High-throughput liquid chromatography/mass spectrometry method for the quantitation of small molecules using accurate mass technologies in supporting discovery drug screening

Development of a Predictive Multiple Reaction Monitoring (MRM) Model for High-Throughput ADME Analyses Using Learning-to-Rank (LTR) Techniques

Multiple Reaction Monitoring (MRM) is an important MS/MS technique commonly used in drug discovery and development, allowing for the selective and sensitive quantification of compounds in complex matrices. However, compound optimization can be resource intensive and requires experimental determination of product ions for each compound. In this study, we developed a Learning-to-Rank (LTR) model to predict the product ions directly from compound structures, eliminating the requirement for MRM optimization experiments. Experimentally determined MRM conditions for 5757 compounds were used to develop the model. Using the MassChemSite software, theoretical fragments and their mass-to-charge ratios were generated, which were then matched to the experimental product ions to create a data set. Each possible fragment was ranked based on its intensity in the experimental data. Different LTR models were built on a training split. Hyperparameter selection was performed using 5-fold cross validation. The models were evaluated using the Normalized Discounted Cumulative Gain at top k (NDCG@k) and the Coverage at top k (Coverage@k) metrics. Finally, the model was applied to predict MRM conditions for a prospective set of 235 compounds in high-throughput Caco-2 permeability and metabolic stability assays, and quantification results were compared to those obtained with experimentally acquired MRM conditions. The LTR model achieved a NDCG@5 of 0.732 and Coverage@5 of 0.841 on the validation split, and its predictions led to 97% of biologically equivalent results in the Caco-2 permeability and metabolic stability assays.

Challenges in LC-MS-based metabolomics for Alzheimer's disease early detection: targeted approaches versus untargeted approaches

BACKGROUND

Alzheimer's disease (AD) is one of the most common causes of dementia in old people. Neuronal deficits such as loss of memory, language and problem-solving are severely compromised in affected patients. The molecular features of AD are Aβ deposits in plaques or in oligomeric structures and neurofibrillary tau tangles in brain. However, the challenge is that Aβ is only one piece of the puzzle, and recent findings continue to support the hypothesis that their presence is not sufficient to predict decline along the AD outcome. In this regard, metabolomic-based techniques are acquiring a growing interest for either the early diagnosis of diseases or the therapy monitoring. Mass spectrometry is one the most common analytical platforms used for detection, quantification, and characterization of metabolic biomarkers. In the past years, both targeted and untargeted strategies have been applied to identify possible interesting compounds.

AIM OF REVIEW

The overall goal of this review is to guide the reader through the most recent studies in which LC-MS-based metabolomics has been proposed as a powerful tool for the identification of new diagnostic biomarkers in AD. To this aim, herein studies spanning the period 2009-2020 have been reported. Advantages and disadvantages of targeted vs untargeted metabolomic approaches have been outlined and critically discussed.

Detection and quantification of Covid-19 antiviral drugs in biological fluids and tissues

Since coronavirus disease 2019 (COVID-19) started as a fast-spreading pandemic, causing a huge number of deaths worldwide, several therapeutic options have been tested to counteract or reduce the clinical symptoms of patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Currently, no specific drugs for COVID-19 are available, but many antiviral agents have been authorised by several national agencies. Most of them are under investigation in both preclinical and clinical trials; however, pharmacokinetic and metabolism studies are needed to identify the most suitable dose to achieve the desired effect on SARS-CoV-2. Therefore, the efforts of the scientific community have focused on the screening of therapies able to counteract the most severe effects of the infection, as well as on the search of sensitive and selective analytical methods for drug detection in biological matrices, both fluids and tissues. In the last decade, many analytical methods have been proposed for the detection and quantification of antiviral compounds currently being tested for COVID-19 treatment. In this review, a critical discussion on the overall analytical procedure is provided, i.e (a) sample pre-treatment and extraction methods such as protein precipitation (PP), solid-phase extraction (SPE), liquid-liquid extraction (LLE), ultrasound-assisted extraction (UAE) and QuEChERS (quick, easy, cheap, effective, rugged and safe), (b) detection and quantification methods such as potentiometry, spectrofluorimetry and mass spectrometry (MS) as well as (c) methods including a preliminary separation step, such as high performance liquid chromatography (HPLC) and capillary electrophoresis (CE) coupled to UV-Vis or MS detection. Further current trends, advantages and disadvantages and prospects of these methods have been discussed, to help the analytical advances in reducing the harm caused by the SARS-CoV-2 virus.

