Automating data ingestion & formatting – improving visualization
Data Restructuring & Informatics Platform
Drug research and testing generate voluminous data from varied sources (diseases, patient information, test/experiment results, FDA compliances) and databases. However, the inability to ingest, structure, and search these makes it’s challenging for pharmaceutical companies to utilize vast quantities of data. DRIP automates the integration and ingestion of this data, helping build a consolidated database for Biotech, Pharma, and Life Sciences companies.
DRIP in a nutshell
Built on complex ML and proprietary rule based algorithms, the platform automates data ingestion and formatting from unstructured or template driven semi-structured spreadsheets. What makes it stand out is the solution’s use of proprietary pattern recognition algorithms and metadata comprehension to generate a database of research data and lab results.
Unstructured Clinical Data To Visualized Formats
A visual representation of DRIP’s role and the end results achieved by the platform while processing unstructured data in various digital formats.
The Advantage In DRIP Led Consolidated Databases
Facilitates the easy processing of unstructured historical data and allows for exploratory analysis.
The semi-automatic formatting of data facilitates the quicker transformation of unstructured data into structured data.
It helps in the realization of rapid drug development and subsequent commercialization.
Effectively manages historical clinical data by handling challenges like data collection, review, and integration.
A consolidated database of research data and lab results helps pharma companies utilize vast quantities of data.
