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来源类型Working Paper
规范类型报告
DOI10.3386/w30126
来源IDWorking Paper 30126
Accelerating Vaccine Innovation for Emerging Infectious Diseases via Parallel Discovery
Joseph Barberio; Jacob Becraft; Zied Ben Chaouch; Dimitris Bertsimas; Tasuku Kitada; Michael Lingzhi Li; Andrew W. Lo; Kevin Shi; Qingyang Xu
发表日期2022-06-13
出版年2022
语种英语
摘要We analyze the financial performance of a hypothetical portfolio of 120 mRNA vaccine candidates in the preclinical stage targeting 11 emerging infectious diseases. We calibrate the simulation parameters with input from domain experts in mRNA technology and an extensive literature review. We find that the portfolio generates an average annualized return on investment of –6.0% per annum and a net present value of –$9.5 billion, despite the scientific advantages of mRNA technology and the financial benefits of diversification. Clinical trial costs account for 94% of the total investment, with manufacturing costs accounting for only 6%. Sensitivity analysis reveals that the most important factor determining financial performance is the price per dose, while the increased probability of success due to mRNA technology, adjusting the size of the portfolio, and the possibility of conducting human challenge trials do not significantly improve financial performance. These results underscore that if the goal is to create a sustainable business model and robust global vaccine ecosystem, continued collaboration between government agencies and the private sector is likely to be necessary.
主题Financial Economics ; Portfolio Selection and Asset Pricing ; Financial Markets ; Financial Institutions ; Corporate Finance ; Public Economics ; Taxation ; Public Goods ; National Fiscal Issues ; Subnational Fiscal Issues ; Health, Education, and Welfare ; Health ; COVID-19
URLhttps://www.nber.org/papers/w30126
来源智库National Bureau of Economic Research (United States)
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条目标识符http://119.78.100.153/handle/2XGU8XDN/587798
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Joseph Barberio,Jacob Becraft,Zied Ben Chaouch,et al. Accelerating Vaccine Innovation for Emerging Infectious Diseases via Parallel Discovery. 2022.
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