[sarchertech]

This has been well researched. Most antibiotic resistance has a fitness cost. Which means the resistance is being actively selected against.

This isn’t always the case. There are some adaptations that don’t have an observable fitness cost, but the majority do. That is, in a lab when you remove the antibiotic, we observed that the number of resistant bacteria drops over time.

We have also observed this in the real world. When we reduce usage of a specific antibiotic. The percentage of resistant bacteria in the wild drops.

The question is how long you’d have to retire an antibiotic and how many different antibiotics you’d need for this strategy to be viable.

[_heimdall]

Sure, but I think we agree then. What you describe is a hypothesis based on a few important assumptions. For example, that controlled lab studies are predictive analogs for the natural world, that a drop in resistance in such a controlled study will match a real world scenario, and that the rate at which resistance is lost can reasonably be matched by cycling in different drugs.

I'm not saying it isn't possible, maybe it is! Only that its a hypothesis and that the key assumptions are still just that rather than known parameters.

[sarchertech]

We have more than lab studies, we have real world observations that show the percentage of resistant strains dropping when we reduce the use of a specific antibiotic.

We may not be able to produce new antibiotics fast enough to get to the point where we have enough to cycle them effectively. That’s entirely possible.

But we have very good evidence that there is a point at which we would have enough. I mean at the limit there is a maximum amount of information bacteria can store in their genes, so there certainly exists some maximum number of resistances they can retain.

My point isn’t that we’re going to have enough to do this in x years. My point is that while we don’t know how many different antibiotics we need, we are almost certain that that number isn’t infinite.