-Written by Dr Siva Kumar Buddha, PV SME/Consultant
The pharmacovigilance sector faces challenges such as handling increased data volume and keeping up with regulatory changes that include adhering to regulatory timelines and reducing mundane tasks performed by highly skilled personnel. This demands a solution which can build efficiency and compliance through AI and automation.
As technology advances, it is becoming increasingly vital for the pharmaceutical sector to adopt new tools and processes in order to assure the safety and efficacy of their medicines. ChatGPT, a big language model built by OpenAI and based on the GPT-3.5 architecture, is one such tool. It has the potential to transform pharmacovigilance, which is the act of monitoring, identifying, analysing and preventing adverse drug effects.
ChatGPT is a natural language processing (NLP) model that recognises and responds to human speech. It can create text, answer questions and do a variety of other linguistic tasks. The programme has been trained on a massive amount of data and can comprehend the context and meaning of words and sentences. As a result, it is an effective tool for pharmacovigilance.
Analysing Unstructured Data
The capacity to analyse unstructured data is one of the primary advantages of adopting ChatGPT for pharmacovigilance. Adverse drug reactions are often reported in a variety of media, including social media posts, news stories and medical records. These reports may contain limited or inconsistent information, making standard techniques of identifying and analysing them difficult. ChatGPT can evaluate these reports and extract pertinent information, such as the kind of adverse event, its severity and the medicine involved. This can assist pharmacovigilance teams in identifying possible safety risks and taking suitable mitigation measures.
Identifying Emergent Safety Concerns
Another possible use for ChatGPT in pharmacovigilance is identifying emergent safety concerns. To discover adverse events, pharmacovigilance teams frequently rely on spontaneous reporting methods. These approaches, however, may fail to detect new or previously undiscovered adverse effects, which can be especially difficult in the case of uncommon or complicated disorders. ChatGPT can analyse a large amount of data from a variety of sources to identify patterns or trends that may suggest impending safety risks. This can assist pharmacovigilance teams in identifying possible safety risks and taking proactive efforts to mitigate them.
Clear and Concise Communication
ChatGPT may also be used to increase patient and healthcare practitioner communication and engagement. Patients and healthcare providers can report adverse drug occurrences through a variety of outlets, including social media, online forums and patient support groups. ChatGPT can analyse these reports and give patients and healthcare practitioners rapid and accurate replies, which increases their engagement and happiness. This can also improve the quality and number of adverse event reports, thereby giving pharmacovigilance teams additional information to work with.
Exploring the Flaws and Challenges of Technology in the Modern World
It is crucial to emphasise, however, that the application of ChatGPT in pharmacovigilance poses several obstacles and restrictions. The model’s precision is one of the most difficult issues. Despite having been trained on a large quantity of data, it is not flawless, and its replies may occasionally be wrong or misleading. As a result, it is critical to check and verify the results obtained by ChatGPT using other sources of information. Another disadvantage is its inability to completely comprehend human language context and subtleties. This can be especially difficult in the case of unfavourable event reports. To increase the model’s accuracy and efficacy, it is critical to train it on relevant data and offer it with suitable context and direction.
ChatGPT has the potential to revolutionise pharmacovigilance and increase drug safety and efficacy. Its capacity to analyse unstructured data, predict emergent safety risks and improve communication with patients and healthcare providers can assist pharmacovigilance teams significantly. However, it is critical to be aware of the model’s issues and limitations and to make sure the deficiencies can be solved.
While ChatGPT can be used to augment pharmacovigilance efforts, it should not be relied upon as the sole means of reporting adverse events. It is important for healthcare professionals to continue using official reporting channels to ensure all potential adverse events are investigated and managed appropriately.
About the Author
Dr Siva Kumar Buddha is a medical doctor by education and also holds an MBA degree in Leadership and Strategy. He has a decade of experience in Pharmacovigilance with work experience in different CROs and pharmaceutical companies. He is currently working at a pharmaceutical company as a Sr Manager Global Safety Physician. Dr Siva has presented in various global and regional PV forums and his special interests are on Lean methodologies and AI integration in pharmacovigilance.
Disclaimer: The views expressed in this blog post are solely based on my personal experiences and opinions, and do not necessarily reflect the views or opinions of my employer or the company I work for. Any information, advice or recommendations provided in this blog post should not be considered official or endorsed by my employer or company and should be used at the reader’s own discretion.