Fractional mass filtering as a means to assess circulating metabolites in early human clinical studies

Ultra-high pressure liquid chromatography coupled to travelling wave ion mobility-time of flight mass spectrometry for the screening of pharmaceutical metabolites in wastewater samples: Application to antiretrovirals

The presence of pharmaceutical compounds in the aquatic environment is a significant environmental health concern, which is exacerbated by recent evidence of the contribution of drug metabolites to the overall pharmaceutical load. In light of a recent report of the occurrence of metabolites of antiretroviral drugs (ARVDs) in wastewater, we investigate in the present work the occurrence of further ARVD metabolites in samples obtained from a domestic wastewater treatment plant in the Western Cape, South Africa. Pharmacokinetic data indicate that ARVDs are biotransformed into several positional isomeric metabolites, only two of which have been reported wastewater samples. Given the challenges associated with the separation and identification of isomeric species in complex wastewater samples, a method based on liquid chromatography hyphenated to ion mobility spectrometry-high resolution mass spectrometry (LC-IMS-HR-MS) was implemented. Gradient LC separation was achieved on a sub-2 µm reversed phase column, while the quadrupole-time-of-flight MS was operated in data independent acquisition (DIA) mode to increase spectral coverage of detected features. A mass defect filter (MDF) template was implemented to detect ARVD metabolites with known phase I and phase II mass shifts and fractional mass differences and to filter out potential interferents. IMS proved particularly useful in filtering the MS data for co-eluting species according to arrival time to provide cleaner mass spectra. This approach allowed us to confirm the presence of two known hydroxylated efavirenz and nevirapine metabolites using authentic standards, and to tentatively identify a carboxylate metabolite of abacavir previously reported in literature. Furthermore, three hydroxylated-, two sulphated and one glucuronidated metabolite of efavirenz, two hydroxylated metabolites of nevirapine and one hydroxylated metabolite of ritonavir were tentatively or putatively identified in wastewater samples for the first time. Assignment of the metabolites is discussed in terms of high resolution fragmentation data, while collisional cross section (CCS) values measured for the detected analytes are reported to facilitate further work in this area.

Untargeted, spectral library-free analysis of data-independent acquisition proteomics data generated using Orbitrap mass spectrometers

We describe an improved version of the data-independent acquisition (DIA) computational analysis tool DIA-Umpire, and show that it enables highly sensitive, untargeted, and direct (spectral library-free) analysis of DIA data obtained using the Orbitrap family of mass spectrometers. DIA-Umpire v2 implements an improved feature detection algorithm with two additional filters based on the isotope pattern and fractional peptide mass analysis. The targeted re-extraction step of DIA-Umpire is updated with an improved scoring function and a more robust, semiparametric mixture modeling of the resulting scores for computing posterior probabilities of correct peptide identification in a targeted setting. Using two publicly available Q Exactive DIA datasets generated using HEK-293 cells and human liver microtissues, we demonstrate that DIA-Umpire can identify similar number of peptide ions, but with better identification reproducibility between replicates and samples, as with conventional data-dependent acquisition. We further demonstrate the utility of DIA-Umpire using a series of Orbitrap Fusion DIA experiments with HeLa cell lysates profiled using conventional data-dependent acquisition and using DIA with different isolation window widths.

Metabolite structure analysis by high-resolution MS: supporting drug-development studies

Effective characterization of drug metabolites in complex biological matrices is facilitated by mass spectrometers with high resolving power, mass accuracy and sensitivity. This review begins with an overview of high-resolution MS terminology and the different types of instrumentation that are currently available. Metabolite structure analysis offers unique challenges and, therefore, the different types of approaches used to solve problems are highlighted through specific examples. Overall, this review describes the value that high-resolution MS brings to drug-metabolism studies.

The early estimation of circulating drug metabolites in humans

INTRODUCTION

An evolution in bioanalytical methodologies to identify and quantify drug metabolites has led to a wealth of biotransformation information during preclinical and early clinical testing phases. However, this abundance of metabolism data has not clarified how to select the most important circulating human metabolites for safety assessment. Consequently, more stringent regulatory expectations for a comprehensive approach to human metabolism have led pharmaceutical sponsors to employ a variety of novel methods to estimate circulating drug metabolites in humans and animals.

