Project Overview

Our pharmaceutical client approached us with a critical challenge: ensuring the safety of their products in an increasingly complex healthcare landscape. They sought a solution to proactively identify potential adverse events (AEs) from a wide range of data sources, including social media, global database and customer feedback.

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Solution Offered

To address our client's challenges, we implemented a cutting-edge solution leveraging a generative AI model. Trained on a vast dataset of healthcare-related information, this model efficiently analyzes text data from diverse sources, identifying potential patterns or anomalies that may indicate adverse events.

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    API:

    Developers can integrate the Gen AI model's functionalities into their applications through a user-friendly API. 

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    Model Catalogs

    We Leveraged LLMs like GPT - 3.5, GPT -4, Llama 2, and Mistral allowing us to explore their capabilities for performing tasks

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    Prompt Catalogs

    Guidance on crafting effective prompts to elicit optimal results from the model.  

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    Workbench (Design Thinking UI):

    This user interface allows customers to interact with the model directly. It includes features like: 

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    AE Visualization

    Clear presentation of identified AEs with detailed explanations.  

Solution:

This solution delivers significant value for healthcare and pharmaceutical companies: 

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    Improved Patient Care:

    Early detection of AEs allows for proactive measures to safeguard patient health and prevent complications.

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    Increased Efficiency:

    The highly accurate Gen AI model streamlines AE detection, saving time and resources compared to manual methods. 

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    Enhanced Product Development:

    Analysis of customer feedback and social media data aids in identifying potential side effects and improving future products.

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    Global Reach:

    Multilingual support empowers the solution to be used by clients worldwide, fostering better patient care on a global scale. 

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