Evolutionary dynamics of drug resistance
Mathematics from population genetics shows that resistant cells almost always exist before treatment in large tumours, and that combining drugs with different resistance mutations from the start can succeed where the same drugs in sequence fail.
Overview
Ivana Bozic, Martin Nowak and colleagues modelled targeted therapy as a branching process in which resistance mutations arise before and during treatment. Their 2013 analysis showed that a tumour of a billion cells almost certainly carries cells resistant to any single drug, that monotherapy therefore fails predictably, and that two drugs without overlapping resistance mutations given together can cure where sequential use cannot, provided no single mutation confers cross-resistance. The framework explains the transient responses to single kinase inhibitors and underpins combination design, and later work added treatment holidays and dose modulation.
How it works
Resistance arises as a stochastic branching process; the probability of pre-existing resistance to k drugs falls steeply with k when their resistance mutations are distinct, favouring simultaneous combinations.
- Quantitative case for upfront combinations
- Explains kinetics of relapse on targeted drugs
- Parameters partly measurable from sequencing
- Assumes genetic resistance; non-genetic adaptation is common
- Toxicity limits combinations in practice
- Fitness costs of resistance often unknown
Latest papers
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