as the basis for understanding the medical literature landscape to formulate responses to HCPs and internal constituencies

MARKET ACCESS

Configure fit-to-purpose reviews of the evidence landscape to inform key value messaging and real-time exploratory analyses to inform product differentiation and Payer communication

PV/Epi/SAFETY

Continuous monitoring and surveillance to identify relevant safety adverse events for signal detection programs and scientific plausibility evaluations as well as landscape epidemiological evaluations for disease incidence and prevalence