Meredith Y Smith1,2, Janine van Til3, Rachael L DiSantostefano4, A Brett Hauber5,6, Kevin Marsh7. 1. Alexion Pharmaceuticals, Inc., 121 Seaport Boulevard, Boston, MA, 02210, USA. meredith.smith@alexion.com. 2. Department of Regulatory and Quality Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA, 90089, USA. meredith.smith@alexion.com. 3. University of Twente, Enschede, Netherlands. 4. Janssen R&D, LLC., Titusville, NJ, USA. 5. RTI-Health Solutions, Research Triangle Park, NC, USA. 6. CHOICE Institute, University of Washington School of Pharmacy, Seattle, WA, USA. 7. Evidera, London, UK.
Abstract
BACKGROUND: Benefit-risk assessments for medicinal products and devices have advanced significantly over the past decade. The purpose of this study was to characterize the extent to which the life sciences industry is utilizing quantitative benefit-risk assessment (qBRA) methods. METHODS: Semi-structured interviews were conducted with a sample of industry professionals working in drug and/or medical device benefit-risk assessments (n = 20). Questions focused on the use, timing, and impact of qBRA; implementation challenges; and future plans. Interviews were recorded, transcribed, and coded for thematic analysis. RESULTS: While most surveyed companies had applied qBRA, application was limited to a small number of assets-primarily to support internal decision-making and regulatory submissions. Positive impacts associated with use included improved team decision-making and communication. Multi-criteria decision analysis and discrete choice experiment were the most frequently utilized qBRA methods. A key challenge of qBRA use was the lack of clarity regarding its value proposition. Championing by senior company leadership and receptivity of regulators to such analyses were cited as important catalysts for successful adoption of qBRA. Investment in qBRA methods, via capability building and pilot studies, was also under way in some instances. CONCLUSION: qBRA application within this sample of life sciences companies was widespread, but concentrated in a small fraction of assets. Its use was primarily for internal decision-making or regulatory submissions. While some companies had plans to build further capacity in this area, others were waiting for further regulatory guidance before doing so.
BACKGROUND: Benefit-risk assessments for medicinal products and devices have advanced significantly over the past decade. The purpose of this study was to characterize the extent to which the life sciences industry is utilizing quantitative benefit-risk assessment (qBRA) methods. METHODS: Semi-structured interviews were conducted with a sample of industry professionals working in drug and/or medical device benefit-risk assessments (n = 20). Questions focused on the use, timing, and impact of qBRA; implementation challenges; and future plans. Interviews were recorded, transcribed, and coded for thematic analysis. RESULTS: While most surveyed companies had applied qBRA, application was limited to a small number of assets-primarily to support internal decision-making and regulatory submissions. Positive impacts associated with use included improved team decision-making and communication. Multi-criteria decision analysis and discrete choice experiment were the most frequently utilized qBRA methods. A key challenge of qBRA use was the lack of clarity regarding its value proposition. Championing by senior company leadership and receptivity of regulators to such analyses were cited as important catalysts for successful adoption of qBRA. Investment in qBRA methods, via capability building and pilot studies, was also under way in some instances. CONCLUSION:qBRA application within this sample of life sciences companies was widespread, but concentrated in a small fraction of assets. Its use was primarily for internal decision-making or regulatory submissions. While some companies had plans to build further capacity in this area, others were waiting for further regulatory guidance before doing so.
Authors: Martin P Ho; Juan Marcos Gonzalez; Herbert P Lerner; Carolyn Y Neuland; Joyce M Whang; Michelle McMurry-Heath; A Brett Hauber; Telba Irony Journal: Surg Endosc Date: 2015-01-01 Impact factor: 4.584
Authors: Chiara Whichello; Karin Schölin Bywall; Jonathan Mauer; Watt Stephen; Irina Cleemput; Cathy Anne Pinto; Eline van Overbeeke; Isabelle Huys; Esther W de Bekker-Grob; Richard Hermann; Jorien Veldwijk Journal: Health Policy Date: 2020-07-30 Impact factor: 2.980
Authors: Kevin Marsh; Janine A van Til; Elizabeth Molsen-David; Christine Juhnke; Natalia Hawken; Elisabeth M Oehrlein; Y Christy Choi; Alejandra Duenas; Wolfgang Greiner; Kara Haas; Mickael Hiligsmann; Kimberley S Hockley; Ilya Ivlev; Frank Liu; Jan Ostermann; Thomas Poder; Jiat L Poon; Axel Muehlbacher Journal: Value Health Date: 2020-07-05 Impact factor: 5.725