Laboratory Methods and Practice: Bioanalytics, Biotechnology and Diagnostics

The paper discusses the advantages of Advanced Ion Mobility Spectrometry (AIMS) for minimally invasive sample analysis. AIMS enables the examination of samples in their native state without requiring chromatography, making it a powerful tool for molecular analysis. It highlights the technique’s efficiency and potential applications in various scientific fields.

This white paper emphasizes the importance of integrating sustainability into bioanalytical workflows, with a focus on reducing waste, optimizing resources, and balancing environmental responsibility with scientific rigor.

The paper emphasizes the shift toward patient-centric and decentralized clinical trials, focusing on innovations like point-of-care testing, low-volume sampling, and wearable devices to enhance data collection and reduce patient burden. It highlights decentralized and hybrid trial models as effective strategies to improve accessibility, inclusivity, and patient engagement while addressing logistical challenges. Additionally, the paper underscores the importance of interdisciplinary collaboration, regulatory engagement, and emerging technologies like artificial intelligence in advancing clinical trial design and operations.

Antibody-drug conjugates (ADCs) are complex therapeutic agents used in cancer treatment, requiring precise bioanalytical methods to evaluate their pharmacokinetics, efficacy, and toxicity. Liquid chromatography-mass spectrometry (LC-MS) is a key tool for ADC analysis, enabling accurate quantification of components such as payloads, linkers, total antibodies, and drug-to-antibody ratio (DAR), while addressing challenges like structural complexity and in vivo changes. The paper emphasizes the importance of method validation, including immunoaffinity purification, surrogate peptide analysis, and tailored criteria based on ICH M10 guidelines, to ensure reliable ADC bioanalysis during drug development.

This paper reviews advancements in mass spectrometry (MS)-based methods for analyzing biomarkers in two progressive diseases: Alzheimer’s disease (AD) and muscular dystrophy (MD). It highlights the use of techniques like immunocapture MS, parallel reaction monitoring (PRM), and ion mobility for detecting amyloid-beta (Aβ) peptides in AD and tryptic peptides from dystrophin (t-Dys) in MD, emphasizing their diagnostic and therapeutic monitoring potential. While MS-based methods for AD are well-established, MD biomarker analysis in biofluids remains at the proof-of-concept stage, requiring further research to improve sensitivity, selectivity, and clinical applicability.

CRISPR, originally known for its precise gene-editing capabilities, has evolved into a powerful tool for diagnostics and biosensing, enabling rapid and sensitive detection of nucleic acids, SNPs, and proteins. Technologies like SHERLOCK and DETECTR, along with innovations such as CRISPR-Chip and enzymatic systems, enhance detection efficiency and signal amplification for point-of-care diagnostics. The integration of CRISPR with AI and digital health platforms is revolutionizing precision medicine by offering scalable, cost-effective, and decentralized diagnostic solutions.

PROTACs are revolutionizing drug discovery by enabling targeted protein degradation, addressing “undruggable” proteins, and overcoming limitations of traditional inhibitors. Advances in molecular design, including ligand discovery, E3 ligase recruitment, and AI-driven modeling, are accelerating development, while innovations like PHOTACs and Ab-PROTACs enhance precision and reduce toxicity. Clinical successes in cancer treatment and expanding applications in neurodegenerative and rare diseases highlight their potential to transform precision medicine.

Mass spectrometry imaging (MSI) allows visualization of numerous analytes in biological tissues and maps time-dependent processes, offering insights into molecular mechanisms underlying tissue function. MSI-based methods can capture data ranging from enzyme-catalyzed transformations to complex metabolic networks, but integrating tissue microenvironment maps, such as oxygenation and pH, remains a challenge. Advancing MSI by pairing in vivo studies with in vitro models and combining it with imaging techniques like magnetic resonance and vibrational spectroscopy could link environmental factors to functional activities, enabling a comprehensive understanding of tissue function.

Adrenaline, a key stress biomarker, is vital for diagnosing conditions like cardiovascular, endocrine, and neurodegenerative diseases. While traditional detection methods offer high sensitivity, their complexity and cost limit point-of-care applications. Emerging biosensing technologies, including nanomaterial-enhanced electrochemical and optical sensors, provide improved sensitivity, selectivity, and portability for decentralized use.

