Interested in more global health innovation news? Every week GHTC scours media reports worldwide to deliver essential global health R&D news and content to your inbox. Sign up now to receive our weekly R&D News Roundup email.
At the 76th World Health Assembly last week, World Health Organization (WHO) member states adopted a resolution on strengthening diagnostics capacity, following a recommendation from the Executive Board earlier this year. The resolution is aimed at raising global awareness of the importance of diagnostics and the major gaps in access, to even the most basic diagnostics, that are faced around the world. Implementation of the resolution will be driven by national governments, which are urged in the resolution to integrate national diagnostics strategies that address the regulation, assessment, and management of diagnostics into their national health plans, as well as to develop a national essential diagnostics list, which will hopefully lead to wider availability and access.
An affordable meningitis vaccine designed to protect against multiple strains was found to be effective in phase 3 trials in Mali and the Gambia. The NmCV-5 vaccine, developed by PATH and the Serum Institute of India, generated a strong immune response against the five primary meningococcal strains in Africa, including the emerging X strain, for which there is currently no licensed vaccines. The cost of available vaccines for the four other strains of meningitis are currently too high for most African countries to buy the tens of millions of doses they need. NmCV-5 is expected to be available in the coming months and has the potential to dramatically reduce vaccine-preventable cases and deaths, especially those linked to the X strain.
Using artificial intelligence, researchers at the Massachusetts Institute of Technology and McMaster University have identified a new antibiotic drug to combat Acinetobacter baumannii, which is responsible for many drug-resistant infections and can lead to pneumonia and meningitis. The drug was identified using a machine-learning model that was trained to evaluate whether drug compounds would inhibit A. baumanii’s growth, which then reviewed a library of nearly 7,000 potential compounds. The finding has the potential to reduce drug-resistant infections and also highlights the potential role of artificial intelligence in accelerating the search for novel antibiotics in the face of growing antimicrobial resistance.