The hunt continues at a brisk pace thanks to rapid developments in generating more potent computing power, writes Kumitaa Theva Das in part three in a series on vaccines beyond Covid
Underway since the 1980s, the search for a vaccine for HIV has delivered several encouraging leads, though no panacea. Now, bigger than ever, data and computing power offers new approaches.
Vaccines are often developed from the immunity of recovered individuals. Molecules produced in the immune system response - antibodies - can be isolated and analysed and used as a basis for vaccine research.
However, HIV attacks the immune system itself, disabling the usual mechanisms that help a vaccine do its job. The few individuals worldwide who have been cured of HIV to date became well after undergoing stem cell transplants. Their immune system was dramatically altered in order for them to recover.
Another route for vaccine development also closed to HIV research is what’s known as attenuated viruses. These are versions of the original virus modified so that they don’t cause severe disease. But for HIV, the attenuated version may raise safety issues. The HIV virus also changes often, developing new strains, which complicates finding a consistent immune response.
This has not discouraged attempts at HIV vaccine development. In recent years, a Thai trial (RV 144), the largest HIV vaccine trial, reduced new infections by 30 percent. The trials were eventually stopped as 30 percent is deemed too low, but it provided hope that an effective HIV vaccine may one day be possible.
Two other large HIV vaccine trials - Imbokodo (HVTN 705) and Mosaico (HVTN 706) have sparked ideas and more research. These trials used the ‘adenovirus type 26’ common cold virus - similar to the one used in the AstraZeneca Covid vaccine - to deliver a computer-designed combination of molecules that induce an immune response. The computer combined antigens from multiple HIV strains and included proteins from the external coating of the virus as boosters.
The Imbokodo studies showed that the vaccine triggered a strong and long-lasting immune response. However, the vaccine didn’t target enough HIV strains and the trial was halted a few months ago when the efficacy was shown to be only around 25 percent. For some reason, however, this vaccine had quite good effectiveness in older women, which shows there is much yet to learn about this virus.
The parallel Mosaico trial is still underway. In contrast to Imbokodo, the booster in Mosaico includes external coat proteins from a larger variety of HIV strains.
Other researchers are exploring a variety of new approaches, including the mRNA technology which was successfully used in the Pfizer and Moderna Covid-19 vaccines.
Early in 2022 as part of the International AIDS Vaccine Initiative, vaccine manufacturer Moderna and the American National Institutes of Health launched a trial of their HIV vaccine with mRNA technology. This first phase tests the safety of different doses of the vaccine in real people. They had earlier obtained promising results in mice and monkeys.
With encouraging data from the Imbokodo and Mosaico trials, could computer models be the key to better vaccines? Modelling seems to assist scientists tremendously in viruses that have multiple variants and subtypes.
Mathematical and computational models have also been used in making decisions about doses in vaccine trials. This can cut down on development time and optimise immune responses. Modelling is also expected to detect unwanted immune responses, which could be especially helpful in populations who require non-standard dosings such as children, the immunocompromised and certain ethnic groups.
America’s Food and Drug Administration received its first submission of a vaccine product created using modelling to optimise dose-response relationships just a few months ago, paving the way for future vaccine research.
Kumitaa Theva Das holds a Ph.D. in genetics from the University of California, Davis and her tasks at Universiti Sains Malaysia focus on gene therapy against HIV/AIDS. She currently undertakes COVID-19 research.
The author declares no conflict of interest.
Originally published under Creative Commons by 360info™.
