J. Maltas

Drug dependence in cancer is exploitable by optimally constructed treatment holidays

This paper shows that drug-dependent cancer cells can be targeted by optimized treatment holidays, reducing population growth through adaptive therapy strategies.

Frequency-dependent ecological interactions increase the prevalence and shape the distribution of pre-existing drug resistance

This study shows frequency-dependent ecological interactions help pre-existing drug resistance persist despite fitness costs, using simulations and engineered mutants in NSCLC.

Hidden Interactions: Frequency-Dependence Emulates Selection-Driven Dynamics in Evolving Populations

This paper shows that frequency-dependent interactions can mask or mimic frequency-independent selection in evolving populations, emphasizing the need to account for interactions in evolutionary inference.

Reinforcement Learning informs optimal treatment strategies to limit antibiotic resistance.

This study uses reinforcement learning to develop optimal antibiotic treatment strategies that reduce antimicrobial resistance in simulated E. coli populations.

Dynamic collateral sensitivity profiles highlight challenges and opportunities for optimizing antibiotic sequences

The paper studies how collateral sensitivity to antibiotics changes over time in E. faecalis, finding that resistance dominates early while sensitivity increases later, with population-specific trends.

Evolution in alternating environments with tunable inter-landscape correlations

This study examines how alternating between correlated fitness landscapes affects evolutionary fitness in asexual populations, finding that correlation and landscape ruggedness influence steady-state fitness outcomes.

Measuring competitive exclusion in non-small cell lung cancer

This study measures frequency-dependent interactions between gefitinib-resistant and sensitive NSCLC populations to show that competitive exclusion depends on growth rate data, not just cost of resistance.

Using selection by non-antibiotic stressors to sensitize bacteria to antibiotics

This study shows that non-antibiotic stressors can sensitize bacteria to antibiotics through sequential adaptation, revealing potential strategies to combat antibiotic resistance.

Pervasive and diverse collateral sensitivity profiles inform optimal strategies to limit antibiotic resistance

The paper quantifies collateral sensitivity in Enterococcus faecalis and develops a model to design optimal drug policies that reduce antibiotic resistance.

Antibiotic interactions shape short-term evolution of resistance in E. faecalis

This study quantifies how antibiotic combinations affect resistance evolution in E. faecalis, showing varied growth and resistance adaptation depending on drug interactions and concentrations.