Resistance, tolerance, and persistence in PK/PD language
In everyday talk, if an antibiotic fails people often say the bug was resistant. That shorthand is understandable. It is also expensive for modeling, because it points the simulator at the wrong object.
This lesson separates three survival ideas and translates them into what a PK/PD model can see: a moved threshold, a slower kill, or a long surviving tail.
Concept map for simulation and reading papers. Related preprint context: comparative modeling of resistance, tolerance, and persistence.
Three words that should not be synonyms
Resistance usually means a heritable drop in susceptibility. In practice that often shows up as a higher MIC or a shifted pharmacodynamic curve. Genetics can sit underneath (target mutation, enzyme, efflux), but the PK/PD layer mainly notices the phenotype change.
Tolerance means a population can endure drug pressure longer without a large MIC shift. Time-kill curves look sluggish. The organism is not “fully susceptible in behavior” just because the MIC table looks polite.
Persistence points to a small subpopulation that survives much longer. The bulk may fall, then a refractory tail remains. Relapse risk lives in that tail more than in the first steep decline.
| Idea | What moved | What a model needs |
|---|---|---|
| Resistance | Threshold / MIC | Updated MIC or PD curve |
| Tolerance | Kill speed of the population | Time-kill or slower kill-rate terms |
| Persistence | Long-lived fraction | Biphasic kill or persister compartment |
A quick self-check
If changing the MIC fully explains the failure story, you are mostly in resistance territory. If MIC barely moved but killing stalled, look at tolerance or persistence before you keep tuning the dose in a PTA-only frame.What the curves look like
Same starting inoculum, different survival stories. MIC alone may not separate these lines.
Why a strong PTA can still disappoint
PTA asks whether exposure clears a threshold rule. That is a fair question. It is not every question.
A regimen can look excellent against the measured MIC distribution while:
- killing is too slow for the planned duration,
- a persistent fraction remains,
- or the assay MIC understates the real challenge at the infection site.
None of that makes PTA useless. It means you should label what your simulation tested. “High PTA vs MIC grid” is not the same claim as “sterilizing cure in every biology.”
Update the MIC distribution or PD curve. Re-run PTA/CFR. Mechanism matters later when you choose inhibitors or drug class switches.
Bring in time-kill information or slower kill parameters. Duration and shape of exposure may matter more than another small dose bump in a MIC-only frame.
Model a refractory fraction or biphasic kill. Ask whether your endpoint is inhibition, bulk kill, or durable clearance of the tail.
Pathogen contrast, briefly
Different organisms lean on different survival styles. In comparative modeling work, Staphylococcus aureus and Mycobacterium tuberculosis are a useful pair: one often shows a faster tolerance-like pattern, the other a longer persistence window. The lesson for the modeler is simple. Do not copy a kill structure from one species into another because the antibiotic name matches.
Takeaway
Resistance moves the threshold. Tolerance slows the population kill. Persistence leaves a long tail. Say which one your simulation is actually testing, especially when the clinical story is failure despite a tidy MIC.
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