Simultaneous Quantitation of Seven Phenethylamine-Type Drugs in Forensic Blood and Urine Samples by UHPLC-MS/MS

Abuse of new psychoactive substances (NPSs) has become a health and social issue of global concern. p-Methoxyamphetamine (PMA)/p-methoxymethamphetamine (PMMA) with fluoro- or chloro-derivatives of amphetamine and methamphetamine were among the most common drugs found in specimens from fatal cases in Taiwan during the January 2011 to December 2018 period. A liquid-liquid extraction sample preparation protocol with highly sensitive ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) approach was developed for the simultaneous analysis of seven phenethylamine-type drugs - PMA, PMMA, p-methoxyethylamphetamine (PMEA), 4-fluoroamphetamine (4-FA), 4-fluoromethamphetamine (4-FMA), 4-chloroamphetamine (4-CA), and 4-chloromethamphetamine (4-CMA) - in postmortem blood and urine specimens. Separation by liquid chromatography was performed by Agilent Zorbax SB-Aq column. Tandem mass spectrometry was operated in Agilent Jet Stream Technology electrospray ionization in positive-ion multiple reaction monitoring (MRM) mode. An analytical methodology was evaluated using drug-free blood and urine after fortification with 100-2000 ng/mL of the seven target analytes. Average extraction recoveries were >80%; slightly higher ion suppression was observed for PMA and 4-CA; intra-/inter-day precision (%CV) and accuracy were in the ranges of 0.52-12.3% and 85-110%, respectively. Limit of detection (LOD) and lower limit of quantitation (LLOQ) for these seven analytes were both in the 0.5-5 ng/mL range. Interference and carryover were not significant. This relatively simple methodology was found effective and reliable for routine identification and quantitation of these seven analytes in postmortem and antemortem blood and urine specimens received in 2018. Analytical data obtained from these actual cases indicated: (i) compared to findings reported during the 2007-2011 period, the use of substituted phenethylamine-type drugs decreased in 2018; (ii) ketamine and 7-aminonimetazepam (the main metabolite of nimetazepam) were the most common co-ingested substances in specimens containing PMA/PMMA, 4-FA/4-FMA, or 4-CA/4-CMA; and (iii) in drug fatalities, the concentration of PMA was significantly higher than the concentration of PMMA in both urine and blood, while the reverse was true in urine specimens from antemortem cases.

Advances in glycosaminoglycan detection

BACKGROUND

Glycosaminoglycans (GAGs) are negatively charged long linear (highly sulfated) polysaccharides consisting of repeating disaccharide units that are expressed on the surfaces of all nucleated cells. The expression of GAGs is required for embryogenesis, regulation of cell growth and proliferation, maintenance of tissue hydration, and interactions of the cells via receptors. Mucopolysaccharidoses (MPS) are caused by deficiency of specific lysosomal enzymes that result in the accumulation of GAGs in multiple tissues leading to organ dysfunction. Therefore, GAGs are important biomarkers for MPS. Without any treatment, patients with severe forms of MPS die within the first two decades of life.

SCOPE OF REVIEW

Accurate measurement of GAGs is important to understand the diagnosis and pathogenesis of MPS and to monitor therapeutic efficacy before, during, and after treatment of the disease. This review covers various qualitative and quantitative methods for measurement of GAGs, including dye specific, thin layer chromatography (TLC), capillary electrophoresis, high-performance liquid chromatography (HPLC), liquid chromatography-tandem mass spectrometry (LC-MS/MS), gas chromatography, ELISA, and automated high-throughput mass spectrometry. Major conclusion: There are several methods for GAG detection however, specific GAG detection in the various biological systems requires rapid, sensitive, specific, and cost-effective methods such as LC-MS/MS.