AREAS COVERED

This review provides context for 'why' human circulating metabolites must be qualified for safety in animals. A detailed overview is also presented concerning 'where,' 'how' and 'when' to conduct these assessments during drug development.

EXPERT OPINION

A human metabolite qualification strategy is now a required element of the drug safety package submitted with a new drug application (NDA). The important question is whether or not this additional information, about metabolite safety, is making human drugs any safer. Currently, this is a debatable issue, especially because stand-alone metabolite testing is fraught with its own challenges. As drug development moves into the twenty-first century, there is a pressing need for more sophisticated methodologies to address human drug and metabolite safety.

Recent advances in metabolite identification and quantitative bioanalysis by LC–Q-TOF MS

The need for rapid, sensitive and effective identification and quantitation of drugs and metabolites to accelerate drug discovery and development has given MS its central position in drug metabolism and pharmacokinetic research. This review attempts to orient the readers with respect to hybrid Q-TOF MS, which enables accurate mass measurement and generates information-rich datasets. The key properties of the Q-TOF MS system, including mass accuracy, resolution, scan speed and dynamic range, are herein discussed. Developments on tandem separation techniques (e.g., UHPLC® and ion mobility spectrometry), data acquisition and data-mining methods (e.g., mass defect, product/neutral loss, isotope pattern filters and background subtraction) that facilitate qualitative and quantitative analysis are then examined. The performance and versatility of LC–Q-TOF MS are thoroughly illustrated by its applications in metabolite identification and quantitative bioanalysis. Future perspectives are also discussed.

Integrated quantitative and qualitative workflow for in vivo bioanalytical support in drug discovery using hybrid Q-TOF-MS

Background: UHPLC coupled with orthogonal acceleration hybrid quadrupole-TOF (Q-TOF)-MS is an emerging technique offering new strategies for the efficient screening of new chemical entities and related molecules at the early discovery stage within the pharmaceutical industry. In the first part of this article, we examine the main instrumental parameters that are critical for the integration of UHPLC–Q-TOF technology to existing bioanalytical workflows, in order to provide simultaneous quantitative and qualitative bioanalysis of samples generated following in vivo studies. Material & Methods: Three modern Q-TOF mass spectrometers, including Bruker maXis™, Agilent 6540 and Sciex TripleTOF™ 5600, all interfaced with UHPLC systems, are evaluated in the second part of the article. The scope of this work is to demonstrate the potential of Q-TOF for the analysis of typical small molecules, therapeutic peptides (molecular weight <6000 Da), and enzymatically (i.e., trypsin, chymotrypsin and pepsin) cleaved peptides from larger proteins. Results & Discussion: This work focuses mainly on full-scan TOF data obtained under ESI conditions, the major mode of TOF operation in discovery bioanalytical research, where the compounds are selected based on their pharmacokinetic/pharmacodynamic behaviors using animal models prior to selecting a few desirable candidates for further development. Finally, important emerging TOF technologies that could potentially benefit bioanalytical research in the semi-quantification of metabolites without synthesized standards are discussed. Particularly, the utility of captive spray ionization coupled with TripleTOF 5600 was evaluated for improving sensitivity and providing normalized MS response for drugs and their metabolites. The workflow proposed compromises neither the efficiency, nor the quality of pharmacokinetic data in support of early drug discovery programs.

Drug metabolite profiling and identification by high-resolution mass spectrometry

Mass spectrometry plays a key role in drug metabolite identification, an integral part of drug discovery and development. The development of high-resolution (HR) MS instrumentation with improved accuracy and stability, along with new data processing techniques, has improved the quality and productivity of metabolite identification processes. In this minireview, HR-MS-based targeted and non-targeted acquisition methods and data mining techniques (e.g. mass defect, product ion, and isotope pattern filters and background subtraction) that facilitate metabolite identification are examined. Methods are presented that enable multiple metabolite identification tasks with a single LC/HR-MS platform and/or analysis. Also, application of HR-MS-based strategies to key metabolite identification activities and future developments in the field are discussed.

