HEALTH TECHNOLOGY ASSESSMENTS FOR PERSONALISED MEDICINES- ARE CURRENT METHODOLOGIES SUITABLE FOR THE ASSESSMENT OF PERSONALISED THERAPIES?
Author(s)
Lauks S1, Gee A1, Wilson LE2
1Quintiles Consulting, Reading, UK, 2Quintiles, Reading, UK
Presentation Documents
Objective: An increased drive towards personalised healthcare and medicine by policy-makers, alongside technological advances in medicines and diagnostics, is leading to more personalised medicines coming to market. Given that personalised medicines differ from traditional medicines in their development, use and cost, previously published articles have stated that current health technology assessments (HTA) methodologies are not designed to appropriately evaluate these technologies. This research was conducted to provide insights on methods for evaluating personalised medicines and what modifications to current HTA processes would be needed to ensure robust and timely assessment. Methods: Qualitative interviews were conducted with five experts in personalised medicine and market access across the UK, US and Germany to discuss the movement towards and benefits of personalised medicines as well as the key metrics on which they should be evaluated. These insights, supported with secondary research, were used to provide suggestions on the structure and methodology of personalised medicine assessments and how current assessment processes would need to be altered to accommodate these unique technologies. Results: The key areas where personalised medicines would need special consideration in HTAs identified were: - Study design: population size, geography, ethnicity - Companion diagnostics: cost, logistics - Unmet need: individualised view of perceived benefit - Cost effectiveness: costs and outcomes of therapy and companion diagnostic, reduction in overall healthcare costs Conculsion: The key areas identified are discussed in further detail, specifically, as to how they could be incorporated into current HTA models to effectively assess personalised medicines and how they would influence the decision-making process.
Conference/Value in Health Info
2014-11, ISPOR Europe 2014, Amsterdam, The Netherlands
Value in Health, Vol. 17, No. 7 (November 2014)
Code
PRM248
Topic
Methodological & Statistical Research
Topic Subcategory
Confounding, Selection Bias Correction, Causal Inference
Disease
Multiple Diseases, Rare and Orphan Diseases