GENERAL SIGNIFICANCE

This review will describe different methods for GAG detection and analysis, including their advantages and limitation.

Strategies for large-scale targeted metabolomics quantification by liquid chromatography-mass spectrometry

Advances in liquid chromatography-mass spectrometry (LC-MS) instruments and analytical strategies have brought about great progress in targeted metabolomics analysis. This methodology is now capable of performing precise targeted measurement of dozens or hundreds of metabolites in complex biological samples. Classic targeted quantification assay using the multiple reaction monitoring (MRM) mode has been the foundation of high-quality metabolite quantitation. However, utilization of this strategy in biological studies has been limited by its relatively low metabolite coverage and throughput capacity. A number of methods for large-scale targeted metabolomics assay which have been developed overcome these limitations. These strategies have enabled extended metabolite coverage which is defined as targeting of large numbers of metabolites, while maintaining reliable quantification performance. These recently developed techniques thus bridge the gap between traditional targeted metabolite quantification and untargeted metabolomics profiling, and have proven to be powerful tools for metabolomics study. Although the LC-MRM-MS strategy has been used widely in large-scale metabolomics quantification analysis due to its fast scan speed and ideal analytic stability, there are still drawbacks which are due to the low resolution of the triple quadrupole instruments used for MRM assays. New approaches have been developed to expand the options for large-scale targeted metabolomics study, using high-resolution instruments such as parallel reaction monitoring (PRM). MRM and PRM-based techniques are now attractive strategies for quantitative metabolomics analysis and high-throughput biomarker discovery. Here we provide an overview of the major developments in LC-MS-based strategies for large-scale targeted metabolomics quantification in biological samples. The advantages of LC-MRM/PRM-MS based analytical strategies which may be used in multiplexed and high throughput quantitation for a wide range of metabolites are highlighted. In particular, PRM and MRM strategies are compared, and we summarize the work flow commonly used for large-scale targeted metabolomics analysis including sample preparation, LC separation and data analysis, as well as recent applications in biological studies.

[Development of a Method for Simultaneous Analysis of Egg and Milk Major Allergens in Beverage Products Using High-Performance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry]

A method for simultaneous analysis of egg and milk allergens using LC-QTOF-MS was developed. The proteins measured were α-casein, β-lactoglobulin, and ovalbumin, which are the main protein allergens in milk and eggs. The proteins were digested using trypsin, and the digests were analyzed by LC-QTOF-MS. Sixteen peaks were detected that confirmed the amino acid sequences of the digests, and a MRM method with high resolution (MRM-HR) using product ions of these peaks was applied for quantification. Next, validation studies were performed using beverage products to which milk and egg standard protein solutions had been added. Good linearity was achieved over the concentration range of 1.25 to 20 μg/g of milk and egg protein, and acceptable reproducibility and accuracy were obtained at 10 μg/g. Moreover, good agreement was also observed between LC-QTOF-MS and ELISA. These findings suggest that this LC-QTOF-MS method may be useful for determining the milk and egg protein contents of beverages.

Recent developments in software tools for high-throughput in vitro ADME support with high-resolution MS

The last several years have seen the rapid adoption of the high-resolution MS (HRMS) for bioanalytical support of high throughput in vitro ADME profiling. Many capable software tools have been developed and refined to process quantitative HRMS bioanalysis data for ADME samples with excellent performance. Additionally, new software applications specifically designed for quan/qual soft spot identification workflows using HRMS have greatly enhanced the quality and efficiency of the structure elucidation process for high throughput metabolite ID in early in vitro ADME profiling. Finally, novel approaches in data acquisition and compression, as well as tools for transferring, archiving and retrieving HRMS data, are being continuously refined to tackle the issue of large data file size typical for HRMS analyses.