This study refines statistical methodologies for cross-validation of bioanalytical methods in clinical trials, integrating Bland–Altman plots with equivalence testing to address limitations in traditional approaches like Deming regression and Lin’s Concordance. The proposed framework accommodates assay variability and ensures consistent, credible validation outcomes across laboratories. By improving the integrity and comparability of pharmacokinetic data, this method supports more reliable clinical trial endpoints.

This review explores challenges in bioanalytical sample preparation and highlights advancements in green sample preparation techniques that improve efficiency while promoting sustainability. Innovations in sorbents, including metal-organic frameworks, magnetic nanoparticles, natural fibers, and molecularly imprinted polymers, along with environmentally friendly solvents such as deep eutectic solvents and ionic liquids, enhance extraction selectivity and reduce toxic solvent use. By integrating these materials into bioanalytical workflows, the review supports the development of precise, environmentally friendly methodologies for drug analysis.

 The FDA’s 2025 guidance on bioanalytical method validation for biomarkers redirects to the ICH M10, which excludes biomarkers, leaving a gap in clear validation standards for biomarker assays. The 2019 Points to Consider document, developed by FDA regulators and industry experts, provides the most comprehensive framework for biomarker assay validation, emphasizing the fit-for-purpose approach based on the biomarker’s context of use. This commentary advocates for updating and expanding the 2019 framework to ensure actionable biomarker data supports regulatory submissions and advances drug development.

This study compared grade-222 and grade-226 filter-papers for dried blood spot phenylalanine measurement, finding that grade-222 demonstrated superior accuracy, precision, and reduced measurement uncertainty. Physical analysis revealed structural differences, with grade-222 lacking the amorphous material present in grade-226. Grade-222 filter-paper offers improved reliability for phenylketonuria monitoring by better distinguishing safe and harmful phenylalanine concentrations.

This article explores patient-centric sampling, a method that prioritizes patient comfort and accessibility in laboratory testing by using devices that collect blood with smaller or needle-free systems, often enabling home use. These technologies improve access for individuals in rural areas or those with transportation challenges but face barriers to widespread adoption. The article provides an overview of PCS devices, their benefits, and the challenges in making them a global standard.

This paper presents updated recommendations from the European Bioanalysis Forum on whole blood stability testing during bioanalytical method validation, addressing feedback on the ICH M10 guidelines. The recommendations emphasize assessing analyte stability immediately after blood collection to ensure accurate concentration measurements. Key considerations include defining fresh blood, equilibration times, assay types, and aligning experiments with the 3Rs principles.

The FDA’s 2025 guidance on bioanalytical method validation for biomarkers fails to address clear standards for biomarker assay validation, instead redirecting to the ICH M10, which excludes biomarkers. The 2019 Points to Consider document, developed with input from FDA regulators and industry experts, provides the most comprehensive framework for biomarker assay validation, emphasizing the fit-for-purpose approach based on the biomarker’s context of use. This commentary advocates for updating and expanding the 2019 framework to ensure actionable biomarker data supports regulatory submissions and advances drug development.

Biobanks and databases are often underutilized due to a lack of understanding of their practical applications and accessibility, leading researchers to overlook their potential. This article highlights the UK Biobank, one of the largest human biobanks, providing insights into its data, access procedures, and tips for successful applications. It aims to improve awareness and utilization of biobank resources for advancing research.

Developing efficient diagnostic tools is crucial for managing infectious diseases like Monkeypox (Mpox), and the CRISPR/Cas system offers precision and versatility for this purpose. Cas12 and Cas13, widely used in point-of-care testing, enable highly specific and sensitive detection of nucleic acids through fluorescence or colorimetric signals by targeting DNA or RNA sequences. This article explores the opportunities and challenges of implementing CRISPR-based diagnostics for Mpox detection.

Despite advancements in RNA-sequencing (RNA-seq) technologies, their application to Mycobacterium tuberculosis has been limited. This study presents a wet-lab and computational protocol optimized for RNA-seq transcriptomics, successfully detecting differential RNA expression in 11 clinical isolates exposed to pyrazinamide. The method, using low-volume cultures and optimized sequencing depth, demonstrates its suitability for RNA-seq applications in tuberculosis research.

This interview highlights how multi-omics approaches such as genomics, transcriptomics, proteomics, and metabolomics are being used to uncover molecular mechanisms underlying Alzheimer’s and Parkinson’s disease. It highlights the importance of biomarker discovery in cerebrospinal fluid and plasma, which holds promise for enabling early detection and patient stratification. This multi-omics approach connects genetic mutations with protein and metabolite changes, enabling precision medicine and improved diagnostics.

