Recent development in high-throughput bioanalytical support forin vitroADMET profiling

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.

Perspective on high-throughput bioanalysis to support in vitro assays in early drug discovery

As the desire for a shortened design/make/test/learn cycle increases in early drug discovery, the pressure to rapidly deliver drug metabolism pharmacokinetic data continues to rise. From a bioanalytical standpoint, in vitro assays are challenging because they are amenable to automation and thus capable of generating a high number of samples for analysis. To keep up with analysis demands, automated method development workflows, rapid sample analysis approaches and efficient data analysis software must be utilized. This work provides an outline of how we implemented those three aspects to provide bioanalytical support for in vitro drug metabolism pharmacokinetic assays, which include developing hundreds of mass spectrometry methods and analyzing thousands of samples per week, while delivering a median bioanalytical turnaround time of 1-2 business days.

Enhanced chromatographic efficiency obtained with vacuum jacketed columns facilitates the rapid UHPLC/MS/MS-based analysis of fasiglifam in rat plasma

The use of vacuum jacketed LC columns (VJC) to minimize on- and post-column band broadening to maximize chromatographic performance has been evaluated as a potential route to improved high throughput (HT) analysis. Here the use of the "VJC" approach has been applied to the HT bioanalysis of the antidiabetic GPR40 agonist drug fasiglifam in rat plasma samples obtained following a 5 mg/kg IV dose. The data obtained from a 1 minute VJC/MS-based analysis showed significant improvements compared to that from a conventional 2 minute UHPLC method for the drug. Notably, using VJC/MS with the rapid 1 min analysis provided a ca. 50% reduction in peak width coupled with a 2-5 fold higher peak response whilst doubling analytical throughput when compared to a conventional UHPLC/MS method. In addition, the increased resolution provided by the VJC system also improved the separation of fasiglifam from common matrix interferences such as co-extracted phospholipids thereby reducing the potential for matrix effects. The concatenation of these improvements suggests that the VJC approach may indeed provide a pathway to more sensitive, robust and high throughput drug bioanalysis, with particular advantages for drug discovery applications.

The Analytical Strategy of “Ion Induction and Deduction Based on Net-Hubs” for the Comprehensive Characterization of Naringenin Metabolites In Vivo and In Vitro Using a UHPLC-Q-Exactive Orbitrap Mass Spectrometer

Naringenin (5,7,4′-trihydroxyflavanone), belonging to the flavanone subclass, is associated with beneficial effects such as anti-oxidation, anticancer, anti-inflammatory, and anti-diabetic effects. Drug metabolism plays an essential role in drug discovery and clinical safety. However, due to the interference of numerous endogenous substances in metabolic samples, the identification and efficient characterization of drug metabolites are difficult. Here, ultra-high-performance liquid chromatography (UHPLC) coupled with high-resolution mass spectrometry was used to obtain mass spectral information of plasma (processed by three methods), urine, feces, liver tissue, and liver microsome samples. Moreover, a novel analytical strategy named “ion induction and deduction” was proposed to systematically screen and identify naringenin metabolites in vivo and in vitro. The analysis strategy was accomplished by the establishment of multiple “net-hubs” and the induction and deduction of fragmentation behavior. Finally, 78 naringenin metabolites were detected and identified from samples of rat plasma, urine, feces, liver tissue, and liver microsomes, of which 67 were detected in vivo and 13 were detected in vitro. Naringenin primarily underwent glucuronidation, sulfation, oxidation, methylation, ring fission, and conversion into phenolic acid and their composite reactions. The current study provides significant help in extracting target information from complex samples and sets the foundation for other pharmacology and toxicology research.

Retention-directed and selectivity controlled chromatographic resolution: Rapid post-hoc analysis of DMPK samples to achieve high-throughput LC-MS separation

High quality chromatographic separation underpins robustness in LC-MS, frequently the analytical method of choice for pharmaceutical drug discovery work. The potential improvements in chromatographic selectivity afforded by serial column coupling (SCC), provide a useful means to enhance the resolution of complex samples. In this work, we present a revised high-throughput form of SCC, in which just two individual mixed phase columns were coupled together and combined with a gradient-optimised, retention-directed ultra-high pressure method to achieve rapid separations, with no further method optimisation necessary. The overall performance was evaluated from an open access DMPK analytical working environment perspective; where in anticipation of bioanalytical or metabolite identification chromatography challenges, or with the knowledge that stronger resolution was required for in-vitro sample analysis, the methodology could be immediately implemented by the analyst. Retention-directed selection of a shallow SCC gradient method was successful in separating peaks throughout the chromatographic window, resulting in a runtime still congruent to high-throughput analyses (3.5 min). In-vitro assay sample interferences were resolved 44-72% of the time, and the overall resolving power for isomeric separations significantly improved against single column comparisons (1.7-fold mean R_S improvement). Over a sustained period of time in our laboratory, SCC methods have been used for metabolite identification and bioanalytical samples, where both convenience and effectiveness in solving analytical challenges has been consistently demonstrated. Examples that highlight SCC chromatography, and a guided discussion of the main high-throughput considerations, are included. The technique offers wide applicability, and we would recommend it as a toolbox consideration to the laboratory analyst.

