Italian Society of Clinical Pathology and Laboratory Medicine (SIPMeL) guidelines on the use of autoantibody tests in the diagnosis of autoimmune liver diseases.

Salivary phosphate: A promising non-invasive biomarker for oral and systemic disease screening.

The rapid advance in the research and development of extracellular vesicle (EV)-based therapeutics has stimulated a paradigm shift in the field of regenerative medicine. However, translating EV-based therapies into the clinic requires robust, scalable, and Good Manufacturing Practice (GMP)-compliant bioprocesses that ensure product consistency, potency and safety. In this Perspective, we propose that metabolomics, particularly by using high-resolution nuclear magnetic resonance (NMR), can serve as a transformative analytical technology in EV manufacturing and quality control. By integrating NMR-metabolomics monitoring into upstream cell culture and downstream EV purification workflows, it becomes possible to identify metabolic fingerprints predictive of cell performance, EV yield and EV bioactivity. Drawing from the experience of the GALVANO consortium, which is developing Spain's first GMP-grade platform for EV manufacturing from clinical-grade human Wharton Jelly's mesenchymal stromal cells (WJ-MSC-EVs) with particular promise in the modulation of inflammation and tissue regeneration, we highlight how NMR-metabolomics can support Quality by Design (QbD) principles, enhance in-process analytics and accelerate regulatory harmonisation. We further discuss the need for collaborative standardisation of analytical methods and reporting frameworks to ensure reproducibility and comparability across EV batches. Together, these strategies can advance EV-based therapeutics toward reliable, large-scale clinical application.

The ubiquitous presence of microplastics (MPs, < 5mm) and nanoplastics (NPs, < 1μm) in food systems has raised serious concerns regarding food safety and human health. Accurate detection and quantification, however, remain formidable challenges due to the complexity of food matrices, particle heterogeneity, and the lack of harmonized analytical protocols. This review critically examines the emerging analytical technologies that are reshaping the detection landscape of MPs and NPs in food. Emphasis is placed on next-generation methods-including stimulated Raman scattering (SRS) microscopy, surface-enhanced Raman spectroscopy (SERS), hyperspectral imaging (HSI), and microfluidic-nanodroplet platforms-along with artificial intelligence (AI)-assisted analytical frameworks that enable automated identification and classification. The mechanisms by which lipids, proteins, and other food components interfere with nanoscale detection are systematically discussed, highlighting the need for improved pretreatment and matrix-deconvolution strategies. Moreover, we identify persistent gaps in reference materials, quantification standards, and interlaboratory comparability. Looking forward, future progress will depend on the co-development of operational definitions, fit-for-purpose analytical workflows, AI-assisted data interpretation, and reference-material-based interlaboratory validation systems. In this way, methodological innovation can be more effectively translated into reliable food safety assessment and regulatory implementation.

Manufacturing process development strategies for high concentration biologic drug products: from downstream processing to fill-finish.

The second-generation lipid-based nanocarrier system, nanostructured lipid carriers (NLCs), has received much attention due to their distinct properties that enable them to address the various limitations that afflict both solid lipid nanoparticles and the conventional delivery system. The special structure (solid lipids/liquid lipids blend) of NLCs provides a better encapsulation, stability, controlled release, and biocompatibility of drugs, therefore, leading to the effective transportation of hydrophilic and lipophilic drugs. This review briefly examines the design methods, formulation strategies, and other more sophisticated characterization methods, such as traditional characterization (e.g., dynamic light scattering (DLS) and X-ray diffraction) and new methods (e.g., cryo-EM and small-angle X-ray scattering (SAXS) that provide an effect on particle size, lipid crystallinity, and release kinetics. The review notes Process Analytical Technology (PAT) and its ability to aid the real-time monitoring and scale-up production of NLC products. Recent dosage forms that have been used as therapeutic agents that involve the use of NLCs are critically discussed, such as the following routes of administration: oral, transdermal, nasal, ocular, pulmonary, and targeted delivery. Moreover, we will review how NLCs can serve to improve bioavailability, enhance patient compliance, and provide sitespecific action of drug delivery. A recent analysis of patents is reviewed to identify where innovative space is being created regarding surface functionalization, hybrid systems, and combinatorial therapies, as well as the challenges faced, such as regulatory implications and translational opportunities. This work provides a summary of the formulation science, characterization methods, and patent data to offer an overview of the current state and prospective future work of NLCs with respect to drug targeting, delivery, and the nanomedicine field.

