The state of quantum computing applications in health and medicine

Research Directions Quantum Technologies, Journal Year: 2023, Volume and Issue: unknown, P. 1 - 21

Published: July 24, 2023

Abstract Quantum computing hardware and software have made enormous strides over the last years 1 . Questions around quantum computing’s impact on research society changed from “if” to “when/how”. The 2020s been described as “quantum decade”, first production solutions that drive scientific business value are expected become available next years. Medicine, including fields in healthcare life sciences, has seen a flurry of quantum-related activities experiments few (although medicine theory arguably entangled ever since Schrödinger’s cat 2 ). initial focus was biochemical computational biology problems 3 , 4 5 6 7 8 ; recently, however, clinical medical drawn increasing interest. rapid emergence health necessitates mapping landscape. In this review, proof-of-concept applications outlined put into perspective. These consist 40 experimental theoretical studies use case areas span genomics, discovery, diagnostics, treatments interventions. machine learning (QML) particular rapidly evolved shown be competitive with classical benchmarks recent research. Near-term QML algorithms, for instance, support vector classifiers neural networks, trained diverse real-world data sets. This includes generating new molecular entities drug candidates, diagnosing based image classification, predicting patient persistence, forecasting treatment effectiveness, tailoring radiotherapy. cases applied algorithms summarized. addition, review provides an outlook era. There much discussion about healthcare’s journey towards precision quadruple aim (better health, lower costs, enhanced experiences, improved practitioner work lives) 9 While range technical ethical challenges remain, is poised key enabler advancing holy grail: keeping people healthy through proactive care guidance at level individual.

Language: Английский

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Drug design on quantum computers

Nature Physics, Journal Year: 2024, Volume and Issue: 20(4), P. 549 - 557

Published: March 4, 2024

Language: Английский

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Recent Advances in Quantum Computing for Drug Discovery and Development

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 64491 - 64509

Published: Jan. 1, 2024

The preservation of human health is utmost importance, and unrestricted availability medications essential for the sustenance overall wellness. Pharmaceuticals, which consist a wide range therapeutic substances utilized to diagnose, treat, improve various diseases conditions, play crucial part in field healthcare. However, drug research development process widely recognized its lengthy duration, demanding nature, substantial expenses. To enhance effectiveness this complex process, interdisciplinary groups have converged, giving rise known as "Bioinformatics". emergence future advancements Quantum Computing (QC) technologies potential significantly accelerate discovery development. This paper explores disciplines, such Computer-Aided Drug Design (CADD), quantum simulations, chemistry, clinical trials, that stand gain significant advantages from rapidly advancing technology. study aims explore fundamental principles, intending facilitate thorough understanding revolutionary

Language: Английский

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A Vision for the Future of Multiscale Modeling

ACS Physical Chemistry Au, Journal Year: 2024, Volume and Issue: 4(3), P. 202 - 225

Published: March 4, 2024

The rise of modern computer science enabled physical chemistry to make enormous progresses in understanding and harnessing natural artificial phenomena. Nevertheless, despite the advances achieved over past decades, computational resources are still insufficient thoroughly simulate extended systems from first principles. Indeed, countless biological, catalytic photophysical processes require ab initio treatments be properly described, but breadth length time scales involved makes it practically unfeasible. A way address these issues is couple theories algorithms working at different by dividing system into domains treated levels approximation, ranging quantum mechanics classical molecular dynamics, even including continuum electrodynamics. This approach known as multiscale modeling its use 60 years has led remarkable results. Considering rapid theory, algorithm design, computing power, we believe will massively grow a dominant research methodology forthcoming years. Hereby describe main approaches developed within realm, highlighting their achievements current drawbacks, eventually proposing plausible direction for future developments considering also emergence new techniques such machine learning computing. We then discuss how advanced methods could exploited critical scientific challenges, focusing on simulation complex light-harvesting processes, photosynthesis. While doing so, suggest cutting-edge paradigm consisting performing simultaneous calculations allowing various domains, with appropriate accuracy, move extend while they interact each other. Although this vision very ambitious, quick development lead both massive improvements widespread techniques, resulting and, eventually, our society.

