‘This research can help doctors prescribe the right doses of medicine so that patients get the best possible benefit from tuberculosis treatment,’ says Elin Svensson at the Department of Pharmaceutical Biosciences, Uppsala University. ‘Patients with HIV have sometimes had to terminate or replace a working HIV treatment while they were being treated for multi-drug-resistant TB. It was previously unknown how concurrent treatments with multiple drugs would affect each other and the patient’s recovery because everyone was treated with a standard dose. Now we can avoid doing that.’
The medication that Elin Svensson has examined dosing for is the active substance bedaquiline, a relatively new antibiotic used to treat multi-drug-resistant tuberculosis. For the treatment to be successful, three to four other drugs must be given at the same time. Much is still unknown about bedaquiline and its side effects.
Tuberculosis is the world’s deadliest infectious disease, killing an estimated one-and-a-half million people in 2014. One in 20 people with tuberculosis are infected by a kind of tuberculosis bacteria that are resistant to the most common and effective medications, so-called multi-drug-resistant tuberculosis. Currently, only half of these patients recover. Most of these cases are in Asia and Eastern Europe.
‘This will be a new link between dosing and drug concentration as well as between drug concentrations and effect,’ says Elin. ‘How much bedaquiline does a patient need to recover within a certain period of time? What effects do different exposure levels have?’
The standard treatment for multi-drug-resistant tuberculosis is long – up to two years – with poor efficacy. It also causes many uncomfortable side effects; it is common, for example, for patients to suffer hearing loss. There is therefore an acute need for new and better drugs. Although there is great uncertainty regarding the effects and side effects of bedaquiline, the drug is one of the most promising options right now.
One possibility with the new calculation models is that the patient can be given an adjusted dose of bedaquiline depending on which other medications that patient is taking. In the studies, Elin Svensson used data shared through the EU collaboration Predict-TB. Information on when, where and how the patients took the drug, along with data on blood tests, age and weight, has been used to produce mathematical models describing concentrations and effects chronologically over the duration of treatment.
How a drug is absorbed, distributed and eliminated from the body is usually referred to as the drug’s pharmacokinetics. The measurable effects that a drug provides, desired or undesired, can be called pharmacodynamics. In pharmacometrics, both of these are combined with mathematical models that can simultaneously represent both the typical pharmacokinetics and/or the pharmacodynamics, and contain variations, for example between individuals or from day to day.
Elin Svensson’s dissertation, which was completed in May, presents a model describing the pharmacokinetics of bedaquiline and one of the main decomposition products the body creates from bedaquiline, the metabolite M2, in patients with multi-drug-resistant tuberculosis. The model is then linked to a recently developed effects model describing how the patients’ bacteria levels decrease during therapy. This model-based analysis is the first successful description of how specific bedaquiline concentrations affect how quickly the treatment provides results and shows that current standard doses do not seem to provide maximum effect. The model will now be used to investigate alternative, potentially better doses of this new drug and to support the interpretation of the clinical relevance of known drug interactions.
‘It is very important that the best science is also used for diseases that primarily affect people in poorer parts of the world,’ says Elin. ‘In Sweden, many people think that tuberculosis is a problem of the past, but it is still a disease that needs lots of innovative research and smart solutions to give more people effective treatment, no matter where in the world they happened to have been born.’
For her production of this new model, Elin Svensson received the Lewis Sheiner Student Award, a prize awarded annually in memory of one of the founders of the scientific discipline to a PhD student presenting outstanding and innovative work.
The study is part of the dissertation Pharmacometric models to improve treatment of tuberculosis.