Using a mathematical formula that carefully measures the degree to which HIV infection of immune system cells is stalled by antiretroviral therapy, AIDS experts at Johns Hopkins have calculated precisely how well dozens of such anti-HIV drugs work, alone or in any of 857 likely combinations, in suppressing the virus. Results of the team's latest research reveal how some combinations work better than others at impeding viral replication, and keeping the disease in check.
"Our study results should help researchers and clinicians develop simpler treatments, using either existing or new drugs, for people who are just starting therapy or people who have already tried and developed resistance to another combination," says senior study investigator and infectious disease specialist Robert Siliciano, M.D., Ph.D.
Siliciano, a professor at the Johns Hopkins University School of Medicine and a Howard Hughes Medical Institute investigator, and colleagues constructed the measurement tool, called the instantaneous inhibitory potential, or IIP, in the laboratory several years ago by analyzing the shape of drug dose-response curves in human immune system cells infected with HIV. They found that the curves' steepness reflects the extent to which small increases in the amount of drugs can further suppress attempts by the virus to bounce back, reproduce and spread.
Researchers say their latest study findings, to be published in the journal Nature Medicine online Feb. 19, along with other recent studies, provide valuable information to physicians about the potential strength of different combination drug therapies, and can help in streamlining and tailoring so-called highly active antiretroviral therapy, or HAART, to as few possible drugs as needed. Several hundred thousand of the more than 1 million Americans living with HIV disease are currently using HAART to fight the disease.
Among the latest study's key findings was that the most potent drug combos included the drugs efavirenz (a non-nucleoside reverse transcriptase inhibitor) and darunavir (a protease inhibitor.) According to the Hopkins team's calculations, the drug mix suppressed viral replication by more than a trillion times, enough to prevent infection of every single lymphocyte, or immune system cell, of which there are a trillion in the body.
The least-powerful drug was found to be one of the oldest anti-HIV medications, d4T, or stavudine (a nucleoside analogue reverse transcriptase inhibitor), which had the power to suppress viral replication by less than 10 times if used on its own (although, Siliciano points out, it works much better when taken in combination with other drugs.)
Siliciano says the most widely used combination, a single pill known as Atripla, consisting of tenofovir disoproxil fumarate (a nucleotide analogue reverse transcriptase inhibitor), emtricitabine (a nucleoside analogue reverse transcriptase inhibitor), and efavirenz, was able to reduce viral replication to as few as one in a billion.
Siliciano points out, however, that any drug combination which suppresses viral replication to the degree that out of every 100,000 lymphocytes exposed to the drugs, only one lymphocyte is likely to be infected (for five tenfold reductions) - is sufficient to keep the disease in check, so long as people take their medication as prescribed.
"This means that overall access to anti-HIV medications could also improve as we develop simpler combinations of fewer drugs to achieve near total suppression," says Siliciano. Less than 7 million of the 34 million people worldwide infected with HIV are taking antiretroviral therapy, he notes.
The Johns Hopkins team based its new calculations on five years of analyzing just how antiretroviral drugs hinder key steps in HIV's life cycle, preventing it from replicating and infecting other immune system cells.
Scientists have for decades focused on multiple drugs targeting different enzymes that are key to the viral life cycle, thinking that multiple barriers along the chain could best halt replication.
Although the strategy worked, scientists had, until now, no theory to explain why some drug combinations worked well and others did not. Indeed, they point out, one of the newest classes of anti-HIV medications, so-called integrase inhibitors, did not work well as single drug treatments in laboratory experiments, but were highly effective in people when combined with other drugs.
Siliciano says that as a result of the Hopkins team's latest research and another of their recent findings, published in Science Translational Medicine in July, experts can finally demonstrate how different drug combinations disrupt and halt viral replication.
Researchers found that the steepest curves occurred when the drug targeted a stage in HIV's life cycle, in which many copies of viral enzymes, were needed. Citing protease inhibitors as an example, Siliciano says several copies of protease enzyme are needed to cleave the virus into hundreds of working parts before HIV can infect a new immune system cell. He goes on to say that "a level of inter-enzyme cooperation" is happening, specific to each stage of HIV replication.
"Our research shows that drugs like protease inhibitors really work like an on-off switch," says Siliciano. "Above a certain concentration, these drugs completely turn off viral replication. When you have only one copy of a viral enzyme needed in any key part of HIV's life cycle, a little more drug won't give you a lot more suppression; but, when you have more than one copy of enzyme needed for viral replication, then the dose-response curve for the drug will be a lot steeper, and a little more drug will completely shut off viral replication, which is what we want.
"It's gratifying to finally have a consistent metric for evaluating HAART medications that offers reliable information on how well they work in stopping HIV replication, and which also gives us a baseline target for suppression at less than one in 100,000 immune cells becoming infected in the presence of any drug combination," he adds.
The Johns Hopkins inhibition index was first developed to compare the level of viral inhibition from different drugs in different classes and to show how they could be graded.
Having measured the different potencies of many drugs, Siliciano conducted his next set of lab experiments to focus on the explanation behind different strengths of viral inhibition. The scientists measured the changes in the dose-response curves, plotting the results on graphs and comparing the sloping curves for each drug or combination of drugs.