Approaches for the rapid identification of drug metabolites in early clinical studies

Understanding the metabolism of a novel drug candidate in drug discovery and drug development is as important today as it was 30 years ago. What has changed in this period is the technology available for proficient metabolite characterization from complex biological sources. High-efficiency chromatography, sensitive MS and information-rich NMR spectroscopy are approaches that are now commonplace in the modern laboratory. These advancements in analytical technology have led to unequivocal metabolite identification often being performed at the earliest opportunity, following the first dose to man. For this reason an alternative approach is to shift from predicting and extrapolating possible human metabolism from in silico and nonclinical sources, to actual characterization at steady state within early clinical trials. This review provides an overview of modern approaches for characterizing drug metabolites in these early clinical studies. Since much of this progress has come from technology development over the years, the review is concluded with a forward-looking perspective on how this progression may continue into the next decade.

Differentiation of structural isomers in a target drug database by LC/Q-TOFMS using fragmentation prediction

Isomers cannot be differentiated from each other solely based on accurate mass measurement of the compound. A liquid chromatography/quadrupole time-of-flight mass spectrometry (LC/Q-TOFMS) method was used to systematically fragment a large group of different isomers. Two software programs were used to characterize in silico mass fragmentation of compounds in order to identify characteristic fragments. The software programs employed were ACD/MS Fragmenter (ACD Labs Toronto, Canada), which uses general fragmentation rules to generate fragments based on the structure of a compound, and SmartFormula3D (Bruker Daltonics), which assigns fragments from a mass spectra and calculates the molecular formulae for the ions using accurate mass data. From an in-house toxicology database of 874 drug substances, 48 isomer groups comprising 111 compounds, for which a reference standard was available, were found. The product ion spectra were processed with the two software programs and 1-3 fragments were identified for each compound. In 82% of the cases, the fragment could be identified with both software programs. Only 10 isomer pairs could not be differentiated from each other based on their fragments. These compounds were either diastereomers or position isomers undergoing identical fragmentation. Accurate mass data could be utilized with both software programs for structural elucidation of the fragments. Mean mass accuracy and isotopic pattern match values (SigmaFit; Bruker Daltonics Bremen, Germany) were 0.9 mDa and 24.6 mSigma, respectively. The study introduces a practical approach for preliminary compound identification in a large target database by LC/Q-TOFMS without necessarily possessing reference standards.

Exploring the feasibility of using the DBS technique for metabolite radioprofiling

Background: The dried blood spots (DBS) technique has been actively evaluated as plasma replacement for monitoring drug exposure to support drug development in preclinical/clinical pharmacokinetic and toxicokinetic studies. Plasma samples from some of these studies are typically used for metabolite profiling and identification and for determination of disproportionate metabolites between safety species and humans to address metabolites in safety testing issues. The objectives of this study were to explore the feasibility of using the DBS technique for a metabolism study and to compare metabolite radioprofiles between DBS, plasma and whole blood samples. Results: The radioactivity extraction recovery in DBS samples was similar or better than that in plasma or whole blood. The metabolite radioprofiles in AUC pooled DBS samples using FTA® and FTA® Elute cards were comparable to those in AUC pooled plasma and whole blood. Conclusion: It is feasible to use DBS as an alternative matrix to plasma for in vivo metabolite radioprofiling studies for SA-1.

Overview of metabolite safety testing from an industry perspective

Regulatory guidelines on MIST were initially established in 2005 and finalized in 2008 by the US FDA and this has led to much discussion and debate on how to apply these recommendations in today’s resource-constrained pharmaceutical environment. There are four aspects of MIST that impact on the field of bioanalysis: definition of a disproportionate human metabolite, establishment of nonclinical (animal) safety coverage for important human metabolites, degree of rigor in validation of bioanalytical methods to quantify metabolites when synthetic standards are available, and semiquantitation of metabolites when synthetic standards are not available. In this manuscript, each of these points has been addressed from a pharmaceutical industry standpoint, including a perspective on the necessary convergence of the fields of metabolite safety testing and bioanalysis.