Bioanalysis in oncology drug discovery

Bioanalysis is an important aspect of drug discovery process regardless of the chosen therapeutic area. There is a general misconception that bioanalysis is seldom important during the drug discovery process because there is no scrutiny of the data from a regulatory perspective. However, bioanalytical data gathered during the discovery stage enable several key decision(s) inclusive of termination of the program and/or creating adequate differentiation from the lead competitive molecules. The review covers various stage gate screens and experimental designs where bioanalytical data are extensively used for making an informed decision during the process of drug discovery.

Cardiovascular drug determination in bioanalysis: an update

The great impact of cardiovascular diseases in human health has led to the development of a huge number of drugs and therapies to improve the treatment of these diseases. Cardiovascular drug analysis in biological fluids constitutes an important challenge for analytical scientists. There is a clear need for reliable methods to carry out both qualitative and quantitative analysis in a short time of analysis. Different problems such as drug monitoring, analysis of metabolites, study of drugs interactions, drugs residues or degradation products, chiral separation, and screening and confirmation of drugs of abuse in doping control must be solved. New trends in sample preparation, instrumental and column technology advances in LC and innovations in MS are described in this work.

Rapid label-free determination of ketamine in whole blood using secondary ion mass spectrometry

A fast and accurate drug screening to identify the possible presence of a wide variety of pharmaceutical and illicit drugs is increasingly requested in forensic and clinical toxicology. The current first-line screening relies on immunoassays. They determine only certain common drugs of which antibodies are commercially available. To address the issue, a rapid screening using secondary ion mass spectrometry (SIMS) has been developed. In the study, SIMS directly analyzed ketamine in whole blood without any pretreatment. While the untreated blood has a complicated composition, principal-components analysis (PCA) is used to detect unknown specimens by building up an analytical model from blank samples which were spiked with ketamine at 100 ng mL(-1), to simulate the presence of ketamine. Each characteristics m/z is normalized and scaled by multiplying the root square of intensity and square of corresponding m/z, developed by National Institute of Standards and Technology (NIST). Using linear regression and the result of PCA, this study enables to correctly distinguish ketamine positive and negative groups in an unknown set of specimens. The quantity of ketamine in an unknown set was determined using gas chromatography-mass spectrometry (GC-MS) as the reference methodology. Instead limited by commercially available antibodies, SIMS detects target molecules straight despite the label-free detection capabilities of SIMS, additional data processing (here, PCA) can be used to fully analyse the produced data, which extends the range of analytes of interest on drug screening. Furthermore, extremely low sample volume, 5 µL, is required owing to the high spatial resolution of SIMS. In addition, while the whole blood is analyzed within 3 min, the whole analysis has been shortened significantly and high throughput can be achieved.

Quantitative performance of online SPE-LC coupled to Q-Exactive for the analysis of sofosbuvir in human plasma

A quantitative strategy towards the detection of sofosbuvir in human plasma was developed with online-SPE-LC-HRMS using t-MS², t-SIM and F-SIM modes.

Introduction of a routine quan/qual approach into research DMPK: experiences and evolving strategies

After graduating with an Oceanography degree from Swansea University, Lloyd has spent over 20 years in the field of bioanalysis and metabolite profiling. He started his career in large pharma at Wyeth UK, where he was involved in setting up the first GC and LC–MS/MS systems for both QC and early DMPK assays, employing EI/CI, thermospray, and the then new electrospray ionization techniques. Lloyd then joined Celltech, now UCB, where he is primarily tasked with metabolite profiling by LC–MS and NMR to support both early research projects and late-stage clinical studies.

The application of liquid chromatography high-resolution mass spectrometry for simultaneous quantitative and qualitative (quan/qual) analysis has gained momentum across a range of different scientific arenas in recent years. The ability to acquire high quality quantitative data, whilst also capturing qualitative data for either parallel or retrospective analysis, is a powerful resource, especially in view of ever-reducing cycle times, laboratory space and budgets. The quan/qual approach employing a Q-Exactive™ Orbitrap high-resolution mass spectrometer has been successfully introduced into UCB's research DMPK department. This article describes our experiences in introducing quan/qual, issues that we discovered in establishing this new working paradigm, the evolution of the strategy and its future potential.

