title: Bridging the gap: need for a data repository to support vaccine prioritization efforts.
abstract: As the mechanisms for discovery, development, and delivery of new vaccines become increasingly complex, strategic planning and priority setting have become ever more crucial. Traditional single value metrics such as disease burden or cost-effectiveness no longer suffice to rank vaccine candidates for development. The Institute of Medicine-in collaboration with the National Academy of Engineering-has developed a novel software system to support vaccine prioritization efforts. The Strategic Multi-Attribute Ranking Tool for Vaccines-SMART Vaccines-allows decision makers to specify their own value structure, selecting from among 28 pre-defined and up to 7 user-defined attributes relevant to the ranking of vaccine candidates. Widespread use of SMART Vaccines will require compilation of a comprehensive data repository for numerous relevant populations-including their demographics, disease burdens and associated treatment costs, as well as characterizing performance features of potential or existing vaccines that might be created, improved, or deployed. While the software contains preloaded data for a modest number of populations, a large gap exists between the existing data and a comprehensive data repository necessary to make full use of SMART Vaccines. While some of these data exist in disparate sources and forms, constructing a data repository will require much new coordination and focus. Finding strategies to bridge the gap to a comprehensive data repository remains the most important task in bringing SMART Vaccines to full fruition, and to support strategic vaccine prioritization efforts in general.
authors.affiliation: Institute of Medicine, National Academy of Sciences, Washington, DC, United States. Electronic address: gmadhavan@nas.edu.
authors.forename: Guruprasad
authors.initials: G
authors.lastname: Madhavan
authors.affiliation: University of Rochester, Rochester, NY, United States.
authors.forename: Charles
authors.initials: C
authors.lastname: Phelps
authors.affiliation: Institute of Medicine, National Academy of Sciences, Washington, DC, United States.
authors.forename: Kinpritma
authors.initials: K
authors.lastname: Sangha
authors.affiliation: Johns Hopkins University School of Medicine, Baltimore, MD, United States.
authors.forename: Scott
authors.initials: S
authors.lastname: Levin
authors.affiliation: Novartis Vaccines and Diagnostics, Siena, Italy.
authors.forename: Rino
authors.initials: R
authors.lastname: Rappuoli
mesh_terms: D000818:Animals; D003141:Communicable Diseases / Q000453:epidemiology*; D016208:Databases, Factual; D003661:Decision Support Techniques; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D012984:Software; D014481:United States; D014612:Vaccines / Q000276:immunology* / Q000302:isolation & purification*
chemical_list: D014612:Vaccines
keywords: Decision making; Disease burden; Population data; Priority setting; Software tool; Vaccine development