Antibiotic research and development: business as usual?

This article contends that poor economic incentives are an important reason for the lack of new drugs and explains how the DRIVE-AB intends to change the landscape by harnessing the expertise, motivation and diversity of its partner

Prioritization models for vaccine development against emerging infections

Vaccine development is essential in efforts to avert and respond to emerging epidemics. The dissertation develops and applies a framework for prioritizing investments in vaccine development against emerging infectious diseases in global funding organizations. The Coalition for Epidemic Preparedness and Innovations (CEPI) is used as a case study. The purpose is to develop prioritization models that consistently link the organization's strategic goals with vaccine development investment decisions under uncertainty and stakeholder heterogeneity. The analysis uses a combination of stakeholder engagement and preference elicitation techniques to identify appropriate strategic objectives in the case organization. A simulation-optimization model is used to estimate the optimal level of investment required to develop vaccines against 11 priority diseases. Multi-criteria decision analysis and operations research methods are employed to support the optimal selection of vaccine development projects for investment against various emerging infectious diseases. There are three key findings in the dissertation. First, the dissertation provides new empirical evidence on emerging infectious disease vaccine development objectives, costs, risks and preferences for investment. Second, the dissertation demonstrates how prioritization models can be developed that are suitable for different investment decision contexts, but which at the same time remain consistent with the organization's overarching strategic goals. Third, the dissertation illustrates how this framework can be applied to support investment decisions in real-life settings, adapting models to practical limitations while maintaining consistency with theoretical foundations. These findings are important as new global governance structures for contingency and response, such as CEPI, are still in the making. For such organizations, the framework developed in this dissertation can contribute to better decisions for global health

Prioritizing investments in rapid response vaccine technologies for emerging infections: A portfolio decision analysis.

This study reports on the application of a Portfolio Decision Analysis (PDA) to support investment decisions of a non-profit funder of vaccine technology platform development for rapid response to emerging infections. A value framework was constructed via document reviews and stakeholder consultations. Probability of Success (PoS) data was obtained for 16 platform projects through expert assessments and stakeholder portfolio preferences via a Discrete Choice Experiment (DCE). The structure of preferences and the uncertainties in project PoS suggested a non-linear, stochastic value maximization problem. A simulation-optimization algorithm was employed, identifying optimal portfolios under different budget constraints. Stochastic dominance of the optimization solution was tested via mean-variance and mean-Gini statistics, and its robustness via rank probability analysis in a Monte Carlo simulation. Project PoS estimates were low and substantially overlapping. The DCE identified decreasing rates of return to investing in single platform types. Optimal portfolio solutions reflected this non-linearity of platform preferences along an efficiency frontier and diverged from a model simply ranking projects by PoS-to-Cost, despite significant revisions to project PoS estimates during the review process in relation to the conduct of the DCE. Large confidence intervals associated with optimization solutions suggested significant uncertainty in portfolio valuations. Mean-variance and Mean-Gini tests suggested optimal portfolios with higher expected values were also accompanied by higher risks of not achieving those values despite stochastic dominance of the optimal portfolio solution under the decision maker's budget constraint. This portfolio was also the highest ranked portfolio in the simulation; though having only a 54% probability of being preferred to the second-ranked portfolio. The analysis illustrates how optimization modelling can help health R&D decision makers identify optimal portfolios in the face of significant decision uncertainty involving portfolio trade-offs. However, in light of such extreme uncertainty, further due diligence and ongoing updating of performance is needed on highly risky projects as well as data on decision makers' portfolio risk attitude before PDA can conclude about optimal and robust solutions

Setting strategic objectives for the coalition for epidemic preparedness innovations: An exploratory decision analysis process

The Coalition for Epidemic Preparedness Innovations (CEPI) was established in 2016 in response to the West African Ebola epidemic. The vision for CEPI is to develop vaccines to prevent future emerging infectious disease outbreaks from becoming humanitarian crises. Leaders from governments, foundations, industry, and civil society convened earlier that year to formulate strategic objectives to support CEPI’s first business plan. We demonstrate how decision analysis can support a rational and transparent approach to strategy formulation that accounts for and ranks the preferences of multiple stakeholders in an international coalition setting. We use value-focused thinking to identify and structure objectives and we combine this with an explorative discrete-choice experiment to elicit preferences between objectives. Our findings suggest that decision-analytic methodologies can rationalize strategic objective setting in a highly complex global health research and development planning context characterized by strong stakeholder interests and conflicting priorities

Setting strategic objectives for the coalition for epidemic preparedness innovations: An exploratory decision analysis process

