Slowing evolution is more effective than enhancing drug development for managing resistance

TL;DR

This paper demonstrates through modeling and analysis that slowing the evolution of drug resistance is more effective than solely increasing drug development efforts in maintaining effective treatments for infectious diseases.

Contribution

The study introduces a queueing theory-based model comparing strategies to combat drug resistance, highlighting the superior impact of slowing resistance evolution over enhancing drug development.

Findings

Slowing resistance evolution outperforms increasing drug development in maintaining drug efficacy.

Analytical and simulation results support prioritizing resistance management strategies.

Evolution management may be the most crucial component in addressing drug resistance.

Abstract

Drug resistance is a serious public health problem that threatens to thwart our ability to treat many infectious diseases. Repeatedly, the introduction of new drugs has been followed by the evolution of resistance. In principle there are two ways to address this problem: (i) enhancing drug development, and (ii) slowing drug resistance. We present data and a modeling approach based on queueing theory that explores how interventions aimed at these two facets affect the ability of the entire drug supply system to provide service. Analytical and simulation-based results show that, all else equal, slowing the evolution of drug resistance is more effective at ensuring an adequate supply of effective drugs than is enhancing the rate at which new drugs are developed. This lends support to the idea that evolution management is not only a significant component of the solution to the problem of drug resistance, but may in fact be the most important component.