Structured Benefit–Risk Assessment of Medicinal Products

This self-paced course will provide an understanding of current techniques, opportunities and challenges of structured benefit risk assessment including different preference elicitation techniques.

The evaluation of the benefit–risk balance is a key element across the entire life cycle of a medicinal product. Intuitive, implicit benefit–risk assessment methods have evolved towards more structured approaches. A structured benefit–risk assessment aims at providing a transparent assessment of the benefit–risk profile of medicinal products by making explicit the underlying assumptions and value trade-offs. Several quantitative and semi-quantitative methodologies have been developed and utilized to complement descriptive or qualitative frameworks in order to facilitate the structured evaluation of the benefit–risk profile of medicinal products.

Although combining key benefits and risks into a single metric have historically only been conducted for the “average” patient, such aggregate assessments may also provide helpful information on the level of an individual patient. Furthermore, there is an increasing interest on the use of real‐world data to substantiate benefit–risk assessment and support a more patient-centered approach and the value of a new treatment options in daily practice. The course is therefore intended for anyone who wishes to extend their knowledge on structured benefit risk assessment with a specific focus on multi-criteria decision analysis, from prescribing physicians to industry, regulatory and other professionals.

The course consists of three self-paced learning units, starting with an introduction to benefit-risk, followed by learning units on decision making styles and multiple-criteria decision analysis. After the course, participants are asked to complete a final assignment, in which they will conduct a benefit-risk assessment. The course takes on average 20 hours to complete.

An overview of the learning units of this course:

Introduction to Benefit-Risk Assessment
Decision Making Styles
Multiple-criteria Decision Analysis
Final Assignment

Quick Overview

Available now

icon 20 hours on average

icon Advanced level

icon No limit on participants

icon English

icon Self-paced, online course

icon Certificate of completion

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Course Fees

Standard

€1100

Government, university and non-profit Fee

€550

Member of the GetReal Institute: 25% discount on the fees
Group: 10% discount on the fees for the enrollment of 4 participants for non-GetReal Institute members

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Learning Objectives

This course consists of different learning units, each with different learning objectives.

At the end of the learning unit on ‘decision making styles’ you will be able to:

Familiarize with structured decision making
Select and structure criteria for an effects table
Describe how patient perspectives are incorporated in regulatory decision making.
Design an effects table
Recognize the different steps in a decision aiding process by means of a structured benefit-risk assessment
Describe what factors are involved in benefit-risk comparison

At the end of the learning unit on ‘multiple-criteria decision analysis’ you will be able to:

Describe how complex decision problems can be addressed and resolved through the specification of value trade-offs.
Describe and interpret the two components of the additive value model (i.e., the weights and the partial value functions).
Describe how clinical data on efficacy and safety can be combined with an elicited value function to perform a quantitative benefit-risk assessment (qBRA)
Describe how stochastic multi-criteria acceptability analysis can be applied to account for uncertainty in the data and imprecision in the preferences

For Whom?

• Participants distributed over the whole medicine development chain: from academic researchers to prescribing physicians, industry, regulatory and other professionals.
• No diplomas are required for enrollment, but the course is aimed at participants who have an advanced level of understanding of benefit-risk in drug development. Familiarity with regulatory science and medicines development is recommended.
• The course will be taught in English. To successfully participate, sufficient proficiency in English reading and writing is required.

Learning Methods

Interactive online learning via the platform of Elevate Health
This self-paced online course is available through Elevate Health’s Virtual Learning Environment. Participants will learn from key experts of the GetReal Academy through web lectures, case studies, individual assignments and self-tests.

The course has no set start date and the workload is estimated to be approximately 20 hours. Participants can study at their own pace and convenience and are not required to attend the course at specific times.

Advantages of an online course
• Flexibility and efficiency: there is no need to travel to attend a lecture, spend your time very efficiently.
• Personalised learning: study at your own pace and choose which form of guidance works best.
• Personal feedback on your final assignment from two experts.

Learning tools
This course consists of web lectures, case assignments, self-tests, reading assignments and stimulating questions.

Deadlines and Certificates

There are no set deadlines in this course.

At the end of the course, participants are asked to complete a final assignment, in which participants will conduct a benefit-risk assessment. To pass the final assignment, participants need a score of 5.5/10 or higher. The final assignment will be graded by the course staff at set times in the year.

The final assignment consist of three steps:
• Evaluate the literature and select the favourable and unfavourable effects to include in your effects table
• Enter the effects table into ADDIS MCDA and use the system to perform a quantitative Benefit-risk assessment
• Write an assessment report according to the template provided and prepare a short presentation

Participants will receive a certificate upon completion of all required learning activities and a score of 5.5 or higher on the final assignment. Access to the course in the online learning environment will be granted for up to 1 year after enrolment into the course.

CME accreditation for this course is currently under request.

Course Staff

Hans Hillege

UMC Groningen

Hans Hillege is a professor in Cardiology and his educational records includes Master’s degrees in Medicine and Epidemiology and a PhD from the University of Groningen. Currently he is an acting member of the European Committee of Human Medicinal Products (CHMP) on behalf of the Netherlands. His fields of specialization and research include cardiovascular epidemiology and the impact of extracardiac comorbidities with specific interest in the coexistence of cardiovascular and kidney disease, epidemiological models, clinical trials, evidence based medicine, regulatory science, medical decision-making and health information technology. He has supervised more than 25 PhD projects and authored/co-authored more than 400 international scientific publications and book chapters.
Douwe Postmus

UMC Groningen

Dr Douwe Postmus is employed as an assistant professor at the Department of Epidemiology of the University Medical Center Groningen, The Netherlands. He has a MSc degree in Operations Research and a PhD degree in Business Administration. His research is concerned with the application of mathematical methods to support the medical decision making at the micro and macro levels. His primary research interests include the application of multi-criteria decision analysis to the benefit-risk evaluation of medicines and the development and application of methods for eliciting patient preferences. Between September 2014 – June 2015 and June 2016 – March 2017, Dr Postmus worked as a National Expert on Secondment at the European Medicines Agency to participate in the Agency’s benefit-risk methodology project and to contribute to the design and conduct of two patient preference studies. In addition to his research, he teaches research methodology and medical statistics to dentistry students. He is (co-)author of over 50 papers in peer reviewed journals.