There is so much discussions and conversations going on around artificial intelligence and machine learning in PV. However, It is critical to understand that there are certain aspects of pharmacovigilance and drug development process that still requires human intelligence.
One of the main reasons as to why human intelligence is paramount importance in the development of next tools for PV is because we humans have a complex and sophisticated neural networks of not just critical thinking but also can show compassion and empathy for human subjects. We as humans can think on a case by case basis for a better solution rather than making the subject a mere number, which is what artificial intelligence does when it analyzes the data that it is featured with.
Here are few insights of such practices:
1. Causality Assessments
2. Case study of individual Sentinel cases of clinical importance
3. Rare occasions of ADRs that are therapeutic area specific and MOA specific with class effect
4. Broader application of signal processing techniques
5. Domain expertise to guide LLMs for better results
6. Proactive assessment of minimal information based on patient experiences
7. Medical justification of complex review of aggregate data for simplification of risk assessment factors
8. Trend analysis of non clinical information to predict human outcomes in clinical trials
9. Development of risk management strategies based on field research and practices.
10. Recommendations to improve the effectiveness of conduct of clinical research based on overlapping toxicities of combination therapies.
Next decade of PV will benefit from the development of AI tools however the human component must not be ignored for better patient outcomes and drug testing.
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