Competition Regulation Innovation Dr. Marisa Miraldo m.miraldo@imperial.ac.uk Brussels, 27th October, 2016
Outline The R&D and innovation challenge Current incentives HTA assessment: (weak) incentive for innovation Towards a new framework 2
The challenges R&D is lengthy, multi-stage, costly and uncertain: 13,5 years R&D costs: US$1.87bn (2011 prices) 90% of drug candidates fail to succeed in the mid-stage of R&D process up to 13.6 new molecule entities required in Phase 1 for one successful NME Economic Impact: total drug bill across OECD countries is around 19% of total health spending Policy concerns: how to balance out innovation incentives with drug access policies? Sources: OECD (2011); Paul et al (2010); Mestre-Ferrandiz et al (2012) 3
What we need? Regulatory landscape that: balances out cost containment while creating incentives for innovation that addresses unmet need promotes innovation towards cure (breakthrough innovation) To achieve Decreased burden of disease Financial sustainable health systems Rewarding to innovators 4
35 30 25 20 15 10 5 0 Total, % of health spending, 2015 R&D Productivity 35 30 25 20 15 10 5 0 Total, % of health spending, 2015 RELATIVE NUMBER: FIRST-IN-CLASS & INCREMENTAL INNOVATION GLOBAL LAUNCHES OF NMES 1 st in class Incremental Sources: Fraser Institute, 2014 OECD (2016), Pharmaceutical spending (indicator). doi: 10.1787/998febf6-en (Accessed on 24 October 2016 FDA CDER, PhRMA and PricewaterhouseCoopers analysis 2005 2006 2007 2008 2009 2010 2012 Average per year 2012-2016 5
Is the current system adequate? Innovation & unmet need Sources: Catala-lopez et al (2010). Does the development of new medicinal products in the European Union address global and regional health concerns? Population Health Metrics Advancing innovation in health measurement20108:34 DOI: 10.1186/1478-7954-8-34 6
Is the current system adequate? 0.2.4.6.8 1 Mental and Behavioral disorders 1990 and 2010 0.2.4.6.8 1 cumulative share of DALYs (less needy first) conc curve 1990 conc curve 2010 line of equality Source: IHME GBD 1990-2010; author's analysis from IMS R&D Focus 7
Key questions 1. How to foster innovation? The role of market incentives - competition 2. How does the current regulatory landscape shape incentives? 3. The way forward? 8
Insights from economics - Schumpeter s hypotheses H1: Less competition (large market shares), more innovation large market shares: more certainty about recouping returns to R&D more profit to finance R&D expenditure H2: larger firms innovate more Large size implies diversification of R&D risks and ability to finance Empirical evidence H1 Amount of innovation H2: mixed Large firms are more likely to do R&D or be IP active But smaller firms that are R&D or IP active have higher intensities of such activity C* Competitive intensity (C) 9
In the pharmaceutical sector Aim: assess key drivers of success/failure across each stage of the R&D process 1980-2012 All ATCs, across all diseases Global, regional level analysis IMS R&D Focus (1980-2012) + World Bank data (GDP, population), ScripIntelligence and Fortune (firm level data) Market competition R&D competition Alliances 10
(some) findings Discovery Phase 1 Phase 2 Phase 3 Failure Market Competition R&D Competition Alliances Number of firms Pure Private Top 100 Success Key message: competition matters, market signals are important + Sector is heavily regulated: the number and type of drugs in the market shaped by HTA assessments HTA: strong signaling instrument & incentive mechanism! 11
How does the current regulatory landscape shape incentives? HTA & reimbursement incentives The consequences Weak strategic prioritization Inefficient reward system: Incremental effectiveness (vs. cure) Unmet need No incentives for breakthroughs No assessment of cost of innovation Static efficiency Cost effectiveness potential is momentary and reflects the transient conditions of each disease market Funding decision highly dependent on the timing of the appraisal Weak prediction of future cost effectiveness No tradeoff between current and future innovation Inefficiency: excessive reward for minor innovations limited rewards to breakthroughs Uncertainty into the development process Inefficient R&D resource allocation: over/under investing in specific disease areas Disruption of the innovation path? 12
Static vs. Dynamic Approach Innovation process HTA Long and dynamic: signals today impact future innovation Innovations incrementally build on one another: incentives today impact future innovation Cost containment considerations Focus on static efficiency Notion of development path overlooked Disregard of societal preferences towards future innovation Decision of not funding a drug might: Stop the innovation past (clinical effectiveness forgone for future generations) Misdirect investment towards what is deemed to be cost effective in the short run Short term (static) efficiency considerations may clash with the dynamic nature of innovation Static analysis can neither explain the occurrence of such productive revolutions nor the phenomena which accompany them Shumpeter, The Theory of Economic Development 1911 13
Towards a new dynamic framework Establish priorities for investment across diseases Assess societal preferences towards current and future innovations Measure the incremental dynamic value of a technology V " = IE " + Δu " IE * max we /0 L V " : dynamic value of incremental benefit of drug d IE " : incremental effectiveness brought by drug d Δu " : change in probability of achieving IE * max, i.e. cure or maximum risk reduction for disease D due to innovation d which is a function of the stock of knowledge and future R&D investment IE * max: maximum incremental effectiveness possible for disease D we /0 : priority weight attached to treating a particular disease D L: cost effectiveness threshold, possibly disease specific 14
Towards a New framework Rewarding breakthrough innovation Assessment of the gap to cure : higher wtp for cure? Relation between the gap and innovation costs Reward system if decreasing returns to R&D investment Maximizing value: new uses for old drugs Data analytics and value assessment Drug repurposing: promoting usage of drugs across different targets Conclusion Better incentives to foster innovation Acknowledge spillover effect of regulation on the dynamic R&D process Requires investment in linked global data, data analytics, new metrics of value Further collaboration between payers, innovators, practitioners 15
Thank you! m.miraldo@imperial.ac.uk https://www.linkedin.com/in/mmiraldo http://www.imperial.ac.uk/people/m.miraldo @mmiraldo