Rapid bloodstream infection diagnosis is essential to enable timely targeted therapy, to reduce the risk of progression to sepsis, to limit unnecessary antimicrobial exposure, and to support effective antimicrobial stewardship. However, conventional culture-based workflows in routine practice often require 48-72 hours to deliver organism identification and antimicrobial susceptibility testing (AST) results. This review summarises rapid AST analytical technologies for bloodstream infections, including commercial systems and emerging phenotypic and molecular methods that aim to shorten time to actionable susceptibility information to less than 8 hours from a positive blood culture. Phenotypic platforms are to be preferred, and they are compared and reviewed according to their dominant analytical principle, while the role of genotypic assays for early identification and resistance inference is discussed as a complementary strategy. Across approaches, sample preparation, including bacterial enrichment and matrix removal, emerges as the dominant limitation, while speed and organism-antibiotic coverage shape clinical utility and implementation. Progress of rapid AST platforms toward routine adoption will require streamlined sample preparation, broader panels, and robust evidence of clinical benefit and cost-effectiveness.

Maintaining consistent quality in the manufacturing of biotherapeutic proteins in mammalian cell culture is challenging, with unplanned deviations causing inconsistencies and potential batch failure. Current methods for monitoring and controlling critical process parameters (CPPs) rely on slow, labor-intensive offline analyses. This is particularly problematic in upstream manufacturing, where infrequent measurements hinder real-time CPP monitoring and result in suboptimal control. This study developed and implemented a robust, standardized framework that integrates Raman spectroscopy with real-time machine learning models and bioreactor control via OPC-UA, enabling seamless communication and effective control of mammalian cell culture CPPs. High-accuracy ML models (R2 >0.92) enabled real-time monitoring of glucose, lactate, viable cell density, and antibody titre. The glucose model was integrated into an automated process analytical technology (PAT) control strategy to maintain glucose at a predefined setpoint. The PAT strategy was compared to a manual bolus glucose control under high and low glucose feeding regimes. The PAT control approach observed an increase in biotherapeutic product titre by up to 35% and reduced glycation by up to 27%. These results indicated that both glucose setpoints and fluctuations impacted cell culture performance. In conclusion, this study highlighted the value of PAT tools in automating control loops, consequently improving process performance with enhanced productivity and quality.

Azole antifungals remain central to the management of superficial and systemic mycoses, yet the growing global incidence, rising resistance, and persistent treatment failures highlight the need for improved oral formulations. Current azole products are predominantly capsules or liquid preparations that have well-documented limitations with patient adherence and bioavailability. Traditional formulation efforts have relied heavily on crystalline solid forms because of their predictable behavior and established manufacturing pathways. However, this long-standing preference has restricted exploitation of alternative solid-state strategies capable of meaningfully improving aqueous solubilitya key determinant of oral bioavailability. Advances in analytical technologies have broadened interest in amorphous and coamorphous systems, but issues such as instability, hygroscopicity, and unpredictable dissolution behavior continue to limit their reliability. This review explores the expanding field of supramolecular solid-state design for azoles, with a focus on noncrystalline forms, particularly eutectic mixtures, as an underutilized but highly promising formulation approach. Eutectic systems occupy a unique microcrystalline space between the high solubility amorphous forms and the stable crystalline solids, offering enhanced solubility without the need for polymeric stabilizers that often complicate amorphous formulations. Despite more than six decades of sporadic investigation, their pharmaceutical potential remains considerably underexplored, especially for BCS II compounds, such as azoles. By consolidating current knowledge on azole solid-state chemistry, highlighting the limitations of existing formulation strategies, and evaluating the emerging rationale for intentional eutectic design, this review positions eutectic mixtures as a viable and impactful pathway for developing next-generation azole formulations with improved oral bioavailability and therapeutic performance.

FAHFAs: structures, distribution, analytical methods, and health implications.

