Pipeline analysis of a vaccine candidate portfolio for diseases of poverty using the Portfolio-To-Impact modelling tool.

Journal Article (Journal Article)

Background: The Portfolio-To-Impact (P2I) P2I model is a recently developed product portfolio tool that enables users to estimate the funding needs to move a portfolio of candidate health products, such as vaccines and drugs, along the product development path from late stage preclinical to phase III clinical trials, as well as potential product launches over time. In this study we describe the use of this tool for analysing the vaccine portfolio of the European Vaccine Initiative (EVI). This portfolio includes vaccine candidates for various diseases of poverty and emerging infectious diseases at different stages of development. Methods: Portfolio analyses were conducted using the existing assumptions integrated in the P2I tool, as well as modified assumptions for costs, cycle times, and probabilities of success based on EVI's own internal data related to vaccine development. Results: According to the P2I tool, the total estimated cost to move the 18 candidates currently in the EVI portfolio along the pipeline to launch would be about US $470 million, and there would be 0.69 expected launches across all six diseases in EVI's portfolio combined during the period 2019-2031. Running of the model using EVI-internal parameters resulted in a significant increase in the expected product launches. Conclusions: Not all the assumptions underlying the P2I tool could be tested in our study due to limited amount of data available. Nevertheless, we expect that the accelerated clinical testing of vaccines (and drugs) based on the use of controlled human infection models that are increasingly available, as well as the accelerated approval by regulatory authorities that exists for example for serious conditions, will speed up product development and result in significant cost reduction. Project findings as well as potential future modifications of the P2I tool are discussed with the aim to improve the underlying methodology of the P2I model.

Full Text

Duke Authors

Cited Authors

  • Gunn, A; Bandara, S; Yamey, G; D Alessio, F; Depraetere, H; Houard, S; Viebig, NK; Jungbluth, S

Published Date

  • January 2019

Published In

Volume / Issue

  • 8 /

Start / End Page

  • 1066 -

PubMed ID

  • 32148758

Pubmed Central ID

  • PMC7043114

Electronic International Standard Serial Number (EISSN)

  • 2046-1402

International Standard Serial Number (ISSN)

  • 2046-1402

Digital Object Identifier (DOI)

  • 10.12688/f1000research.19810.2


  • eng