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Expanding antibiotic, vaccine, and diagnostics development and access to tackle antimicrobial resistance
Open accessAbstract
The increasing number of bacterial infections globally that do not respond to any available antibiotics indicates a need to invest in-and ensure access to-new antibiotics, vaccines, and diagnostics. The traditional model of drug development, which depends on substantial revenues to motivate investment, is no longer economically viable without push and pull incentives. Moreover, drugs developed through these mechanisms are unlikely to be affordable for all patients in need, particularly in low-income and middle-income countries. New, publicly funded models based on public-private partnerships could support investment in antibiotics and novel alternatives, and lower patients' out-of-pocket costs, making drugs more accessible. Cost reductions can be achieved with public goods, such as clinical trial networks and platform-based quality assurance, manufacturing, and product development support. Preserving antibiotic effectiveness relies on accurate and timely diagnosis; however scaling up diagnostics faces technological, economic, and behavioural challenges. New technologies appeared during the COVID-19 pandemic, but there is a need for a deeper understanding of market, physician, and consumer behaviour to improve the use of diagnostics in patient management. Ensuring sustainable access to antibiotics also requires infection prevention. Vaccines offer the potential to prevent infections from drug-resistant pathogens, but funding for vaccine development has been scarce in this context. The High-Level Meeting of the UN General Assembly in 2024 offers an opportunity to rethink how research and development can be reoriented to serve disease management, prevention, patient access, and antibiotic stewardship.
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Metadata
- Authors
- Laxminarayan, R., Impalli, I., Rangarajan, R., Cohn, J., Ramjeet, K., Trainor, B. W., Strathdee, S., Sumpradit, N., Berman, D., Wertheim, H., Outterson, K., Srikantiah, P., & Theuretzbacher, U.
- Affiliations
- Princeton University (US)
- Central Drug Research Institute (IN)
- Global Antibiotic Research & Development Partnership (CH)
- FIND (CH)
- Boston University (US)
- University of California San Diego (US)
- Ministry of Public Health (TH)
- Radboud University Medical Center (NL)
- Gates Foundation (US)
- Corresponding author
- Laxminarayan, Ramanan
- ORCID
- Venue
- The Lancet
- Publisher
- Elsevier BV
- Published
- 2024-06
- Volume
- 403
- Issue
- 10443
- Pages
- 2534-2550
- ISSN
- 0099-5355 (ISSN-L)
- 0140-6736
- OpenAlex
- W4398244676
- Cited by
- 111
- References
- 98
- Citations by year
- 2026: 32 · 2025: 54 · 2024: 25
- FWCI
- 4.65
- Type
- journal article
- Language
- en
- Open access
- green
- repository.ubn.ru.nl
- Licence
- Locations
- The Lancet (publishedVersion)
- PubMed (publishedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- bepress Legal Repository (submittedVersion)
- Funders
- Bill and Melinda Gates Foundation
- Topics
- Health Sciences › Medicine › Infectious Diseases › Antibiotic Use and Resistance
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Pharmaceutical Economics and Policy
- Health Sciences › Medicine › Microbiology (medical) › Antibiotic Resistance in Bacteria
- Keywords
- antimicrobial resistance, antibiotic development, vaccine development, diagnostics, public-private partnerships, drug development incentives, access to medicines, low- and middle-income countries, clinical trial networks, platform technology, infection control, antibiotic stewardship, drug-resistant pathogens, out-of-pocket costs
- MeSH terms
- Drug Development, COVID-19, SARS-CoV-2, Anti-Bacterial Agents, Bacterial Infections, Health Services Accessibility, Humans, Drug Resistance, Bacterial, Pandemics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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