The manufacture of monoclonal antibody (mAb) therapeutics relies on stringent downstream processing, where low-pH viral inactivation (VIN) safeguards against enveloped viruses. Here we introduce simultaneous absorbance, polarized intrinsic emission, and scattering (APIES) measurements as a rapid (<1 min), robust analytical platform for real-time assessment of protein aggregation, concentration, and tertiary structural integrity during VIN. Dual excitation wavelengths (280 and 350 nm), multichannel detection, and parallel polarizers provide high sensitivity for aggregation monitoring. APIES provides three orthogonal readouts: protein concentration via A280, aggregation by an aggregation index (AggIndex = (A350/(A280 - A350)) × 100), Rayleigh-to-fluorescence ratios (IR/IF), and large tertiary structure changes (e.g., unfolding) via an intrinsic emission ratio (I350/I330). We evaluated APIES using a bovine IgG model (∼1 mg mL-1) undergoing simulated VIN at pH 3.4, 3.6, and 3.8 for 8 h. Measurements were acquired hourly using APIES, dynamic light scattering (DLS), and absorbance spectroscopy, with offline size exclusion chromatography (SEC) after sample neutralization. Under all pH conditions, DLS and APIES confirmed extensive increases of in-vessel aggregation, with AggIndex and IR/IF strongly correlating with DLS determined aggregate content (R2 > 0.9). However, SEC only showed an increase in irreversible aggregates (of ∼5% after 8 h) at pH 3.4, with no increase for pH 3.6 or 3.8. This highlights a limitation of SEC for in-process monitoring and shows that APIES better monitors in-vessel aggregation. Furthermore, APIES, via AggIndex and IR/IF ratio scatter plots, potentially distinguishes between reversible from irreversible aggregation pathways. Repeating these experiments using a flowcell over 3 h, with 1 min APIES measurement sampling intervals, confirmed that APIES was suitable for online aggregation monitoring. Overall, APIES is a simple, fast, and sensitive process analytical technology for real-time protein aggregation monitoring during industrial processes like VIN.

Approximately three decades ago, in response to the growing demand for rapid and sensitive analysis of small-volume samples, monolithic column technology emerged contemporaneously with other key concepts in analytical chemistry, such as the micro-total analysis system (µTAS) and lab-on-a-chip technology. These innovations attracted considerable attention as paradigm-shifting tools in the field. In the post-genomic era in particular, where miniaturization and high-throughput workflows became critical, monoliths-characterized by their continuous porous structure, high permeability, and low back pressure-were recognized as next-generation separation media, especially in omics-driven research. However, subsequent advances in liquid chromatography-most notably the development of core-shell particle packing materials and the widespread adoption of ultra-high-performance liquid chromatography (UHPLC)-gradually diminished the relative advantages of monolithic columns in standard high-throughput HPLC applications. Despite this shift, their intrinsic features, including ease of fabrication, outstanding flow properties, and flexible moldability into diverse formats, have continued to generate new value. In recent years, applications of monoliths have expanded beyond analytical separations into diverse fields, including biopharmaceutical purification (e.g., antibody drugs), solid-phase extraction, immobilized catalytic systems, and integration into micro- and nanoscale devices. This review provides a comprehensive overview of the three-decade evolution of monolithic column technology, highlighting its historical context, current applications, and emerging roles in both analytical and preparative sciences within the broader context of evolving analytical technologies.

Traditional off-line analysis methods to quantify residual metabolite concentrations in a drug substance fermentation process consume valuable time, require costly resources, and demand potentially hazardous manual operations when working with pathogenic biological organisms. This case study focuses on the successful method development and validation of Raman spectroscopy as an in-line process analytical technology (PAT) to replace the existing off-line assay for real-time glucose quantification. The value and feasibility of Raman spectroscopy as an in situ PAT method are recognized and demonstrated as an enabling technology suited to mitigate challenges fundamental to lab-scale process development and commercial manufacturing. Herein, application of chemometric techniques and multivariate analysis of Raman spectral data is described to develop a partial least squares model capable of predicting real-time and accurate glucose concentrations with a root mean square error of prediction of 1.2 g/L. Through this work, the predictive Raman PAT glucose quantification method was validated to make process decisions in a commercially licensed Pneumococcal vaccine drug substance manufacturing facility for the first time at our company. The method was integral to the process control strategy and applied to accurately and robustly indicate the glucose concentration target ± 2 g/L for triggering subsequent process operations. Several advantages were realized through this work including advanced process control, reduced operating costs, and improved safety posture.

