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AI Advancements for HIV/AIDS

By Arushi Neravetla

A new era of rapid advancements of technology is heading our way as we focus on engineering devices to counter diseases and infections across the global spectrum Specifically, an example of one such disease being studied by researchers is HIV. HIV is particularly significant because the virus attacks a particular white blood cell called CD4+ T cells, which are important as our first-line defense of our immune system. “Although we expect there is no complete cure for HIV yet, the condition can be effectively controlled by appropriate treatment, such as antiretroviral therapy (ART), which is effective in reducing traces of the virus in the blood” (2).

In general, patients diagnosed with HIV that are prescribed with ART can achieve a healthy life without any risk to sexually transmitting the virus to their partner. Furthermore, there is significant improvement in ART through today’s research, discovering how we can improve antiretroviral medicines that can last for periods of time and through different approaches such as pills, injections, or implants. By doing so, we can have a less degree of side-effects and safe cost-effective care for patients as a result.

Another example is HIV immunotherapy using drug-mediated activation, by using a potential vaccine that can trigger antibody production against the HIV virus, where our T-cells can recognize and kill the virus in an effective way. AI such as gene editing is a potential approach to introduce a specific mutation in the human genome. “Over 1% of the world population which are immune to HIV possess this mutation, and in the future, such mutations can be set through gene-editing” (2). By asking participants who possess this mutation to study their genome can be beneficial in conducting research regarding immune protection against HIV.

To continue, computer scientists and researchers at Harvard John A. Paulson School of Engineering and Applied Sciences, have developed a social network system that can identify individuals who can effectively promote HIV prevention to other peers. “Through research conducted over 7000 homelessness, their algorithm significantly reduced risky behaviors of HIV transmission” (1). Working with social workers and participants themselves, they mapped out social networks and identified peer-group leaders with the most diverse set of connections across the internet. Soon, the research team facilitated training to the newly selected peer-group leaders and found out that the youth enrolled in an AI-assisted strategy group, called “CHANGE

(CompreHensive Adaptive Network samplinG for social influencE)” (1). Researchers studied improvement rates to steadily increase as rapid acceptance of new behaviors of using condoms and protective barriers in safe-sex, allowed the transmission of HIV to decrease.

Studying preventative transmission of HIV can outline future possibilities in eliminating the HIV virus and educating the youth in our generation will make it worth it. Subsequently, focusing on the chances of peer groups and youth channels of HIV’s origin can give valuable information on protecting yourself and significant others as a result.


  1. Burrows, Leah. “Using AI to Reduce the Risk of HIV.” Harvard Gazette, Harvard Gazette, 19

Feb. 2021,

  1. Dutta, Dr. Sanchari Sinha. “Advancements in Treating HIV.” News,

21 July 2020,


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