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.
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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