Advancing single-cell omics and cell-based therapeutics with quantum computing

Abstract

The generation of highly accurate models of behaviours of individual cells and cell populations through integration of high-resolution assays with advanced computational tools would transform precision medicine. Recent breakthroughs in single-cell and spatial transcriptomics and multi-omics technologies, coupled with artificial intelligence, are driving rapid progress in model development. Complementing the advances in artificial intelligence, quantum computing is maturing as a novel compute paradigm that may offer potential solutions to overcome the computational bottlenecks inherent to capturing cellular dynamics. In this Roadmap article, we discuss the advancements and challenges in spatiotemporal single-cell analysis, explore the possibility of quantum computing to address the challenges and present a case study on how quantum computing may be integrated into cell-based therapeutics. The specific confluence of quantum and classical computing with high-resolution assays may offer a crucial path towards the generation of transformative models of cellular behaviours and perturbation responses.