Neha Singh

Patient Event Prediction:

• Analyzed large datasets (~600k patients) to identify trends and patterns in patient behaviors.
• Devised predictive models using machine learning algorithms like XGBOOST and LightGBM to predict patient drug switching behavior and drugs drop offs .

Adopter Analysis:

• Analyzed structured & unstructured data for US based primary healthcare providers to identify opportunities to promote the newly launched drugs.
• Applied tree based algorithms to predict the possibility for adopting newly launched products in the pharmaceutical market.

Potential Incliner/Decliner :

• Sales prediction for next month using XGBOOST and LSTM for regression based on historical data of US based healthcare providers to facilitate course of action for medicals representatives.

• Collected data on competitors, consumers and the marketplace and consolidated data into presentations and reports.

• Patentability, infringement and state of the art patent analysis.