What scares you? As a kid, I hid behind couch cushions while watching Jurassic Park and could never finish a Goosebumps book. Nowadays, I am terrified of the growing epidemic of antimicrobial resistance. And I’m not the only one. Last year, as part of a five-year strategy to combat drug resistance, British Prime Minister David Cameron commissioned a review to examine the economic and health costs of antimicrobial resistance. In their first report published last December, the panel predicted that left unchecked, antimicrobial resistance will lead an extra 100 million deaths by 2050 and cost the world economy up to $100 trillion USD.

Efforts to halt the spread of antimicrobial resistance have focused on removing antibiotics from animal feed and curtailing the overzealous and oftentimes unnecessary use of antibiotics in humans. Another strategy to prevent resistance from developing is combination therapy, when two or more drugs with unique modes of action are taken together to treat an infection. In a paper published this week in the Proceedings of the National Academy of Sciences, a team of mathematicians and biologists led by Dr. Pleuni Pennings at San Francisco State University examined how differences in drug penetrance can impact the effectiveness of combination therapy and subsequent emergence of multidrug resistance.

Combination therapy reduces the risk of drug resistance because in theory, the pathogen needs to acquire multiple mutations at the same time to withstand the assault of multiple drugs. In reality, combination therapies fail to stem the development of resistance for a number of reasons. For example, some patients are started on a single drug first before a second drug is added. This type of treatment regiment facilitates resistance development because bacteria can acquire singular mutations in a stepwise fashion. Another reason is that different drugs have different staying power, which means that even though you may be taking both drugs at the same time, one could pass through your body much faster than the other. This creates periods of “effective monotherapy” where resistance can develop easily to the single long-lived drug. While a lot of attention has been paid to how drugs with different half-lives impact resistance, not a lot is known about how the spatial distribution of drugs influence the evolution of multidrug resistance. That’s where this paper comes in. 

When we take a drug, we often assume that enough of it will end up where it’s suppose to be and produce the desired outcome. But that’s not always the case. Certain body parts are difficult for drugs to penetrate. These include the central nervous system and genital tract where suboptimal levels of antimicrobials have been observed in previous studies. Pennings and his colleagues used mathematical models to predict how combination therapy with drugs that have different penetration will affect how quickly resistance to one or both drugs will develop. In their model, the researchers conceptualized the body as discrete but interconnected compartments. A sanctuary is a compartment where no drug is present whereas a single-drug compartment contains only one of the drugs. The double drug compartment where both drugs are present was assumed to always be the largest compartment. For simplicity, the researchers limited their model to two drugs and assumed that the drugs were either 100% effective in suppressing bacterial growth or completely absent and ineffective. Using these parameters, the researchers modeled various aspects of bacterial growth and the rate of resistance. In their studies, treatment failure was defined as the growth of a multidrug resistant mutant in the double-drug compartment.

Perhaps unsurprisingly, the researchers found that drugs with mismatched penetrance led to faster development of multidrug resistance. Evolution proceeded in a stepwise manner where resistant bacteria first grew in the single-drug compartment, migrated to the double-drug compartment and then developed resistance to the second drug. When the drugs have identical penetrance, there are only two compartments, the sanctuary and the double-drug compartment. In this case, multidrug resistance can only occur when two independent mutations arise simultaneously in the same bacterium, a slow and rare process. Their modeling also showed that resistance was more likely to develop against the drug with the highest penetrance and therefore, the largest single-drug compartment.

The researchers found a trade-off between reducing pathogen growth and preventing resistance. In prescribing a combination therapy, doctors are faced with the dilemma of trying to eliminate as many bacteria as soon as possible (ie. by minimizing the size of the sanctuary) or trying to prevent the stepwise evolution of multidrug resistance (ie. by minimizing the size of the single-drug compartment). As the size of the single-drug compartment increases to a certain point, the likelihood of treatment failure also increases. In their modeling, the researchers identified an inflection point beyond which increasing the size of the single-drug compartment actually reduces the likelihood of treatment failure. This is because as the single drug-compartment gets bigger, the size of the sanctuary shrinks thereby reducing the pool of bacteria from which single-drug resistant mutants can arise. If there is no sanctuary at all, treatment failure can only occur if the bacteria contained a preexisting mutation that conveyed resistance to one of the drugs or if resistance to both drugs developed very quickly after treatment starts.

These results provide important insights that doctors can take into consideration when choosing a combination therapy. For instance, in situations where it’s possible to eliminate all sources of infection, it might be preferable to choose a combination of drugs with different penetration profiles. The advantages of immediately wiping out all the pathogens could outweigh the risk of multidrug resistance developing in the long term. In cases where it is impossible to exterminate all the sanctuaries, a better strategy might be to choose drugs with similar penetrance profiles to prevent multidrug resistance.

There are several limitations to the model used by the researchers. Firstly, they do not take into account gene transfer between bacteria, which can speed up the spread of resistance through a population. Secondly, the researchers did not consider drug interactions that can act to enhance or impede the activities of the drugs. Finally, the model precluded mutations that convey cross-resistance, or resistance to multiple drugs. To more accurately reflect real life scenarios, these parameters will need to be included in future models. Furthermore, the results in this paper were based on purely mathematical models and not validated in the lab so much work remains to be done to verify these findings in a living system.

With more studies on how we can better prevent antimicrobial resistance in the clinic, maybe I will one day overcome my fears.

Update: Here is a really neat video that Dr. Pennings made to explain their results.

Reference:

Moreno-Gamez, S., Hill, A., Rosenbloom, D., Petrov, D., Nowak, M., & Pennings, P. (2015). Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multidrug resistance Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.1424184112