Ignacio Medrano
Founder / CMO
Savana
Savana utilizes Clinical Natural Language Processing to extract and analyze data from Electronic Health Records, transforming unstructured clinical information into actionable insights. This technology enables healthcare providers and life sciences companies to access real-world evidence efficiently, improving patient care and decision-making in real time.
- Artificial Intelligence
- Data & Analytics
- Digital Health
- Healthcare Technology
- Software Only
Updated 5 months ago
Funding
Funding rounds are not available yet.
Founders
Product
Problem
Healthcare providers and life science companies struggle to efficiently extract and analyze meaningful insights from the vast amounts of unstructured data contained within Electronic Health Records (EHRs). This makes it difficult to leverage real-world evidence (RWE) for improving patient care and decision-making.
Solution
Savana provides an AI-powered platform that utilizes Clinical Natural Language Processing (NLP) to unlock the value of unstructured clinical data within EHRs. The platform transforms this data into actionable knowledge, enabling healthcare providers to reuse existing medical records for clinical research and decision support. For life science companies, Savana facilitates the creation of deep RWE, making data easily accessible for improved patient care in real time. Savana's technology is designed to comply with OHDSI standards and utilizes the OMOP Common Data Model to ensure efficient analysis and reliable evidence generation.
Target Audience
Savana's primary customers include healthcare providers seeking to reuse EHR data for actionable knowledge and life sciences companies aiming to create disease RWE for improved patient care.
Features
- Clinical NLP engine for multi-language processing of medical records
- Capabilities include anonymization, section detection, named entity recognition (NER), negation/speculation detection, temporality analysis, named entity disambiguation (NED), and acronym NED
- Data modeling set up following the OMOP Common Data Model
- Compliance with OHDSI standards for efficient analysis and reliable evidence
- ISO 27001 certified for information security management
- European patent for patient privacy mathematical formula
- AI + RWE studies across 17 therapeutic areas and 13 countries