Current position of high-resolution MS for drug quantification in clinical & forensic toxicology

This paper reviews high-resolution MS approaches published from January 2011 until March 2014 for the quantification of drugs (of abuse) and/or their metabolites in biosamples using LC-MS with time-of-flight or Orbitrap™ mass analyzers. Corresponding approaches are discussed including sample preparation and mass spectral settings. The advantages and limitations of high-resolution MS for drug quantification, as well as the demand for a certain resolution or a specific mass accuracy are also explored.

Distinguishing analyte from noise components in mass spectra of complex samples: where to cut the noise?

Fourier transform mass spectrometry (FTMS) enables comprehensive analysis of complex molecular mixtures. Given the broad intensity ranges of components in the mass spectra, it is imperative to accurately determine a noise threshold level above which peak assignments will be made. Conventionally, to find the threshold level, the "N sigma" approach or an equivalent rule is used. However, the "N sigma" approach cannot be applied to mass spectra stored with partially removed noise (reduced-profile mode). It is also not directly applicable to mass spectra acquired in the absorption mode with removed negative spectral amplitudes. Moreover, N value selection is normally made based on a rule of thumb, meaning that the calculated threshold level may be biased. Here, we present a noise thresholding method which addresses these limitations for analysis of mass spectra of complex molecular mixtures. The introduced data-dependent thresholding method involves analysis of the distribution of logarithmic intensity of all peaks, including noise and analyte, for a given mass spectrum. Selected method applications include FTMS analysis of crude oil fractions as well as tandem MS analysis of intact proteins.

Recent advances in LC–MS/MS analysis of Δ9-tetrahydrocannabinol and its metabolites in biological matrices

Cannabis is the most widely used illicit drug in the world. The pharmacological properties of Δ9-tetrahydrocannabinol also make it a promising molecule in the treatment of different pathologies. Understanding the PKs and PDs of this drug requires the determination of the concentration of Δ9-tetrahydrocannabinol and metabolites in biological matrices. For this purpose many analytical methodologies using mass spectrometric detection have been developed. In recent years, LC–MS/MS has become the gold standard in analysis of tetrahydrocannabinol and its metabolites due to the high selectivity and sensitivity, but above all, due to the ability to determine free and conjugate analytes in one run.

Method development and validation of six bile acids for regulated bioanalysis: improving selectivity and sensitivity

BACKGROUND

Quantification of bile acids using LC-MS has previously been very challenging on triple quadrupole MS systems due to the absence of a primary fragment ion for unconjugated bile acids.

RESULTS

A LC-high-resolution/accurate mass MS method for the analysis of six bile acids (cholic acid, chenodeoxycholic acid, taurocholic acid, deoxycholic acid, lithocholic acid and ursodeoxycholic acid) was developed and successfully validated. The method includes a single extraction and a single injection with all analytes separated using target-selected ion monitoring (SIM) mode in two periods with a resolution of 70,000 and 140,000, respectively.

CONCLUSION

This is the first LC-high-resolution/accurate mass assay fully validated to quantify six bile acids for regulated bioanalysis.

Sample reduction strategies in discovery bioanalysis

It is a constant challenge to provide timely bioanalytical support for the evaluation of drug-like properties and PK/PD profiles for the ever-increasing numbers of new chemical entities in a cost-effective manner. While technological advancement in various aspects of LC–MS/MS analysis has significantly improved bioanalytical efficiency, a number of simple sample reduction strategies can be employed to reduce the number of samples requiring analysis, and as a result increase the bioanalytical productivity without deploying additional instruments. In this review, advantages and precautions of common sample reduction strategies, such as sample pooling and cassette dosing, are discussed. In addition, other approaches such as reducing calibration standards and eliminating over-the-curve sample reanalysis will also be discussed. Taken together, these approaches can significantly increase the capacity and throughput of discovery bioanalysis without adding instruments, and are viable means to enhance the overall productivity of the bioanalytical laboratory.