Peter J Pitts, President of the Center for Medicine in the Public Interest, and Hervé Le Louet, President of CIOMS, have just published an intellectually-stimulating essay on the future of pharmacovigilance entitled “Advancing Drug Safety Through Prospective Pharmacovigilance“. The complete reference of the article is: Pitts PJ, Le Louet H. Ther Innov Regul Sci 2018; https://doi.org/10.1177/2168479018766887.
First, the authors point out that we are entering a new era in drug development. To support that statement, they refer to how the FDA is transforming its way of thinking. On the FDA guidelines on collaborative approach for drug development for pediatric rare diseases, the agency proposes new design types for rare diseases, utilizing the example of Gaucher disease. The proposed study design features include: double-blind, controlled, randomized, multi-center, multi-arm, multi-company noninferiority or superiority trial to evaluate the efficacy and safety of product A, B, C…
Other innovative approaches found in the FDA guideline are those related to the use of modeling and simulation to optimize pediatric studies, as for example to predict the effect of a drug in children based on previously known performance in adults, particularly to inform the dosing rationale.
Small frequency of the disease or the outcome under study should never be an excuse for the weaknesses of a study design. As we were taught when studying Epidemiology, if you don’t have enough cases in your center, then you should try a multi-center study. Now, the next frontier is, not only multi-center studies, but multi-company studies.
The pharmacovigilance paradigm is changing and evolving very fast, keeping up with all the new developments in artificial intelligence (AI), the analysis of real world data to obtain real world evidence, and the multiple, really diverse sources of safety information that are available today. According to the authors:
Artificial intelligence will facilitate what the pharmacovigilance ecosystem lacks today – coordinated and efficient systems for developing actionable evidence on safety and effectiveness
The field of artificial intelligence is evolving so rapidly, that I’m convinced we will pretty soon face the paradox of needing AI help for human intelligence to understand what AI is delivering.
To me, the most important point of this paper relies on the subtle comparison between what I would call the ‘old’ pharmacovigilance, which is reactive and non-anticipatory, and the ‘new’ pharmacovigilance, which is proactive in continuously evaluating the benefit-risk profile of a product, elaborating predictive models giving place to predictive pharmacovigilance.
I cannot finish my review without mentioning the most interesting and intriguing section of the paper “Inventing the Pharmacovigilance Future“. In this section, the authors present brilliant ideas they very probably can help to put into practice. I would like to highlight their suggestion of “an international effort under the tripartite chairmanship of the WHO, the ICH, and the CIOMS, to investigate, debate and develop prototype programs for drugs approved via expedited review pathways, based on more sensitive premarket metrics of risk pontential”. And the last, and most intriguing of the concepts presented in this paper, is the Real World Pharmacovigilance Score (RWPS), a baseline prediction of likely adverse events based on projected volume and specific clinical use. Many questions I have about RWPS are not responded in the paper: how is it calculated, do you have any example of application in ‘real world’? I wish they will publish a paper on this matter.
I recommend you to read the essay, eye opening and intellectually challenging.
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