Separating Host and Microbiome Contributions to Drug Pharmacokinetics and Toxicity
By Katie E Golden, MD
One of the biggest challenges in modern disease treatment is the large amount of variation in anindividual’s response to drug therapy. Despite the rapidly developing pharmaceutical industry, researchers and clinicians still struggle to predict a particular patient’s therapeutic response, or even toxicity, from oral medication. This is determined by not only an individual’s metabolism, but also their intestinal microbiome, which actively contributes to drug metabolism. To date, however, there has been no clear way to quantify the distinct metabolic contributions of host versus gut microbiota, and how that ultimate influences a drug’s pharmacokinetics.
In a recent study published in Science by Zimmerman (et.al) 1 , researchers developed a model to quantify the unique contribution of our intestinal microbiota to pharmacokinetics. They developed their model by studying the metabolism of an antiviral drug, Brivudine, in germ-free mice (with no intestinal bacteria), conventional mice (with normal intestinal flora), and ultimately gnotobiotic mice. The gnotobiotic mice were particularly key to the experiment, as they were colonized with bacteria specifically identified as contributing to Brivudine metabolism in earlier experiments. This allowed the investigators to create mouse models that were essentially identical other than a single bacterial gene responsible for drug metabolism. The researchers then measured concentrations of both the drug and its metabolite in several different body compartments (such as in the blood and liver), as well as at several points along the intestinal tract. They then used this data to ingeniously develop a computational model to predict host and microbiome contributions to the metabolism (and toxicity) of the studied drug.
To test whether this model could be applied to other microbiome-metabolized drugs, they studied its application with two other drugs. First, they applied the model to the metabolism of Sorivudine, which is similar to the originally studied drug Brivudine, but metabolized at different rates by both the host and microbiota. They also applied the model to Clonazepam, a widely administered benzodiazepine with a complicated metabolic pathway. The model successfully predicted host and microbiome contributions, as its predictions matched the observed drug metabolism in both experiments.
This physiologic model developed by Zimmerman and his team has far-reaching potential to inform future therapeutic strategies. By developing a quantitative framework to understand the interplay between host and microbiome in drug metabolism, we are now one step closer to developing personalized medical treatments that enhance therapeutic response and minimize toxicity in drug therapy.