Optically pumped magnetometers (OPMs) enabling contactless, flexible retinal diagnostics, reducing discomfort and movement artefacts, potentially matching traditional methods’ reliability while improving accuracy and patient comfort in vision research and eye disease assessment.

Quantum computing enables precise simulation of molecular interactions and quantum machine learning to predict drug toxicity early, reducing late-stage failures, accelerating approvals, and improving drug safety and efficacy.

Quantum computing reframes mRNA structure prediction as a binary optimisation problem, efficiently finding minimum free energy structures. This accelerates RNA-based drug design, overcoming classical limitations and driving breakthroughs in healthcare and advanced therapeutics.

Quantum machine learning predicting CAR T-cell efficacy from limited data, guiding experimental focus to the most promising designs, accelerating development, reducing costs, and enabling exploration of novel, effective immunotherapy combinations.

Quantum computing optimizing clinical trial design by efficiently exploring complex variables, improving patient selection, dosage, and protocols, reducing costs and duration, and enabling faster, more precise, and personalized treatments.

Quantum computing enabling precise simulation of photosensitizers’ excited-state dynamics, improving photodynamic drug design, accelerating discovery, and creating new cancer and infection treatments previously too complex for classical methods.

Quantum computing optimizing drug manufacturing and pricing by efficiently handling complex, multi-variable challenges, enhancing supply chains, production, and dynamic pricing, leading to cost-efficient, agile, and accessible drug development globally.

Magnetocardiograms (MCGs) using quantum sensors to measure the heart’s magnetic fields contactlessly, enabling faster, more comfortable, and highly accurate diagnostics compared to ECGs. Enhancing efficiency, detects subtle conditions, and enables versatile applications from home monitoring to in-vehicle health tracking.

Quantum sensors that can detect subtle magnetic signals from both surface and deep muscles, enabling more natural prosthetic control than myoelectric sensors. Future brain-computer interface applications could further enhance precision and offer unprecedented prosthesis control.

Quantum computing accelerating risk measure calculations for insurers, enabling faster, more accurate premium setting and reserve management through quantum amplitude estimation of expectiles and Range Value-at-Risk.

Quantum-inspired digital annealing optimizing emergency patient allocation in hospitals, reducing bottlenecks and wait times, improving patient flow, and enhancing overall healthcare efficiency.

Quantum algorithms like VQE, QAOA, and quantum annealing accelerating protein folding and drug interaction predictions, improving energy estimation, ligand docking, and aiding protein design, drug discovery, and understanding biological behavior.

SQUID-based MRI enabling affordable, portable imaging using weak magnetic fields, eliminating complex infrastructure. This allows early disease detection and treatment on a global scale, improving outcomes and healthcare accessibility.

Quantum optimisation and quantum machine learning can accelerate medical image analysis, improving reconstruction, classification, and neuroimaging alignment, enabling faster, more accurate diagnostics and large-scale brain studies for personalised treatment.

Quantum neural networks and solvers enabling efficient, scalable modeling of complex, nonlinear brain-genetics-behaviour dynamics, offering deeper insights for digital phenotyping and improved clinical decision-making.

A diamond-based quantum sensor tracks free radicals in real time within single mitochondria, enabling precise mapping of oxidative stress and advancing understanding of cell function, disease progression, and targeted treatment development.

Quantum sensing with NV-centre diamond magnetometry enables non-invasive protein structure and dynamics analysis under physiological conditions, revealing nanoscale details and movements, advancing disease understanding, drug design, and therapeutic target discovery.

Optically Pumped Magnetometers enabling wearable, high-resolution MEG without cryogenics, allowing natural movement, closer scalp measurements, and more affordable, accessible brain monitoring for research and disease prevention.

Graphene quantum dots (GQDs) enabling targeted cancer therapy via photothermal and photodynamic effects, enhancing tumour destruction while minimizing healthy tissue damage, potentially advancing precision drug delivery and personalized treatment strategies.

Quantum machine learning accelerates drug discovery by generating molecules, screening vast libraries, and improving safety predictions, enabling faster, cost-efficient identification of effective drug candidates with higher hit rates.

Quantum Machine Learning, using QLSTM and variational quantum circuits, improves drug retrosynthesis by predicting reactions with higher accuracy (80% vs. 70%), accelerating complex drug development and overcoming classical method limitations.

Quantum Neural Networks (QNNs) analyzing clinico-demographic and real-world data to forecast individual treatment effectiveness, supporting precision medicine and improving patient outcomes, with early studies showing promising results.

NV-based magnetometry enabling nanoscale NMR under ambient conditions, allowing high-resolution analysis of tiny samples, single cells, and proteins, advancing metabolomics, disease diagnosis, and drug discovery beyond traditional NMR limits.