Antifungal resistance: what if chance outperforms natural selection?

The protocol adopts a cautious, stepwise approach, with an in silico phase to validate theoretical predictions before committing to costly and time-consuming experiments. This sequential design with explicit GO/NO-GO criteria represents excellent methodological practice.

The hypothesis successfully integrates three well-established but often separate theoretical frameworks—nearly neutral theory (Ohta), founder effect/bottleneck dynamics (Mayr), and network phylogenetics—into a coherent mechanistic model for a pressing applied problem (antifungal resistance). This synthesis is intellectually compelling.

The hypothesis elegantly bridges population genetics theory (drift in bottlenecks) with a pressing clinical problem (antifungal resistance), proposing a non-adaptive pathway that is often overlooked.

The panel addresses a critical unmet need in antifungal therapy: the prediction of the emergence of 'stochastic' resistances that elude deterministic models, targeting directly the R&D departments of major pharmaceutical groups (Pfizer, Gilead, MSD) and public health agencies (CDC, ECDC).

An original mechanistic hypothesis linking population genetics, evolutionary ecology and public health — an angle highly valued in interdisciplinary calls.