Optimal control in combination therapy for heterogeneous cell populations with drug synergies

TL;DR

This paper develops an optimal control framework for designing drug combination therapies targeting heterogeneous cell populations, accounting for drug synergies and aiming to improve treatment outcomes in cancer.

Contribution

It introduces a general mathematical framework using coupled differential equations to optimize multi-drug treatments for heterogeneous cells, incorporating drug interactions.

Findings

Framework applied to three canonical examples

Results provide insights into optimal drug dosing strategies

Systematic approach links mathematical optimality to clinical outcomes

Abstract

Cell heterogeneity plays an important role in patient responses to drug treatments. In many cancers, it is associated with poor treatment outcomes. Many modern drug combination therapies aim to exploit cell heterogeneity, but determining how to optimise responses from heterogeneous cell populations while accounting for multi-drug synergies remains a challenge. In this work, we introduce and analyse a general optimal control framework that can be used to model the treatment response of multiple cell populations that are treated with multiple drugs that mutually interact. In this framework, we model the effect of multiple drugs on the cell populations using a system of coupled semi-linear ordinary differential equations and derive general results for the optimal solutions. We then apply this framework to three canonical examples and discuss the wider question of how to relate mathematical optimality to clinically observable outcomes, introducing a systematic approach to propose qualitatively different classes of drug dosing inspired by optimal control.