The Coalition for Epidemic Preparedness Innovations (CEPI) was established in 2016 in response to the West African Ebola epidemic. The vision for CEPI is to develop vaccines to prevent future emerging infectious disease outbreaks from becoming humanitarian crises. Leaders from governments, foundations, industry, and civil society convened earlier that year to formulate strategic objectives to support CEPI’s first business plan. We demonstrate how decision analysis can support a rational and transparent approach to strategy formulation that accounts for and ranks the preferences of multiple stakeholders in an international coalition setting. We use value-focused thinking to identify and structure objectives and we combine this with an explorative discrete-choice experiment to elicit preferences between objectives. Our findings suggest that decision-analytic methodologies can rationalize strategic objective setting in a highly complex global health research and development planning context characterized by strong stakeholder interests and conflicting priorities

Estimating the cost of vaccine development against epidemic infectious diseases: a cost minimisation study

Background The Coalition for Epidemic Preparedness Innovations was established in 2016, to develop vaccines that can contribute to preparedness for outbreaks of epidemic infectious diseases. Evidence on vaccine development costs for such diseases is scarce. Our goal was to estimate the minimum cost for achieving vaccine research and development preparedness targets in a portfolio of 11 epidemic infectious diseases, accounting for vaccine pipeline constraints and uncertainty in research and development preparedness outcomes. Methods We assembled a pipeline of 224 vaccine candidates from preclinical through to phase 2 for 11 priority epidemic infectious diseases. We used a linear regression model to identify drivers of development costs from preclinical through to end of phase 2a. Drawing from published estimates of vaccine research and development probabilities of success, we simulated costs for advancing these 224 vaccine candidates through to the end of phase 2a. We combined these findings to determine minimum costs for progressing at least one vaccine through to the end of phase 2a per epidemic infectious disease by means of a stochastic optimisation model. Findings The cost of developing a single epidemic infectious disease vaccine from preclinical trials through to end of phase 2a is US$31–68 million (US$14–159 million range), assuming no risk of failure. We found that previous licensure experience and indirect costs are upward drivers of research and development costs. Accounting for probability of success, the average cost of successfully advancing at least one epidemic infectious disease vaccine through to the end of phase 2a can vary from US$84–112 million ($23 million–$295 million range) starting from phase 2 to$319–469 million ($137 million–$1·1 billion range) starting from preclinical. This cost includes the cumulative cost of failed vaccine candidates through the research and development process. Assuming these candidates and funding were made available, progressing at least one vaccine through to the end of phase 2a for each of the 11 epidemic infectious diseases would cost a minimum of $2·8–3·7 billion ($1·2 billion–$8·4 billion range). Interpretation Our analysis provides new evidence on vaccine research and development pipelines and associated costs for 11 epidemic infectious diseases, highlighting both funding needs and research and development gaps for achieving vaccine research and development preparedness targets. Funding This work was partly supported by the Research Council of Norway through the Global Health and Vaccination Programme GLOBVAC.publishedVersion© 2018 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND 4.0 license

Estimating the cost of vaccine development against epidemic infectious diseases: a cost minimisation study

Summary: Background: The Coalition for Epidemic Preparedness Innovations was established in 2016, to develop vaccines that can contribute to preparedness for outbreaks of epidemic infectious diseases. Evidence on vaccine development costs for such diseases is scarce. Our goal was to estimate the minimum cost for achieving vaccine research and development preparedness targets in a portfolio of 11 epidemic infectious diseases, accounting for vaccine pipeline constraints and uncertainty in research and development preparedness outcomes. Methods: We assembled a pipeline of 224 vaccine candidates from preclinical through to phase 2 for 11 priority epidemic infectious diseases. We used a linear regression model to identify drivers of development costs from preclinical through to end of phase 2a. Drawing from published estimates of vaccine research and development probabilities of success, we simulated costs for advancing these 224 vaccine candidates through to the end of phase 2a. We combined these findings to determine minimum costs for progressing at least one vaccine through to the end of phase 2a per epidemic infectious disease by means of a stochastic optimisation model. Findings: The cost of developing a single epidemic infectious disease vaccine from preclinical trials through to end of phase 2a is US$31–68 million (US$14–159 million range), assuming no risk of failure. We found that previous licensure experience and indirect costs are upward drivers of research and development costs. Accounting for probability of success, the average cost of successfully advancing at least one epidemic infectious disease vaccine through to the end of phase 2a can vary from US$84–112 million ($23 million–$295 million range) starting from phase 2 to$319–469 million ($137 million–$1·1 billion range) starting from preclinical. This cost includes the cumulative cost of failed vaccine candidates through the research and development process. Assuming these candidates and funding were made available, progressing at least one vaccine through to the end of phase 2a for each of the 11 epidemic infectious diseases would cost a minimum of $2·8–3·7 billion ($1·2 billion–$8·4 billion range). Interpretation: Our analysis provides new evidence on vaccine research and development pipelines and associated costs for 11 epidemic infectious diseases, highlighting both funding needs and research and development gaps for achieving vaccine research and development preparedness targets. Funding: This work was partly supported by the Research Council of Norway through the Global Health and Vaccination Programme GLOBVAC