Current status and future directions of high-throughput ADME screening in drug discovery

During the last decade high-throughput in vitro absorption, distribution, metabolism and excretion (HT-ADME) screening has become an essential part of any drug discovery effort of synthetic molecules. The conduct of HT-ADME screening has been "industrialized" due to the extensive development of software and automation tools in cell culture, assay incubation, sample analysis and data analysis. The HT-ADME assay portfolio continues to expand in emerging areas such as drug-transporter interactions, early soft spot identification, and ADME screening of peptide drug candidates. Additionally, thanks to the very large and high-quality HT-ADME data sets available in many biopharma companies, in silico prediction of ADME properties using machine learning has also gained much momentum in recent years. In this review, we discuss the current state-of-the-art practices in HT-ADME screening including assay portfolio, assay automation, sample analysis, data processing, and prediction model building. In addition, we also offer perspectives in future development of this exciting field.

Optimization of microflow LC-MS/MS and its utility in quantitative discovery bioanalysis

Aim: The sensitivity advantage of microflow LC (μFLC)-MS/MS is potentially impactful for challenging compounds not detectable by conventional flow LC-MS/MS in drug discovery bioanalysis. Relatively new to μFLC technology, discovery bioanalytical scientists would benefit from an effective strategy for method development and optimization. Results: A systematic μFLC-MS/MS method optimization approach was developed in this study. With optimized conditions, μFLC-MS/MS demonstrated an improved sensitivity compared with conventional LC-MS/MS analysis, ranging from 6× to 49× (by peak area) depending on the compounds, with acceptable analytical performance and robustness. The optimized conditions demonstrated universal applicability to various compounds of diverse properties. Conclusion: The systematic method optimization strategy, and the general applicability of the optimized conditions could facilitate the routine utilization of μFLC in quantitative discovery bioanalysis.

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.

Mass spectrometry and NMR spectroscopy: modern high-end detectors for high resolution separation techniques--state of the art in natural product HPLC-MS, HPLC-NMR, and CE-MS hyphenations

Current natural product research is unthinkable without the use of high resolution separation techniques as high performance liquid chromatography or capillary electrophoresis (HPLC or CE respectively) combined with mass spectrometers (MS) or nuclear magnetic resonance (NMR) spectrometers. These hyphenated instrumental analysis platforms (CE-MS, HPLC-MS or HPLC-NMR) are valuable tools for natural product de novo identification, as well as the authentication, distribution, and quantification of constituents in biogenic raw materials, natural medicines and biological materials obtained from model organisms, animals and humans. Moreover, metabolic profiling and metabolic fingerprinting applications can be addressed as well as pharmacodynamic and pharmacokinetic issues. This review provides an overview of latest technological developments, discusses the assets and drawbacks of the available hyphenation techniques, and describes typical analytical workflows.

Laboratory automation of high-quality and efficient ligand-binding assays for biotherapeutic drug development

Background: Regulated bioanalytical laboratories that run ligand-binding assays in support of biotherapeutics development face ever-increasing demand to support more projects with increased efficiency. Laboratory automation is a tool that has the potential to improve both quality and efficiency in a bioanalytical laboratory. The success of laboratory automation requires thoughtful evaluation of program needs and fit-for-purpose strategies, followed by pragmatic implementation plans and continuous user support. Results: In this article, we present the development of fit-for-purpose automation of total walk-away and flexible modular modes. We shared the sustaining experience of vendor collaboration and team work to educate, promote and track the use of automation. Conclusion: The implementation of laboratory automation improves assay performance, data quality, process efficiency and method transfer to CRO in a regulated bioanalytical laboratory environment.

The stability of amitriptyline N-oxide and clozapine N-oxide on treated and untreated dry blood spot cards

Procedures for drug monitoring based on Dried Blood Spot (DBS) sampling are gaining acceptance for an increasing number of clinical and preclinical applications, where ease of use, small sample requirement, and improved sample stability have been shown to offer advantages over blood tube sampling. However, to-date, the vast majority of this work has described the analysis of well characterized drugs. Using amitriptyline, clozapine, and their potentially labile N-oxide metabolites as model compounds, we consider the merits of using DBS for discovery pharmacokinetic (PK) studies where the metabolic fate of test compounds are often unknown. Both N-oxide metabolites reverted to parent compound under standard drying (2hr) and extraction conditions. Card type significantly affected the outcome, with 14% and 22% degradation occurring for clozapine-N-oxide and amitriptyline-N-oxide on a brand of untreated DBS cards, compared to 59 and 88% on a brand of treated DBS cards. Enrichment of the parent compound ex vivo leads to overestimation of circulating blood concentration and inaccurate determination of the PK profile.

