The HIV Resistance Response Database Initiative (RDI) has developed a free online tool that enables healthcare professionals to make informed, individualised treatment decision-making for HIV positive patients.
The RDI is an independent, not-for-profit international research collaboration set-up in 2002 with the mission to improve the clinical management of HIV infection through the application of bioinformatics to HIV drug resistance and treatment outcome data.
Since its inception, the RDI has worked with leading clinicians and scientists from around the world to develop the world’s largest database of HIV drug resistance and treatment outcome data, containing information from approximately 240,000 patients in more than 30 countries.
The new tool, called the HIV Treatment Response Prediction System (HIV-TRePS), is based on predictive computer models that were specifically designed to optimise HIV therapy in countries with limited healthcare resources.
RID developed the models based on the data they collected from over 150,000 HIV patients treated in hundreds of collaborating clinics around the world. They used the data to train computational models that accurately predict how an individual on failing therapy will respond to any new combination of HIV drugs.
In a paper published in the Journal of Antimicrobial Chemotherapy (JAC), the authors described two new sets of models: one that does not require the genetic code of the virus, for use settings where HIV genotyping tests are unavailable, and another that includes this information for use in well-resourced settings.
Both sets of models were developed with relaxed requirements for input data, again to suit low to middle-income countries.
Both sets of models predicted the responses to the new regimen introduced in the clinic with approximately 80% accuracy. They were significantly more accurate than using genotyping, with state of the art interpretation, to predict responses. Both sets of models were able to identify combinations of locally available drugs that were predicted to produce a response in 90% or more of the cases that failed the new combination introduced in the clinic.
“These models represent a significant step forward towards the individualisation of HIV therapy in countries where genotyping is unavailable, treatment options are limited, and the selection of the best combination is particularly critical,” said Scientific Chair of the RDI and an author on the paper, Dr Brendan Larder.
Currently, drug changes are not generally individualised but made according to set protocols, which can lead to sub-optimal treatments being introduced that can enable the development of drug resistance.
HIV-TRePS is freely available to be used by healthcare professionals via: https://www.hivrdi.org/treps/
The RDI’s participation in this project is through a subcontract with Leidos Biomedical Research, the prime contractor for the Frederick National Laboratory for Cancer Research, sponsored by the National Cancer Institute.