Highlights

Above

The molecular structure of lopinavir, an HIV medication that is being investigated for its potential to treat COVID-19.

© Shutterstock

Could an HIV drug treat COVID?

7 Oct 2020

A*STAR researchers use digital drug simulators to predict the efficacies of repurposed antivirals for treating COVID-19.

In the hunt for pharmaceuticals to combat COVID-19, repurposed antiviral drugs are low-hanging fruit; instead of starting drug discovery from scratch, it is much faster to use drugs that are already known to be safe and effective in treating viral infections. In particular, a drug used to treat HIV infections—lopinavir—is of particular interest to scientists. Not only had the antiviral shown clinical efficacy in HIV patients, but it also inhibited the growth of coronaviruses closely related to SARS-CoV-2 in prior outbreaks.

Given its successful track record, could lopinavir also be used to treat COVID-19 patients? To answer this question, a team of researchers led by James Chan of A*STAR’s Singapore Institute of Food and Biotechnology Innovation (SIFBI) turned to a state-of-the-art computational tool, called the Simcyp® Simulator, to carry out physiologically-based pharmacokinetic (PBPK) modeling. In PBPK modeling, hundreds of differential equations are integrated to create a virtual human being that is then used to digitally map drug kinetics in the body.

When a patient takes a dose of lopinavir, most of the drug binds strongly to proteins in the bloodstream, with only the unbound drug remaining clinically active. Of this, only a fraction of the unbound drug then finds its way to the lungs. Even though lopinavir was found to inhibit SARS-CoV-2 in cell-based systems, its clinical efficacy is not guaranteed. “Being pharmacodynamically active is only half the story. We have to ensure that the drug reaches where it is needed, and at a high enough level to work,” explained Chan.

The team deployed the PBPK model to estimate how lopinavir would be absorbed, distributed and metabolized by COVID-19 patients over time. “While it is reasonably easy to repeatedly measure the levels of a drug in the blood of a human subject, it is considerably harder and deeply invasive to do the same in tissues such as the lung,” said Chan. “One major advantage of the virtual human model is the ability to accurately estimate drug levels within human organs using modeling and simulation.”

Unfortunately, the simulations revealed that administering the standard twice-daily regimen of lopinavir would not give patients high enough drug concentrations in the lung to inhibit SARS-CoV-2. Ramping up the dose is also not an option, as it may result in serious side effects. Similar limitations have also caused other antivirals such as hydroxychloroquine to fall flat as COVID-19 countermeasures.

The researchers have not stopped searching, however, and are currently running PBPK as well as viral dynamics simulations on other promising antivirals for COVID-19. “Coupling both types of simulations will allow us to determine the effective window to initiate treatment and the appropriate duration of treatment. These considerations are important to optimize therapy and ensure the judicious use of antivirals,” said Chan.

The A*STAR-affiliated researchers contributing to this research are from the Singapore Institute of Food and Biotechnology Innovation (SIFBI) and the Skin Research Institute of Singapore (SRIS).

Want to stay up to date with breakthroughs from A*STAR? Follow us on Twitter and LinkedIn!

References

Thakur, A., Tan, S.P.F., Chan, J.C.Y. Physiologically-Based Pharmacokinetic Modeling to Predict the Clinical Efficacy of the Coadministration of Lopinavir and Ritonavir against SARS-CoV-2. Clinical Pharmacology and Therapeutics (2020) | article

About the Researchers

James Chan graduated from the Department of Pharmacy at the National University of Singapore in 2011, subsequently obtaining his PhD in Pharmaceutical Sciences from the same department in 2015. He currently leads a research group at A*STAR’s Singapore Institute of Food and Biotechnology Innovation (SIFBI), specializing in applying physiologically-based pharmacokinetic modeling in the pharmaceutical, food & nutrition and consumer care sectors.

Aarzoo Thakur completed her MSc from the National Institute of Pharmaceutical Education and Research, India, in 2019, where she worked on physiologically-based pharmacokinetic (PBPK) modeling. She is now a Research Officer at A*STAR’s Singapore Institute of Food and Biotechnology Innovation (SIFBI) and plans to pursue her doctorate studies in the future.

Shawn Tan

Research Officer, ZUDL Lab

Skin Research Institute of Singapore
Shawn Tan graduated with a BSc (Pharmacy) from the National University of Singapore in 2019 and is a recipient of the National Science Scholarship awarded by the A*STAR’s Graduate Academy. He is in midst of completing a one-year research attachment with the Skin Research Institute of Singapore and will be pursuing a PhD in Pharmacy & Pharmaceutical Sciences at the University of Manchester thereafter.

This article was made for A*STAR Research by Wildtype Media Group