Exposure to ionizing radiation has been associated with the development of neoplasms in humans and other animals. Detection of both neoplastic growth and effects of radiation with standard laboratory testing (hematology and serum chemistry analyses) is problematic. There are no specific biomarkers present in biological fluids (blood, urine) for early detection of neoplastic growth or long-term effects of radiation exposure, but these would be extremely useful for monitoring both treatment efficacy and detecting undesirable side effects in patients undergoing radiotherapy. We conducted a retrospective study of 76 urine samples from rhesus macaques using a novel Raman spectroscopy-based analytical technology (Raman Molecular Urinalysis) to establish a urine fingerprint for past radiation treatment. Forty-nine animals were irradiated (of which 12 developed sarcomas following experimental exposure to total body ionizing radiation) and 27 animals were not irradiated (2 of which developed non-radiation-associated sarcomas). We applied an unsupervised principal component analysis and supervised discriminant analysis of principal components and averaged the spectra. The results showed the groups had a highly similar average spectra, but more variability and outliers existed in the irradiated group of animals. The unique characteristics of these outliers were unclear, and further investigation is needed. Animals with sarcomas had a distinct spectral profile with high specificity and high negative predictive value. A definitive radiation molecular spectral fingerprint was not identified in the urine of irradiated macaques in comparison to unirradiated control animals, but this study provides initial evidence and insights for future research.

Magnetic sensing technologies: Principles and recent advances in food safety analysis.

ISO 14644-1 defines ISO-8 cleanrooms, often found in pharmaceutical manufacturing facilities, by maximum allowable concentrations of airborne particles at specified threshold sizes (commonly ≥0.5 μm and ≥5.0 μm) within a classification particle size range of 0.1-5 μm. For ISO Class 8, though ISO 14644- 1 lists sizes from 0.1 to 5.0 μm, classification commonly uses the operationally relevant limits of ≥0.5 μm and ≥5.0 μm. While ISO classification establishes a compliance boundary, it does not fully leverage modern optical particle counter (OPC) time series data to detect early environmental degradation driven by controllable operational factors in non-sterile areas (traffic, door cycling, material handling, and housekeeping drift). FDA's Process Analytical Technology (PAT) guidance combined with Quality by Design (QbD) principles, promotes timely measurement, enhanced process understanding, and multivariate/statistical approaches to manage variability proactively. This paper proposes a PAT aligned framework for installing and operating particle counting systems in ISO-8 non-sterile controlled areas to detect pre-limit particle size distribution (PSD) shifts. The approach integrates (i) risk-based monitoring network design, (ii) PSD-shift features (coarse to fine ratios, event rate, recovery time, persistence) that translate raw counts into actionable change signals, and (iii) statistical change detection (EWMA/CUSUM) to distinguish transient events from sustained shifts. One thing which is often overlooked is physical collection issues, especially when pulling samples through long tubes or curved lines. Particles at 5 microns or more tend to drop out under those conditions, skewing results noticeably. So this guidance covers considerations for choosing particle counters and where to place ports for truer readings. Instead of waiting until thresholds breach, the system proposed in this article acts earlier using feedback loops tied directly to control actions there by providing a robust continuous monitoring system.

The manufacturing of cysteine-based antibody-drug conjugates (ADCs) requires precise control of the drug-to-antibody ratio (DAR), a critical quality attribute influencing product safety and efficacy. Conventional analytical techniques used for DAR determination, such as hydrophobic interaction chromatography (HIC) and reversed-phase high-performance liquid chromatography (RP-HPLC), are low-throughput and unsuitable for real-time process monitoring, limiting process development efficiency. To address this challenge, we developed a high-throughput size-exclusion chromatography-mass spectrometry (SEC-MS) workflow with and without postcolumn denaturation (PCD) functionality, enabling real-time monitoring of both reduction and conjugation kinetics during cysteine-based ADC manufacturing. Using a short SEC column coupled to a mass spectrometer, analysis time can be performed under 2 min per sample. This workflow was applied to rapidly optimize critical process parameters, including reductant concentration and pH during reduction, and drug-linker ratio during conjugation. The approach provided deeper mechanistic insights into reaction kinetics and supports process analytical technology (PAT)-enabled strategies for advanced process control. Overall, this high-throughput SEC-MS workflow accelerates ADC development while improving manufacturing robustness.