Full utilization of a mass spectrometer using on-demand sharing with multiple LC units

The applicability of liquid chromatography-mass spectrometry (LC/MS) is often limited by throughput. The sharing of a mass spectrometer with multiple LCs significantly improves throughput; however, the reported systems have not been designed to fully utilize the MS duty cycle, and as a result to achieve maximum throughput. To fully utilize the mass spectrometer, the number of LC units that a MS will need to recruit is application dependent and could be significantly larger than the current commercial or published implementations. For the example of a single analyte, the number may approach the peak capacity to a first degree approximation. Here, the construction of a MS system that flexibly recruits any number of LC units demanded by the application is discussed, followed by the method to port a previously developed LC/MS method to the system to fully utilize a mass spectrometer. To demonstrate the performance and operation, a prototypical MS system of eight LC units was constructed. When 1-min chromatographic separations were performed in parallel on the eight LCs of the system, the average LC/MS analysis time per sample was 10.5 s when applied to the analysis of samples in 384-well plate format. This system has been successfully used to conduct large-volume biochemical assays with the analysis of a variety of molecular entities in support of drug discovery efforts. Allowing the recruitment of the number of LC units appropriate for a given application, this system has the potential to be a plug-and-play system to fully utilize a mass spectrometer.

Development of a high-speed, multiplexed sample-delivery instrument for LC–MS/MS bioanalysis

Background: The number of new chemical entities and types of in vitro and in vivo samples that require bioanalysis in drug discovery is large and diverse. In addition, method development time is limited as data turnaround is the highest priority. These circumstances require that a well-defined set of bioanalysis options be available in short timeframes to triage samples for analysis. Method: The Apricot Designs Dual Arm (ADDA) instrument is an LC–MS/MS sample delivery system that features a flexible hardware design coupled with software automation to enhance throughput in LC–MS/MS bioanalysis drug discovery. The instrument can perform high-throughput LC–MS/MS (8–10 s/sample) for screening and in vitro bioanalysis, as well as multiplexed LC for traditional gradient or isocratic LC approaches. The instrument control software is designed to integrate with DiscoveryQuant™ software (AB Sciex) and a global database of MS/MS conditions. Conclusion: Development of the sample delivery platform and its application in high-throughput and gradient LC will be described.

SPE–MS analysis of absorption, distribution, metabolism and excretion assays: a tool to increase throughput and steamline workflow

In an effort to create faster and more efficient bioanalytical methods for drug development, many investigators have evaluated a variety of SPE–MS systems. Over the past 15 years online systems have evolved from run times of >1.5 min/sample to <10 s/sample. High-throughput SPE–MS methods for in vitro absorption, distribution, metabolism and excretion screening assays have been described by several laboratories and shown to produce results comparable to conventional LC–MS/MS systems. While quantitative analysis of small molecules in biological matrixes holds many challenges, for several applications SPE–MS methods have achieved comparable results to LC–MS/MS with the benefit of 10–30-times the throughput. Based on its distinct advantages of throughput and streamlined workflow efficiencies, SPE–MS is a useful tool for the analysis of many in vitro absorption, distribution, metabolism and excretion assays and in vivo bioanalytical studies. Further development of SPE–MS methods and analysis workflows has the potential to expand the capabilities of this technology for other challenging bioanalytical applications.

Recent development in software and automation tools for high-throughput discovery bioanalysis

Bioanalysis with LC–MS/MS has been established as the method of choice for quantitative determination of drug candidates in biological matrices in drug discovery and development. The LC–MS/MS bioanalytical support for drug discovery, especially for early discovery, often requires high-throughput (HT) analysis of large numbers of samples (hundreds to thousands per day) generated from many structurally diverse compounds (tens to hundreds per day) with a very quick turnaround time, in order to provide important activity and liability data to move discovery projects forward. Another important consideration for discovery bioanalysis is its fit-for-purpose quality requirement depending on the particular experiments being conducted at this stage, and it is usually not as stringent as those required in bioanalysis supporting drug development. These aforementioned attributes of HT discovery bioanalysis made it an ideal candidate for using software and automation tools to eliminate manual steps, remove bottlenecks, improve efficiency and reduce turnaround time while maintaining adequate quality. In this article we will review various recent developments that facilitate automation of individual bioanalytical procedures, such as sample preparation, MS/MS method development, sample analysis and data review, as well as fully integrated software tools that manage the entire bioanalytical workflow in HT discovery bioanalysis. In addition, software tools supporting the emerging high-resolution accurate MS bioanalytical approach are also discussed.

