Laboratory medicine is an essential part of the diagnostic process, supporting clinical decisions, guiding and addressing therapy. The recent COVID-19 pandemic illustrated well the key role of laboratory medicine in the diagnosis, management and prognosis of SARS-CoV-2 infected patients. Technological advances improved the laboratory diagnosis and patients’ management and others appear very promising as clustered regularly interspaced short palindromic repeats (CRISPR) or artificial intelligence (AI). This review describes the current diagnostic assays routinely used in laboratory as well as the novel technologies not in routine yet but that represent future directions and will probably dominate the laboratory in the next years. Serology is important for detecting antibodies and/or antigens of the infectious pathogens or for epidemiological purposes, while real-time PCR with its high sensitivity and specificity has a key role in pathogen detection in different biological matrices and in monitoring the therapy. Nanochip-based technologies make possible delivering a laboratory report at the patient’s bed or in settings where a laboratory-based hospital is not available. Next generation sequencing (NGS) is a massively high throughput parallel sequencing technology that allows the simultaneous sequence of billions of DNA fragments in a short time frame. This technology can be used to detect drug-associated mutations, minority species within an infected patient or for pathogen identification. CRISPR-based technology is a fast and accurate diagnostic method that can be applied to different human diseases including infectious diseases. Artificial intelligence is increasingly used in laboratory medicine. In clinical microbiology, it is used to build up diagnosis analyzing genomic information or mass spectra from isolated bacteria, for predicting antibiotic sensitivity or for processing in a short time a large number of images with meaningful results. Thus, the laboratory is becoming increasingly automated and interwoven with sophisticated software or algorithms that will increase the sensitivity and specificity of diagnoses, besides reducing time to results.

Mass spectrometry (MS) is an analytical technique for molecular identification and characterization, with applications spanning various scientific disciplines. Despite its significance, MS faces challenges in widespread adoption due to cost constraints, instrument portability issues, and complex sample handling requirements. In recent years, 3D printing has emerged as a technology across industries due to its cost-effectiveness, customization capabilities, and rapid prototyping features. This review explores the integration of 3D printing with MS technology to overcome existing limitations and enhance biomedical analysis capabilities. We first categorize mainstream 3D printing methods and assess their potential in MS applications. We also discuss their roles in different MS categories such as liquid chromatography mass spectrometry (LCMS), gas chromatography mass spectrometry (GCMS), ambient ionization mass spectrometry (AIMS), and matrix-assisted laser desorption/ionization MS (MALDI MS) in biomedical research. Additionally, we highlight the current challenges and future research directions for advancing 3D printing-assisted mass spectrometry, emphasizing its role in enabling portable, cost-effective, and customized MS solutions for biomedical analysis.

This work marks the first practical use of boson sampling, long seen as a key demonstration of quantum computing’s potential to outperform classical methods.

The researchers used computer simulations to model a quantum optical experiment that recognizes images using just three photons, successfully identifying images from several well-known datasets.

This paves the way towards future applications of quantum AI in complex image recognition, and represents a step toward low-resource, energy-efficient quantum computing.