Neurological and psychiatric diseases often result from abnormal protein synthesis, where imbalances in protein production harm brain cell function. This article describes the development of a drug screening platform using the Protein Quantitation Ratioing (PQR) technique, which tracks protein expression via fluorescence in human cells modified with CRISPR-Cas9. This platform enables high-throughput drug screening to identify compounds targeting protein expression, with hits validated through PQR or animal models.

This paper presents qDATA, a software tool that automates the analysis of qRT-PCR gene expression data through a user-friendly interface. By processing raw cycle threshold (Ct) values, qDATA streamlines data analysis by performing essential calculations and statistical tests, ensuring accurate and meaningful results. Its efficiency and practical utility were validated using two published qRT-PCR datasets, demonstrating its effectiveness in gene expression research. By implementing a robust framework for analyzing data within biological samples, the software tool enhances the reliability and reproducibility of results, enabling laboratories to generate high-quality and trustworthy findings in gene expression studies.

This article evaluates the health and value of core facilities requires aligning metrics with institutional strategic priorities and using a broad range of indicators to assess their impact. Core directors should be equipped with tools for data collection, financial reporting, utilization tracking, publication tracking, and user satisfaction assessments to support informed decision-making. As core facilities play a vital role in advancing rigorous science amid funding challenges, tracking meaningful metrics underscores their importance and necessity.

 This study systematically evaluates the necessity of technical triplicates in RT-qPCR by analyzing over 71,000 cycle threshold (Ct) values, revealing that duplicate or single replicates can reliably approximate triplicate means, reducing reagent use, labor, and time. Variability was assessed across operators, instruments, and detection chemistries, showing dye-based detection had higher variability than probe-based, while operator expertise and calibration timing had minimal impact. These findings challenge traditional assumptions about RT-qPCR variability, offering a data-driven framework for optimizing experimental design and enabling resource savings without compromising data quality.

This study used digital PCR to quantify the stability of select miRNAs in human plasma during progressive thawing and ambient temperature storage, revealing a general decline in miRNA concentrations. miR-150-5p and miR-517a-3p were the least stable, degrading by 32% and 52% respectively after 24 hours, with sensitivity unrelated to GC content or initial abundance. The findings suggest that factors like protein interactors and vesicle carriers may influence miRNA stability during temperature fluctuations.

This paper presents a practical RNA-sequencing (RNA-seq) method designed specifically for studying Mycobacterium tuberculosis, which has been challenging to analyze using RNA-seq. The approach uses a streamlined RNA extraction process to produce high-quality RNA from small cultures, making it easier to study gene expression in clinical isolates. By successfully detecting changes in RNA expression in samples exposed to pyrazinamide, this method shows promise for understanding drug responses and advancing research in tuberculosis within clinical microbiology.

The paper describes the development of a highly specific anti-pan-N-formylmethionine antibody to detect fMet-bearing proteins, a hallmark of bacterial protein synthesis. This tool enhances the ability to study bacterial presence and host immune responses, as fMet peptides act as chemoattractants during infection. Its improved sensitivity and cross-species applicability hold promise for diagnostic assays and research into bacterial pathogenesis. 

The study explores the potential of biobanked cervical screening samples for RNA-based research, revealing that even after extended storage, these samples can yield analyzable RNA despite signs of degradation. This underscores their value in advancing molecular investigations, including those relevant to histopathology, particularly for assessing biomarkers linked to disease risk.

This study introduces SC-YOLO, a deep learning framework that automates spermatogenic cell classification, reducing reliance on the complex and subjective Johnsen score. By capturing detailed texture and shape features and simplifying scoring criteria, it improves diagnostic accuracy and efficiency in evaluating azoospermia. This approach demonstrates the potential of AI-driven methods to standardize and accelerate assessments in reproductive health.

This paper explores how organoids are advancing laboratory research by providing realistic models for disease studies, drug testing, and regenerative medicine. It addresses challenges such as reproducibility, cellular diversity, and vascularization while highlighting innovations like co-culture systems, organoid-on-chip platforms, and 3D bioprinting. These developments require specialized skills in stem cell culture and bioengineering, making organoid technology a key component of future lab workflow.