Understanding chemical reactions is central to pharmaceutical and chemical development, and nuclear magnetic resonance (NMR) spectroscopy is increasingly attractive for reaction analysis because it provides direct structural insight and quantitative information without dependence on response factors. However, conventional high-field NMR instruments are rarely located in chemistry laboratories due to demanding infrastructure requirements and reliance on liquid cryogens. Recent advances in cryogen-free magnet technologies address this limitation and enable practical deployment of NMR directly in laboratory and manufacturing environments. This work evaluates cryogen-free NMR as a process analytical technology (PAT) by comparing a 400-MHz high-temperature superconducting (HTS) magnet NMR system with an 80-MHz benchtop NMR instrument. Two representative reactions were studied: a ring-closing metathesis reaction and the transesterification of a pinacol arylboronic ester to an aryl triolborate. The comparison focuses on data quality, the ability to extract kinetic and speciation information, and the strengths and limitations of each platform for complex reaction monitoring. Results demonstrate that both cryogen-free systems can deliver meaningful reaction insights, including in cases with overlapping NMR signals, while offering distinct technical advantages. The higher-field HTS system provides improved resolution and analytical capability, whereas the benchtop instrument offers simplicity, accessibility, and ease of integration. Overall, cryogen-free NMR instruments lower barriers to adoption, eliminate liquid-cryogen's requirements, and expand the use of NMR for routine reaction monitoring. These technologies enable broader application of NMR-based PAT, and support more informed decision-making in chemistry laboratories and manufacturing settings across diverse reaction types and operational scales worldwide.

Glucose is a critical nutrient in mammalian cell culture processes, influencing cellular metabolism, productivity, and product quality. In industrial Chinese hamster ovary (CHO) fed-batch processes, glucose concentrations are commonly controlled using manual offline measurements and operator-based feed adjustments. Although online Process Analytical Technology (PAT) solutions and oxygen uptake rate (OUR)-based feeding approaches have previously been investigated, their implementation in existing Good Manufacturing Practice (GMP) manufacturing environments remains challenging due to instrumentation, validation, and process integration requirements. In this study, the relationship between cumulative oxygen consumption and glucose utilization was investigated across 58 CHOK1SV GS-KO® fed-batch cultures performed in stirred glass and single-use bioreactors ranging from 10 L to 2 kL scale. Building on previously reported oxygen-based glucose estimation concepts, a lactate-adjusted framework was developed to account for both lactate production and re-consumption during the fed-batch process. Oxygen transfer rates were calculated from standard online process parameters and integrated over time to determine cumulative oxygen consumption, which was subsequently correlated with cumulative glucose utilization. The results demonstrated robust linear correlations between cumulative oxygen consumption and lactate-adjusted cumulative glucose utilization across different projects, cell lines, and process scales (R2 ≥ 0.984). Incorporation of lactate metabolism improved the robustness of the oxygen-glucose relationship, particularly during metabolic transitions associated with lactate re-consumption. The predictive capability of the framework was further evaluated in three 200 L fed-batch processes by prospectively estimating glucose consumption over sequential 24h intervals using cumulative oxygen consumption and routine offline metabolite measurements. Overall, the study demonstrates that cumulative oxygen consumption provides a robust and scalable basis for oxygen-based soft-sensing of glucose demand in industrial CHO fed-batch cultures. The presented framework enables predictive glucose demand estimation using standard bioreactor process data without requiring additional glucose-specific PAT hardware and may support future implementation of automated feeding concepts in mammalian cell culture processes. KEY POINTS: • Cumulative oxygen consumption correlates linearly with glucose utilization. • Lactate-adjusted O₂-glucose correlations are consistent across bioreactor scales. • Glucose control can be automated using existing bioreactor process data.

Carbon capture plays a crucial role in both climate mitigation and carbon-based analytical technologies involving gas-liquid separation. Nanoporous graphene membranes (NGMs) provide an atomically thin platform for studying CO2 transport. Here, using all-atom molecular dynamics simulations, we investigate the CO2 transport mechanism through NGMs at the gas-liquid interface. We show that pore-edge electrostatics strongly modulate interfacial hydration. Surface charges and polar functional groups promote water accumulation near the pore mouth and suppress CO2 transport, whereas hydrophobic pores reduce water blockage and enhance permeance. By comparing pristine, H-terminated, charged, and functionalized pores, we identify interfacial hydration as a key factor governing transport at the gas-liquid interface. Contrary to the common expectation that stronger electrostatic interactions facilitate CO2 transport, our results show that enhanced electrostatics strengthen interfacial hydration and thereby suppress transport, limiting the performance of carbon-based analytical technologies that require precise detection.