AI engine to extract, compare and standardize clinical data from unstructured data
One of the biggest challenge in clinical trial data management is to extract the meaningful clinical information from unstructured clinical data and standardize them to appropriate target structure. This process is both time-consuming and manual. At doLoopTech, we have developed our Clinical NLP engine from ground up to specifically solve these problems of clinical trial industry.
It takes an average 3 months to write a single Clinical Study Report (CSR) document. Over 40% of the text in the CSR document is taken as it is from various input sources. Multiple resources (Internal + CROs) are invovled in writing CSR. One of the biggest challenge in Medical Writing is inconsistency of the text and language across the CSRs from the same pharma company.
Mining for similar clinical content from the historical library of CSRs is humanly immpossible. Our AI engine Clinical NLP with a state of the art cloud based platform application helps find similar clinical content from various input source documents and allows you to create/manage standard clinical content database.
Our Clinical NLP engine allows you to perform an intelligent match to find the most optimum standardized MedDRA code for your incoming AETERMs. Based on the NLP and statistical confidence level, the solution learns and improves the matching algorithm automatically. The AI engine is API based product which allows easy integration with any third party TMS systems. It is also fully integrated with our Clinical eBridge data integration platform.
The solution uses the following clinical information to perform the match and provides the standardized clinical term: