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Australian Takeaways from EACS 2025
Striving for Improvement in Australia: Takeaways From EACS 2025

Released: December 05, 2025

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Key Takeaways
  • Although the impact of low-level viremia in people living with HIV remains unknown, machine learning may be harnessed to identify patterns of low-level viremia that are associated with increased risk of virologic failure.
  • More options for long-acting ART are on the horizon, including a weekly oral combination of islatravir and lenacapavir and a twice-yearly injection of lenacapavir with broadly neutralizing antibodies teropavimab and zinlirvimab.

Addressing Low-Level Viremia
Despite excellent efficacy of current antiretroviral therapy (ART) for HIV, there are still significant challenges in ART adherence, long-term comorbidities, adverse effects, and occasional regimen failure among people living with HIV in Australia. Low-level viremia on ART is one clinical situation that many Australian healthcare professionals find challenging. To this end, there were 2 very interesting presentations in relation to low-level viremia at the recent EACS 2025 meeting in Paris that may inform future clinical management of low-level viremia.

First, a small cohort study from Clemente and colleagues attempted to determine the immunologic impact of low-level viremia. Of interest, there was no decline in CD4+ or CD8+ T-cell counts in the presence of low-level viremia. However, the investigators did not assess immune activation, which is probably the immunologic parameter that is more likely to be associated with an adverse clinical outcome of low-level viremia.

Then, a much larger analysis of the Swiss HIV Cohort Study by Kusejko and colleagues used machine learning to identify patterns of low-level viremia associated with virologic failure. They examined participants who started ART after 2010 with a follow-up of at least 2 years without virologic failure (defined as HIV-1 RNA >200 copies/mL) before at least 1 measure of low-level viremia (HIV-1 RNA 50-200 copies/mL). Among these participants, 20.4% experienced virologic failure.

Using unsupervised clustering, an algorithm identified patterns of low-level viremia that had the highest likelihood of predicting subsequent virologic failure:

  • Consistently high low-level viremia
  • A late peak in low-level viremia, years after starting ART
  • ≥1 low-level viremia measurement >100-150 copies/mL
  • ≥2 consecutive low-level viremia measurements

This approach is one of the first examples of how artificial intelligence algorithms could potentially alter clinical practice in Australia, through identifying who is at greatest risk of virologic failure following low-level viremia. The next step will be to determine if any intervention alters the clinical outcome.

Long-Acting ART
Two important follow-up studies of long-acting investigational ART were also presented.

The first was the 96-week data for a phase II study where participants were randomized to receive a weekly oral combination of islatravir and lenacapavir (LEN) or daily oral bictegravir, emtricitabine, and tenofovir alafenamide for 48 weeks. At the end of the 48 weeks, all participants received the weekly combination. At 96 weeks, no participant had HIV-1 RNA ≥50 copies/mL. In addition, there were no grade 3 adverse events related to islatravir and LEN, nor any change in CD4+ cell count. Of importance, weight and BMI remained stable.

Another study randomized 80 participants 2:1 to LEN in combination with 2 long-acting, investigational, broadly neutralizing antibodies—teropavimab (TAB) and zinlirvimab (ZAB)—every 6 months, or daily oral ART.  Susceptibility to both antibodies was an inclusion criteria.

At Week 52, LEN plus TAB and ZAB was found to be well tolerated, with 88.7% of participants demonstrating HIV-1 RNA <50 copies/mL. Efficacy of LEN plus TAB and ZAB was similar to daily oral ART. Three participants receiving LEN plus TAB and ZAB met criteria for virologic rebound; 2 had emergent resistance (one each to LEN and ZAB). All 3 participants resuppressed on oral ART.

Given the ongoing challenge of ART adherence in Australia and the need for more long-acting ART, the infrequent dosing and high acceptability of this regimen are of high interest for HIV care in Australia. The main issue that I could potentially see arising for Australian people living with HIV is that not all people have HIV that is sensitive to both of these specific broadly neutralizing antibodies. In addition, sensitivity to both antibodies is less common in people with non–HIV-B subtypes compared with subtype B. 

Your Thoughts
How do you think machine learning could be harnessed to improve HIV care in your area? Leave a comment to join the discussion!