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Pharma & Life Sciences

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

The field of pharmaceuticals has always been at the forefront of medical innovation, continuously striving to develop new and effective treatments for various diseases and conditions. In recent years, the integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies has brought about a revolution in the pharmaceutical industry. These advanced technologies have accelerated drug discovery, improved clinical trials, enhanced patient care, and transformed the entire healthcare landscape. This section explores the significant impact of AI/ML in the pharmaceutical sector, highlighting its advantages and potential challenges.

There is significant value at stake that can be created with AI/ML across multiple Pharma Functions.

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.

Determine the most optimum drug price​

Optimize pricing, making the process data driven and automated while managing the sometimes-opposing forces of ​staying within regulatory swim lanes, managing public perception ​and driving greater profits.


Model analyzes influential predictors such as drug exclusivity, patent expiry, changes in competition, changes in market prices of similar / competitive drugs, regulatory guidelines etc. It can also factor in the impact of price changes on market access.

Once in force, the model can in real time, incorporate the effect of any change in cost of raw materials or production, regulatory guidelines, inventory or demand supply equilibrium.

Tailored marketing and sales strategies for Pharmacies. 

Develop customized sales & marketing strategies for individual pharmacies / allocate resources to maximize returns​


Analyze pharmacy panel data (anonymized), sales activities, demographic information and location data​ to

  • Derive insights on potential for each pharmacy location for various segments / products / brands. ​
  • Allocate resources across pharmacies in order to maximize returns. ​
  • Tailor the sales & marketing efforts based in insights on promotions / pricing, brands etc. derived from past sales data​