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Pharma & Life Sciences

AI / ML Applications and Use Cases in Pharma & Life Sciences Industry

Gestalt brings pre-built AI analytics enabled solutions and has invested in (& matured) building a methodology which helps our clients institutionalize AI/ML solutions within their organization.  We bring to every project well defined frameworks, templates and best practices which accelerate the delivery and adoption of AI enabled solutions.

Key solutions detailed below, which have been developed in close association with various clients, have relied heavily on using advanced Anomaly detection, NLP and Transparent Machine learning capabilities of EazyML.

Prioritize Clinical Trials

In the drug certification process, understand early on in the process of the likelihood of success or rejection of the drug, in case of higher probability of rejection, withdraw early from the process and save considerable resources.

The answer to which trials to pursue, and which not to, lies buried in data. EazyML’s Augmented Intelligence can mine these insights – express as simple rules about the characteristics of the drugs that are likely to go through, and those that aren’t, helping the executives make smart business decisions based on data’s objectivity. As a next step, predictive model could be developed to predict this; coupled with EazyML’s Explainable AI, this could be a powerful tool for researchers and executives to understand the profitable drugs that are likely to get approved.

Predict & prevent cost overruns during Clinical Trials

Clinical trials of drugs are expensive. Why not mine the trial data to find out what are the characteristics of a drug that results in cost overrun – for instance, the disease, the medical professionals engaged, the pool of patients, among other important parameters – expressed as simple rules, each rule with its parameters-and-thresholds? EazyML’s Augmented Intelligence does precisely that. And as documented above, as a next step, predictive analytics coupled with Explainable AI will help immensely by Decision AI.

Quality Assurance of the Product

Derive insight from a large portfolio of imaging data and quality ratings and assist with Quality Assurance of the end product. EazyML’s patent pending confidence score can enable Quality Assurance teams to determine which images of product for assessing product quality and which should not, so as to not be misled.