Language: Английский

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High Ground State Overlap via Quantum Embedding Methods

PRX Life, Journal Year: 2025, Volume and Issue: 3(1)

Published: Jan. 14, 2025

Quantum computers can accurately compute ground state energies using phase estimation, but this requires a guiding that has significant overlap with the true state. For large molecules and extended materials, it becomes difficult to find states good for growing molecule sizes. Additionally, required number of qubits quantum gates may become prohibitively large. One approach dealing these challenges is use embedding method, which allows reduction one or multiple smaller cores embedded in larger region. In such situations, unclear how method affects hardness constructing states. work, we therefore investigate preparation context methods. We extend previous work on impurity problems, framework rigorously analyze subset orbitals. While there exist results optimal active orbital space selection terms energy minimization, demonstrate same principles be used define selected spaces Moreover, perform numerical studies molecular systems relevant biochemistry, field methods are due size biomacromolecules as proteins nucleic acids. two different strategies exhibit qualitatively entanglement. all cases, easy-to-obtain mean-field will have sufficiently high target estimation. Published by American Physical Society 2025

Language: Английский

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Deep learning and generative artificial intelligence in aging research and healthy longevity medicine

Aging, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 16, 2025

With the global population aging at an unprecedented rate, there is a need to extend healthy productive life span. This review examines how Deep Learning (DL) and Generative Artificial Intelligence (GenAI) are used in biomarker discovery, deep clock development, geroprotector identification generation of dual-purpose therapeutics targeting disease. The paper explores emergence multimodal, multitasking research systems highlighting promising future directions for GenAI human animal research, as well clinical application longevity medicine.

Language: Английский

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Control Flow in Active Inference Systems—Part I: Classical and Quantum Formulations of Active Inference

IEEE Transactions on Molecular Biological and Multi-Scale Communications, Journal Year: 2023, Volume and Issue: 9(2), P. 235 - 245

Published: May 1, 2023

Living systems face both environmental complexity and limited access to free-energy resources. Survival under these conditions requires a control system that can activate, or deploy, available perception action resources in context specific way. In this Part I, we introduce the principle (FEP) idea of active inference as Bayesian prediction-error minimization, show how problem arises systems. We then review classical quantum formulations FEP, with former being limit latter. accompanying II, when are described executing driven by their flow always be represented tensor networks (TNs). TNs implemented within general framework topological neural networks, discuss implications results for modeling biological at multiple scales.

Language: Английский

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Quantum computing in bioinformatics: a systematic review mapping

Briefings in Bioinformatics, Journal Year: 2024, Volume and Issue: 25(5)

Published: July 25, 2024

Abstract The field of quantum computing (QC) is expanding, with efforts being made to apply it areas previously covered by classical algorithms and methods. Bioinformatics one such domain that developing in terms QC. This article offers a broad mapping review methods QC bioinformatics, marking the first its kind. It presents an overview aids researchers identifying further research directions early stages this knowledge. work presented here shows current state-of-the-art solutions, focuses on general future directions, highlights limitations gathered data includes comprehensive list identified along descriptions, classifications, elaborations their advantages disadvantages. Results are not just descriptive table but also aggregated visual format.

Language: Английский

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More quantum chemistry with fewer qubits

Physical Review Research, Journal Year: 2024, Volume and Issue: 6(4)

Published: Oct. 7, 2024

Quantum computation is one of the most promising new paradigms for simulation physical systems composed electrons and atomic nuclei, with applications in chemistry, solid-state physics, materials science, molecular biology. This requires a truncated representation electronic structure Hamiltonian using finite number orbitals. While it is, principle, obvious how to improve on by including more orbitals, this usually unfeasible practice (e.g., because limited qubits available) severely compromises accuracy obtained results. Here, we propose quantum algorithm that improves problem virtue second-order perturbation theory. In particular, our evaluates energy correction through series time-evolution steps under unperturbed Hamiltonian. An important application go beyond active-space approximation, allowing include corrections virtual known as multireference exploit fact diagonal orbitals show independent gives rise accurate estimates without increasing qubits. Moreover, demonstrate numerically realistic chemical total runtime has highly favorable scaling compared previous studies. Numerical calculations confirm necessity theory reach ground-state estimates. Our can also be applied symmetry-adapted As such, help reduce hardware requirements chemistry. Published American Physical Society 2024

Language: Английский

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Quantum natural language processing and its applications in bioinformatics: a comprehensive review of methodologies, concepts, and future directions

Frontiers in Computer Science, Journal Year: 2025, Volume and Issue: 7

Published: Feb. 18, 2025

Quantum Natural Language Processing (QNLP) is a relatively new subfield of research that extends the application principles natural language processing and quantum computing has enabled complex biological information to unprecedented levels. The present comprehensive review analyses potential QNLP in influencing many branches bioinformatics such as genomic sequence analysis, protein structure prediction, drug discovery design. To establish correct background techniques, this article going explore basics including qubits, entanglement, algorithms. next section devoted extraction material valuable knowledge related development, prediction assessment drug-target interactions. In addition, paper also explains structural by embedding, simulation, optimization for exploring sequence-structure relationship. However, study acknowledges future discussion challenges weaknesses hardware, data representation, encoding, construction enhancement This looks into real-life problems solved from industry applications, benchmarking criteria, comparison with other traditional NLP methods. Therefore, enunciates perspectives, well developmental implementation blueprint bioinformatics. plan follows: its function achieve objectives precision medicine, design, multi-omics, green chemistry.

Language: Английский

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