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arXiv · 2601.18082

Feedback-Based Quantum Control for Safe and Synergistic Drug Combination Design

Mai Nguyen Phuong Nhi·Lan Nguyen Tran·Le Bin Ho
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Abstract

Drug-drug interactions (DDIs) strongly affect the safety and efficacy of combination therapies. Despite the availability of large DDI databases, selecting optimal multi-drug combinations that balance safety, therapeutic benefit, and regimen size remains a challenging combinatorial optimization problem. Here, we present a quantum-control-based framework for DDI-aware drug combination optimization, in which known harmful and synergistic interactions are encoded into Ising Hamiltonians as penalties and rewards, respectively. The optimization is performed using the feedback-based quantum algorithm FALQON, a gradient-free variational approach. We study two clinically motivated tasks: the Maximum Safe Subset problem and the Synergy-Constrained Optimization problem. Numerical simulations using interaction data from Drugs.com and SYNERGxDB demonstrate efficient convergence and high-quality solutions for clinically relevant drug sets, including COVID-19 case studies.

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Mai Nguyen Phuong Nhi, Lan Nguyen Tran, Le Bin Ho. 2026-01-26. Feedback-Based Quantum Control for Safe and Synergistic Drug Combination Design. https://doi.org/10.1016/j.jocs.2026.102965

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