Competition delays multi-drug resistance evolution during combination therapy

Abstract

A R T I C L E I N F O Keywords: probability of drug resistance combination therapy simulation of individual-based models stochastic processes A B S T R A C T Combination therapies have shown remarkable success in preventing the evolution of resistance to multiple drugs, including HIV, tuberculosis, and cancer. Nevertheless, the rise in drug resistance still remains an important challenge. The capability to accurately predict the emergence of resistance, either to one or multiple drugs, may help to improve treatment options. Existing theoretical approaches often focus on exponential growth laws, which may not be realistic when scarce resources and competition limit growth. In this work, we study the emergence of single and double drug resistance in a model of combination therapy of two drugs. The model describes a sensitive strain, two types of single-resistant strains, and a double-resistant strain. We compare the probability that resistance emerges for three growth laws: exponential growth, logistic growth without competition between strains, and logistic growth with competition between strains. Using mathematical estimates and numerical simulations, we show that between-strain competition only affects the emergence of single resistance when resources are scarce. In contrast, the probability of double resistance is affected by between-strain competition over a wider space of resource availability. This indicates that competition between different resistant strains may be pertinent to identifying strategies for suppressing drug resistance, and that exponential models may overestimate the emergence of resistance to multiple drugs. A by-product of our work is an efficient strategy to evaluate probabilities of single and double resistance in models with multiple sequential mutations. This may be useful for a range of other problems in which the probability of resistance is of interest.

Antibiotic resistance genes in bacteria: Occurrence, spread, and control

“…Not only is the use of novel antimicrobial molecules likely to foster the evolution of de novo resistance mechanisms, but it can also favor the emergence of pathogens possessing yet unidentified combinations of resistance genes [51]. However, in combination therapy, competition delays the evolution of MDR [52]. Because of individual drug-resistant mutations, the incidence is equal to the product of the drug-resistant mutation rate for each drug.…”

Control predictivo basado en modelo como alternativa al modo de operación estándar en morbidostato

“…La Eq. ( 2) describe el crecimiento en la población bacteriana X(t), que se encuentra ahora inhibido por los efectos de la concentración A(t) de antimicrobiano (medida en mg L −1 ) presente en el sistema para cada tiempo t, y que actúa únicamente con efecto bacteriostático según el modelo planteado en [1]. La dinámica del antimicrobiano también se tiene en cuenta en el modelo a través de la Eq.…”

“…donde el horizonte de integración es el doble del intervalo necesario para añadir 1mL de volumen al sistema (es decir, t(k) + 2∆t), y donde se ha fijado como estado inicial del modelo X(t(1)) = OD (1).…”

“…The morbidostat control law used so far in the literature consists of a fairly simple algorithm incorporating two conditional rules to determine when the addition of the antimicrobial to the system is necessary. In this work, we show two main results in this context: (1) to carry out simulations and extract conditions under which simple control in morbidostat cannot stabilize the concentration of microorganisms to the target concentration and (2) the realtime control, with stabilization to the target point, of the bacterial concentration using model predictive control.…”

Mutators drive evolution of multi-resistance to antibiotics

“…Concentration gradients are expected to facilitate the evolution of resistance 40,41 , particularly if multiple mutations are required [42][43][44][45] .…”