Biotech, Pharmaceutical, and Life Sciences companies face significant challenges in integrating data from a variety of sources. Drug research and testing is one of the biggest data producer and the inability to ingest, structure, and search data from labs, CROs, and the field make data interpretation a highly inefficient process.
Aventior’s DRIP uses a combination of complex machine learning (ML) and rule-based algorithms to automate the data ingestion, integration, and formatting. Using proprietary pattern recognition algorithms and metadata comprehension, DRIP builds a consolidated database of research data and lab results. Irrespective of the nature of the source data (structured or unstructured) DRIP is capable of transforming the source data into a usable format while maintaining strict control over the quality of data transformation. The platform also enables data visualization and exploration using its own extension, that can be hosted on cloud platforms. DRIP also supports integration with some of the leading data visualization platforms such as TIBCO Spotfire and Tableau or custom R/Shiny applications.
The following two illustrations show the end results achieved by DRIP while processing in-vivo lab tests (unstructured data) into a structured format and followed by visualizing the end result.