One step forward: the use of transgenic zebrafish tumor model in drug screens

The zebrafish (Danio rerio) has been an experimental model in the developmental biology and toxicology since the 1950s. In recent years, with the aid of transgenic technology, it has also gained an increasing popularity to model human diseases, including various cancers. As a feasible vertebrate model for large-scale chemical screens, the zebrafish has also given us a new option for the search of potential anticancer drugs. It is hopeful that in the near future with automation and analytical tools, drug development processes will be significantly shortened for quick and effective identification of candidate drugs.

Ultrafast mass spectrometry based bioanalytical method for digoxin supporting an in vitro P-glycoprotein (P-gp) inhibition screen

The evaluation of interactions between drug candidates and transporters such as P-glycoprotein (P-gp) has gained considerable interest in drug discovery and development. Inhibition of P-gp can be assessed by performing bi-directional permeability studies with in vitro P-gp-expressing cellular model systems such as Caco-2 (human colon carcinoma) cells, using digoxin as a substrate probe. Existing methodologies include either assaying (3)H-digoxin with liquid scintillation counting (LSC) detection or assaying non-labeled digoxin with liquid chromatography-tandem mass spectrometric (LC-MS/MS) analysis at a speed of several minutes per sample. However, it is not feasible to achieve a throughput high enough using these approaches to sustain an early liability screen that generates more than a thousand samples on a daily basis. To address this challenge, we developed an ultrafast (9 s per sample) bioanalytical method for digoxin analysis using RapidFire™, an on-line solid-phase extraction (SPE) system, with MS/MS detection. A stable isotope labeled analog, d3-digoxin, was used as internal standard to minimize potential ionization matrix effect during the RF-MS/MS analysis. The RF-MS/MS method was more than 16 times faster than the LC-MS/MS method but demonstrated similar sensitivity, selectivity, reproducibility, linearity and robustness. P-gp inhibition results of multiple validation compounds obtained with this RF-MS/MS method were in agreement with those generated by both the LC-MS/MS method and the (3)H-radiolabel assay. This method has been successfully deployed to assess P-gp inhibition potential as an important early liability screen for drug-transporter interaction.

An integrated bioanalytical platform for supporting high-throughput serum protein binding screening

Quantification of small molecules using liquid chromatography/tandem mass spectrometry (LC/MS/MS) on a triple quadrupole mass spectrometer has become a common practice in bioanalytical support of in vitro adsorption, distribution, metabolism and excretion (ADME) screening. The bioanalysis process involves primarily three indispensable steps: MS/MS optimization for a large number of new chemical compounds undergoing various screening assays in early drug discovery, high-throughput sample analysis with LC/MS/MS for those chemically diverse compounds using the optimized MS/MS conditions, and post-acquisition data review and reporting. To improve overall efficiency of ADME bioanalysis, an integrated system was proposed featuring an automated and unattended MS/MS optimization, a staggered parallel LC/MS/MS for high-throughput sample analysis, and a sophisticated software tool for LC/MS/MS raw data review as well as biological data calculation and reporting. The integrated platform has been used in bioanalytical support of a serum protein binding screening assay with high speed, high capacity, and good robustness. In this new platform, a unique sample dilution scheme was also introduced. With this dilution design, the total number of analytical samples was reduced; therefore, the total operation time was reduced and the overall throughput was further improved. The performance of the protein binding screening assay was monitored with two controls representing high and low binding properties and an acceptable inter-assay consistency was achieved. This platform has been successfully used for the determination of serum protein binding in multiple species for more than 4000 compounds.

Cell-based assays: fuelling drug discovery

It has been estimated that over a billion dollars in resources can be consumed to obtain clinical approval, and only a few new chemical entities are approved by the US Food and Drug Administration (FDA) each year. Therefore it is of utmost importance to obtain the maximum amount of information about biological activity, toxicological profile, biochemical mechanisms, and off-target interactions of drug-candidate leads in the earliest stages of drug discovery. Cell-based assays, because of their peculiar advantages of predictability, possibility of automation, multiplexing, and miniaturization, seem the most appealing tool for the high demands of the early stages of the drug-discovery process. Nevertheless, cellular screening, relying on different strategies ranging from reporter gene technology to protein fragment complementation assays, still presents a variety of challenges. This review focuses on main advantages and limitations of different cell-based approaches, and future directions and trends in this fascinating field.