What is the biggest change that you are seeing in pharma's drug safety strategies at the moment?
The new EU PV legislation brings (amongst other challenges) the task to constantly evaluate the real-world benefit-risk balance of a drug, meaning that pharma will have to evaluate their risk management strategies based on the real world use of their drugs, including off-label uses outside of the labelled indications and/or outside the intended patient populations. This will require a much more pro-active approach to risk management (or actually: benefit-risk management), processes will have to be adapted and key audiences inside and outside the companies will have to understand the different needs. The second big change that will have to be implemented is the need to appropriately evaluate the effectiveness of risk management activities; based on discussions with colleagues from the industry and regulatory authorities, I am not convinced that we (collectively) have a good idea on how to best achieve this, how to integrate this activity in safety RM, and how to plan for actions that follow the evaluations.
What are the key challenges that pharma faces in effective benefit/risk communication?
Benefit and Risk mean different things to different audiences and decision making on the personal BR balance is a process that ultimately every patient has to perform (with the aid of their physician and – in some cases – their families or other affected persons). Pharma has to work with regulators and payers on a framework to communicate the BR balance in a non-paternalistic way to patients to enable them to make their own decision on whether or not they are willing to accept the risks that come with the benefits of a particular drug. For that purpose, we have to provide them with unbiased, yet interpreted data that are comprehensible in the same way as a PIL. The biggest challenge there is to overcome the functional innumeracy of a large proportion of the general populace that exceeds functional illiteracy by far, i.e., finding representations of numbers and probabilities that are intuitively comprehensible for non-statisticians. Naturally, these types of data representation must be agreeable to regulators as well and must be designed in a way to minimize the risk of liability litigation.
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