AI-enabled Landscape Intelligence Platform for Life SciencesGet your products to market and keep them there
Drive dramatic efficiencies across clinical, regulatory, labeling, safety, market access, and medical affairs teams.
Rapidly answer critical questions by leveraging Dr.Evidence’s Augmented Intelligence approach,
which combines human domain expertise and fit-for-purpose AI.
Who We Serve and How
Understand the competitive landscape globally, from labels to regulatory documents to clinical trials and scientific literature
Easily research prior precedent to inform clinical, regulatory, labeling, safety, market access, and medical affairs strategy
Generate rapid, on-the-spot answers for internal and external stakeholders, with reliability and accuracy you can trust
“Fantastically efficient… gives me more time to strategize rather than manually sort the data.”
"...saves me hours and hours of time."
"Very useful when comparing safety profiles of competitive or companion drugs."
"...the best source of information with a potent search engine."
“…a significant step forward in driving efficiencies…”
"Could not do my job without it."
Platform Modules
The industry standard in label intelligence, enabling rapid prior precedent research, side-by-side comparisons and competitive monitoring to advance regulatory and labeling strategy.
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A breakthrough in regulatory intelligence capabilities, streamlining the access and interrogation of FDA and EMA documents. No more combing through multiple websites and weeding through hundreds of pages of PDFs.
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The next-generation scientific search engine, powered by artificial intelligence, enabling teams to generate actionable insights based on the universe of published literature, clinical trials, patents, grants, congresses, and beyond.
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Why Choose Us?
Augmented Intelligence — 20 years of human-powered domain expertise combined with artificial intelligence.
Dr.Evidence leverages over 25 robust large language, machine learning, and natural language processing models to rapidly identify and extract the relevant content from...