New malaria vaccine is world-changing, say scientists
BBC (9/7)
Additional coverage from Africa News (9/8), Fierce Biotech (9/8), Health Policy Watch (9/10), The Guardian (9/7), and Bloomberg (9/7)
A University of Oxford research team published promising results for a new malaria vaccine, R21. The trial, conducted among 409 children in Burkina Faso, found that an initial three doses followed by a booster after one year showed up to 80 percent efficacy in preventing malaria. The developers say the vaccine can be produced for just a few dollars and that they expect the vaccine to be rolled out next year through a manufacturing deal for more than 100 million doses a year with the Serum Institute of India. The rollout of the vaccine will follow an approval process that hinges on the results from a larger trial, which will be published in the coming months.
India and China clear needle-free COVID-19 vaccines
Associated Press (9/6)
Additional coverage from Nature (9/6)
Both India and China have approved needle-free COVID-19 vaccines¬—nasal and inhaled versions, respectively. The nasal version, licensed to Bharat Biotech, was developed by scientists at Washington University in St. Louis. CanSino Biologics has developed the inhaled version, which is a version of their own injected vaccine. Both vaccines use harmless cold viruses although the developers of the nasal version are seeking approval to use the vaccine as a regular and booster dose whereas the inhaled version was only tested as a booster. It is unclear when either vaccine will be available for distribution. These needle-free vaccines are just two of more than ten candidates being studied, as scientists are pursuing needle-free vaccines as a potential strategy to improve protection and make vaccines easier to administer, particularly in low-income countries
Google debuts a new AI tool in the global fight against tuberculosis
STAT (9/6)
A new study published in the journal Radiology looked at Google’s artificial intelligence (AI) model for automating tuberculosis (TB) detection compared to radiologists identifying TB on chest X-rays. The model uses AI to analyze X-ray images to determine which patients should receive follow-up confirmatory molecular testing that is expensive and time-consuming. The AI model could address physician shortages as well as improve TB outcomes and lower costs. While the study revealed promising results across large and diverse patient populations, the model needs to be further tested in real world environments with populations that are older and have more atypical presentations of the disease or other lung abnormalities. A study in a Zambian clinic, which will be finished in the coming months will provide further insight into the potential of the model.
