December 2, 2022

Why Antibiotics Don’t Work; Implications for clinical trial design

I want to discuss the idea of ​​superiority trials for antibiotics and some of the questions that many experienced researchers overlook when thinking about this topic. I am grateful to George Drusano for his contribution here.

Before I get into this topic, I want to say that I know I haven’t written a blog since April. This is because I believe that if we don’t have a significant incentive such as that contemplated in the PASTEUR Act before the US Congress, everything else is futile, including antibiotic trial design issues. . .

There are many reasons why antibiotics don’t work, and most of the time it’s not related to resistance. Consideration of this issue will be important in the design of clinical trials for antibacterials, as Contrafect has just learned the hard way.

Yes, resistance to antibiotic treatment is an important concern, but it is difficult to design trials around this issue for several reasons. Resistance to reference comparator antibiotics remains rare. Even when this happens, in a randomized, double-blind trial, we usually exclude patients whose infection is resistant to a comparator antibiotic so that they can be treated with something more likely to be effective. There are occasional exceptions to this, but this issue complicates trial design.

Some experts believe, based on certain data, that so-called bactericidal antibiotics like beta-lactam antibiotics are generally superior to bacteriostatic antibiotics like tetracyclines. Others believe that it is mainly a question of choosing an appropriate dose for the indication under study. Still others believe that this is only true for certain situations such as nosocomial pneumonia or serious infections occurring in severely immunocompromised patients. But proving it in a clinical trial remains very difficult.

Of course, other obvious problems exist. We try to exclude patients with non-bacterial infections from the study when possible because antibiotics won’t be effective – but we don’t always succeed. The inclusion of these patients tends to change the result to the difference “nil” or -no difference. That would be a big deal in a superiority trial. We also try to exclude patients who are not likely to respond even to effective antibiotic treatment, such as those who are unlikely to survive long enough to provide enough time for the study and those who are severely immunocompromised for whom the antibiotic treatment may be less effective. But that still leaves many patients with susceptible infections who will respond poorly to antibiotic treatment. Why and how?

Let’s take an example – serious infections caused by Staphylococcus aureus. Disseminated infections with. aureus tend to involve multiple foci of infection, including abscesses of varying sizes. Because there may be several such foci, drainage is not possible. Antibiotics may not penetrate these areas well and may not work well in the local abscess environment where the pH may be low. Left-sided staphylococcal endocarditis still results in a 30% mortality rate despite proper treatment. Personally, I think this is more likely caused by mechanical issues and multiple abscesses rather than a problem with the antibiotic’s lack of destructive activity.

Sometimes patients slip into a sepsis where a systemic inflammatory response is triggered. Although it may not be immediately fatal, even with antibiotic therapy, the inflammatory response could progress and could ultimately lead to organ failure and death. Again, protected infection sites could be the issue here. Yet these patients will be enrolled in clinical trials and the antibiotic itself will be doomed without further interventions such as surgery.

Animal models in the antibiotic world are incredibly useful in predicting efficacy and effective dosage. In vitro pharmacodynamic models using the hollow fiber system can also be useful and are often more “conservative” than traditional animal models because you can study longer-term effects, including that of slowly emerging resistance. But these models do not, in general, predict superiority as studied in the context of a clinical trial.

What I’m trying to make here is that superiority trials for antibiotics will be confounded by infections where the antibiotic is not the problem. Most antibiotics will work well in the absence of such intractable problems. Therefore, even in the absence of resistance, it will be difficult to demonstrate clinical superiority even with an antibiotic that might appear superior in vitro or in various model systems.

# Reproduced with permission. Dr. Shlaes’ original blog post can be read here.