AI and its applications in Pharmaceutical and Lifescience industries

Pharmaceutical companies strive to develop and deliver safe and effective new therapies to fight and cure diseases. On an average, it takes atleast 10 years for a new drug to complete its journey from initial discovery to the market place. Pharmaceutical companies are investing in AI powered solutions to reduce the time taken in drug development from the lab to post-marketing.

In the pharmaceutical and the drug development industry, there are ample opportunities for deploying AI powered solutions. In drug development, deep learning models are being used to optimize and accelerate drug discovery and development process, for example mapping of raw data to SDTM for faster analysis. During the clinical trials phase, machine learning models are being used to help Data managers to monitor and identify data quality issues continuously.

Pre-trained Natural Language Processing (NLP) models have proven effective to reduce data entry effort while significantly improving quality. AI models have also proven successful in ingesting, optimally searching and correlating thousands of scholarly articles and providing easy to use customized dashboard for research.

Explainable AI (XAI) is an emerging field of machine learning which aims to address how decisions of a AI systems are made. Explainable AI, addresses the concerns of deploying AI in clinical research by providing clear articulation of how an AI decision was made and how the results were produced.

At DataFoundry we are focused on delivering AI based solutions to the Pharmaceutical and Lifesciences industries. Checkout our AI enabled solution for Pharmacovigilance and Drug safety.

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