The purpose of medicines is to improve patients' lives. Stakeholders involved in the development and lifecycle management of medicines agree that more effective patient involvement is needed to ensure that patient needs and priorities are identified and met. Despite the increasing number and scope of patient involvement initiatives, there is no accepted master framework for systematic patient involvement in industry-led medicines research and development, regulatory review, or market access decisions. Patient engagement is very productive in some indications, but inconsistent and fragmentary on a broader level. This often results in inefficient drug development, increasing evidence requirements, lack of patient-centered outcomes that address unmet medical needs and facilitate adherence, and consequently, lack of required therapeutic options and high costs to society and involved parties. Improved patient involvement can drive the development of innovative medicines that deliver more relevant and impactful patient outcomes and make medicine development faster, more efficient, and more productive. It can lead to better prioritization of early research; improved resource allocation; improved trial protocol designs that better reflect patient needs; and, by addressing potential barriers to patient participation, enhanced recruitment and retention. It may also improve trial conduct and lead to more focused, economically viable clinical trials. At launch and beyond, systematic patient involvement can also improve the ongoing benefit-risk assessment, ensure that public funds prioritize medicines of value to patients, and further the development of the medicine. Progress toward a universal framework for patient involvement requires a joint, precompetitive, and international approach by all stakeholders, working in true partnership to consolidate outputs from existing initiatives, identify gaps, and develop a comprehensive framework. It is essential that all stakeholders participate to drive adoption and implementation of the framework and to ensure that patients and their needs are embedded at the heart of medicines development and lifecycle management.
Word count: 3,668 without Acknowledgements or 4,089 with Acknowledgements Key messages Formal and transparent discussion of multiple viewpoints, interests and priorities facilitates mutual understanding of complex decision problems Benefit-risk assessments of treatments should be undertaken in a structured way so that it is clear how a decision on the overall balance of a treatment's effects has been reached Various structured approaches and singular methodologies/visual representations are available to support benefit-risk assessment of medicines, but so far universal agreement as to the most suitable method for structured benefit-risk assessment has been lacking A team combining expertise from public and private institutions carried out a review of benefit-risk methods and visual representations, including application of the tools to case studies based on real regulatory scenarios The project produced a clear set of practical recommendations for undertaking benefit-risk assessments, organised around a generic, five stage benefit-risk assessment roadmap /2007-2013) and EFPIA companies' in kind contribution.The processes described and conclusions drawn from the work presented herein relate solely to the testing of methodologies and representations for the evaluation of benefit and risk of medicines. This report neither replaces nor is intended to replace or comment on any regulatory decisions made by national regulatory agencies, nor the European Medicines Agency.The authors declare the following conflicts of interest: Dr Hughes has been employed by Pfizer Inc. for the duration of the project. Mr Downey reports that he is an employee of Amgen, a participant in the Innovative Medicines Initiative, which is a public-private partnership. The manuscript describes testing benefit-risk methodologies and visualizations using case studies of marketed products. No Amgen treatments were used in the work associated with this publication. Dr Juhaeri is an employee of Sanofi, the producer of rimonabant and telithromycin, which were used in the PROTECT project as case studies. Dr Juhaeri declares that he is an employee or Sanofi, the manufacturer of rimonabant which was studied in this project. Mr Lieftucht reports that he is an employee of GlaxoSmithKline, a participant in the Innovative Medicines Initiative, which is a public-private partnership. One of the case studies described in the manuscript is a GSK product but Mr Lieftucht did not work on that case study. Dr Metcalf reports that she is an employee of GlaxoSmithKline, a participant in the Innovative Medicines Initiative, which is a publicprivate partnership. One of the case studies described in the manuscript is a GSK product but Dr Metcalf did not work on that case study. To draw on the practical experience from the PROTECT BR case studies and make recommendations regarding the application of a number of methodologies and visual representations for benefit-risk assessment. MethodsEight case studies based on the benefit-risk balance of real medicines were ...
Benefit-risk assessment is the foundation for decision making throughout the life cycle of medical products. Because patients are the beneficiaries of the efficacy of medical treatments and also bear their possible risks, their perspectives and judgments about value and the relative importance of benefits and risks should be at the heart of the medical decision-making process. Patient engagement is now at a tipping point; there have been a growing number of patient engagement initiatives over the past several years, but there remains the need for a common language, alignment on engagement approaches and best practices, and a shared vision regarding a desired future state. This article discusses insights gleaned from the DIA conference, ''Patient Engagement in Benefit-Risk Assessment throughout the Life Cycle of Medical Products'' (September 2015). It highlights the changes that will need to occur within the patient, medical-product sponsor, and regulatory cultures in order for patient engagement to become integrated into the medical-product development process and life cycle maintenance. Furthermore, it emphasizes that reaching the desired future state will require a conscious commitment from all stakeholders to work collaboratively to develop shared solutions and to map a common path forward.
Purpose Difficulties may be encountered when undertaking a benefit–risk assessment for an older product with well‐established use but with a benefit–risk balance that may have changed over time. This case study investigates this specific situation by applying a formal benefit–risk framework to assess the benefit–risk balance of warfarin for primary prevention of patients with atrial fibrillation. Methods We used the qualitative framework BRAT as the starting point of the benefit–risk analysis, bringing together the relevant available evidence. We explored the use of a quantitative method (stochastic multi‐criteria acceptability analysis) to demonstrate how uncertainties and preferences on multiple criteria can be integrated into a single measure to reduce cognitive burden and increase transparency in decision making. Results Our benefit–risk model found that warfarin is favourable compared with placebo for the primary prevention of stroke in patients with atrial fibrillation. This favourable benefit–risk balance is fairly robust to differences in preferences. The probability of a favourable benefit–risk for warfarin against placebo is high (0.99) in our model despite the high uncertainty of randomised clinical trial data. In this case study, we identified major challenges related to the identification of relevant benefit–risk criteria and taking into account the diversity and quality of evidence available to inform the benefit–risk assessment. Conclusion The main challenges in applying formal methods for medical benefit–risk assessment for a marketed drug are related to outcome definitions and data availability. Data exist from many different sources (both randomised clinical trials and observational studies), and the variability in the studies is large. Copyright © 2014 John Wiley & Sons, Ltd.
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