This blog is discussing about:
- How AI can help with pharmacovigilance.
- The pros and cons of using AI right now in this field.
- What we think about AI in pharmacovigilance based on our experience.
Table of Contents:
- AI: An Overview
- Artificial intelligence and pharmacovigilance
- Artificial Intelligence: A Blessing or a Burden?
- Key takeaways: Considering Limits
- Conclusion
- References
- FAQ
AI: An Overview
The field of AI research was founded at a workshop held on the campus of Dartmouth College, USA during the summer of 1956.
Artificial Intelligence (AI) is a technology that enables machines to search for and collect information available on the internet.
Although, until now it does not have a physical brain, it designed to perform tasks that traditionally require human intelligence, such as recognizing speech, interpreting complex data, making decisions, and solving problems.
While it may not possess its own intelligence, its ability to access vast amounts of information on the web can make it more efficient than humans in some tasks.
Overall, AI meant to augment and assist human decision-making, rather than replace it.
Given its continuous evolution, anything can change in the future. Let’s adopt a “wait and watch” approach.
Artificial intelligence and pharmacovigilance
There are various potential benefits of using artificial intelligence in pharmacovigilance.
No doubt in that in increasing efficiency, faster identification of potential safety concerns, and may improve in data analysis.
Our Key Concern
However, there are also concerns about the credibility and reliability of AI, particularly when it comes to making decisions and assessments in the field of medicine.
Additionally, the safety and confidentiality of sensitive medical data must ensure when utilising AI in pharmacovigilance.
“Artificial Intelligence, the wondrous fusion of human ingenuity and technological brilliance, reshaping our world with each digital heartbeat, propelling us towards a future where dreams and machines dance in harmonious coexistence.”
Artificial Intelligence: A Blessing or a Burden?
Certain Possibilities
Artificial Intelligence (AI) has the potential to revolutionise pharmacovigilance by helping to reduce the burden on human resources and improving the efficiency of the process.
Here are some ways in which AI can help in pharmacovigilance:
- Automation
- Case Triage and Prioritization
- Language Processing
- Streamlining Reporting Processes
- Semantic searching
- Optical character recognition (OCR)
- Interact with PDFs
- Automatic Report Generation
- Bringing Data Together
1. Automation:
- Can help to Automate in Signal Detection
- Ability to find side effects using real-life evidence from places like social media.
- Responding, phrasing, and answering questions.
2. Case Triage and Prioritization:
AI can help prioritize cases by finding the potential severity of cases.
3. Language Processing:
- LLM: The Large Language Model (LLM) can assist in generating languages by offering suitable prompts that align with the intended output.
- Translations
4. Streamlining Reporting Processes:
AI can help automate the process of adverse event reporting, reducing the time and resources required to submit reports.
5. Semantic searching:
Enhance the accuracy of searchers understanding.
6. Optical character recognition (OCR):
Identify text in scanned documents, also for verification of handwriting text.
7. Interact with PDFs:
Utilize AI to streamline the process of extracting essential points from numerous pages. Simply ask questions and receive answers, leveraging AI’s capability to locate relevant information within the document.
8. Automatic Report Generation:
AI can help create reports on its own and remind us when they’re due, making sure we don’t miss any deadlines. It can also spot the right information to include in these reports.
9. Bringing Data Together:
AI can help us combine information from different places, like websites, social media, and electronic health records. This helps us find problems early and understand them better.
While AI can certainly provide valuable assistance in pharmacovigilance, it’s important to note that its assessments may not always be completely clear or accurate. However, the suggestions provided by AI can still be considered.
Unreliable Possibilities
Unreliable possibilities refers to potential outcomes or options that are uncertain or not completely dependable at the moment. While there are possibilities, they lack full certainty and may not be entirely accurate, although they can still provide some level of assistance.
- Checking Quality: AI can help us find mistakes and risks by looking at the quality of our work.
- Predicting Cases: AI can look at information and guess what might happen next, like figuring out if there might be problems in reports about bad events that were missed.
Limitations
When considering the implementation of AI in pharmacovigilance, it is important to take into account the potential limitations and risks associated with the use of AI.
One critical factor to consider is confidentiality, as sensitive medical data must kept private and secure.
To ensure the confidentiality and security of the data, robust security measures must put in place when designing AI systems for pharmacovigilance.
This can include implementing appropriate access controls and data handling protocols, and ensuring that data not saved in back-end.
Despite these measures, it is still important to carefully evaluate the potential risks and limitations of using AI in pharmacovigilance before implementation.
Key takeaways: Considering Limits
In our view, the use of AI in pharmacovigilance sparks concerns about workforce reduction and cost savings. We believe that AI should be employed within specific limits, focusing on gathering opinions and some limited discussions. Our perspective is based on practical testing.
AI, a computer system, has its limitations:
- AI lacks human-like critical thinking abilities.
- AI isn’t adept at making sound decisions.
- AI’s accuracy is around 80-85%, not infallible.
- It relies on information available on the internet.
- AI serves as a suggested point of reference, not a definitive solution.
- The AI is not able to consistently give accurate scientific proof or consistently summarize questions based on facts.
“We’ve tried and tested this, and it’s what we believe in about AI and its abilities—up to the point it has reached. At the moment, it’s not the right time to let AI handle all the processing on its own.“
Conclusions
The conclusion of this article suggests that there are numerous opportunities for leveraging AI in the realm of pharmacovigilance.
However, it highlights the importance of prioritising security and confidentiality concerns before implementing AI in this domain. I hope that in the future, AI will keep getting better at helping us with medicine safety by making it easier to find and handle problems.
By taking these factors into account, the utilisation of AI in pharmacovigilance can be a safe and effective way to increase productivity and efficiency.
References:
FAQ:
Can you please define artificial intelligence?
What does artificial intelligence in the context of pharmacovigilance?
What are the possibilities of AI in pharmacovigilance?
2. Case Triage and Prioritisation
3. Language Processing
4. Streamlining Reporting Processes
5. Semantic search
6. Optical character recognition (OCR)
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