Novel MS solutions inspired by MIST

To improve patient safety and to help avoid costly late-stage failures, the pharmaceutical industry, along with the US FDA and International Committee on Harmonization (ICH), recommends the identification of differences in drug metabolism between animals used in nonclinical safety assessments and humans as early as possible during the drug-development process. LC–MS is the technique of choice for detection and characterization of metabolites, however, the widely different LC–MS response observed for a new chemical entity (NCE) and its structurally related metabolites limits the direct use of LC–MS responses for quantitative determination of NCEs and metabolites. While no method provides completely accurate universal response, UV, corona charged aerosol detection (CAD), radioactivity, NMR and low-flow (<20 µl/min) nanospray approaches provide opportunities to quantify metabolites in the absence of reference standards or radiolabeled material with enough precision to meet the needs of early clinical development.

Non-linear classification for on-the-fly fractional mass filtering and targeted precursor fragmentation in mass spectrometry experiments

MOTIVATION

Mass spectrometry (MS) has become the method of choice for protein/peptide sequence and modification analysis. The technology employs a two-step approach: ionized peptide precursor masses are detected, selected for fragmentation, and the fragment mass spectra are collected for computational analysis. Current precursor selection schemes are based on data- or information-dependent acquisition (DDA/IDA), where fragmentation mass candidates are selected by intensity and are subsequently included in a dynamic exclusion list to avoid constant refragmentation of highly abundant species. DDA/IDA methods do not exploit valuable information that is contained in the fractional mass of high-accuracy precursor mass measurements delivered by current instrumentation.

RESULTS

We extend previous contributions that suggest that fractional mass information allows targeted fragmentation of analytes of interest. We introduce a non-linear Random Forest classification and a discrete mapping approach, which can be trained to discriminate among arbitrary fractional mass patterns for an arbitrary number of classes of analytes. These methods can be used to increase fragmentation efficiency for specific subsets of analytes or to select suitable fragmentation technologies on-the-fly. We show that theoretical generalization error estimates transfer into practical application, and that their quality depends on the accuracy of prior distribution estimate of the analyte classes. The methods are applied to two real-world proteomics datasets.

AVAILABILITY

All software used in this study is available from http://software.steenlab.org/fmf

CONTACT

hanno.steen@childrens.harvard.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

An accurate-mass-based spectral-averaging isotope-pattern-filtering algorithm for extraction of drug metabolites possessing a distinct isotope pattern from LC-MS data

Detection and identification (ID) of all drug metabolites following liquid chromatography (LC)/mass spectrometry (MS) analysis of complex biological matrixes are not trivial. To facilitate detection of drug-derived materials that possess highly diagnostic isotopic patterns (e.g., chlorine- and bromine-containing compounds), we report an accurate-mass-based spectral-averaging isotope-pattern-filtering (AMSA-IPF) algorithm developed in the computational language R. The AMSA-IPF algorithm offers three significant improvements over the traditional isotope filtering method often provided by instrument vendors. First, spectral averaging is performed before the IPF to reduce scan-to-scan variability of ion intensities. Second, the IPF process is strictly based on accurate mass typically obtained on high resolution mass spectrometers. The designated isotopic ion-pairs (e.g., M + 2:M or M + 1:M, where M is the molecular ion and M + 1 and M + 2 are the isotopic ions) must fall into the predefined accurate mass tolerance window (e.g., 5 ppm) and at the same time satisfy the predefined relative abundance criteria. Third, both M + 1:M and M + 2:M ion pairs are inspected in the filtering process. The inclusion of M + 1:M ion pair enhanced the specificity of this algorithm by removing background ions that form M:M + 2 ion pairs within predefined isotope ratios by coincidence. The algorithm demonstrated excellent effectiveness in detecting drug-related ions in in vivo samples (plasma, bile, urine and feces) obtained from rats orally dosed with 14C-loratadine. The ion chromatograms of the filtered LC-MS data files showed near perfect qualitative correlation with the corresponding radioprofiles. AMSA-IPF will be another great tool to facilitate detection and ID of drug metabolites in complex LC-MS data without the help of radiolabels. The AMSA-IPF algorithm is applicable to not only compounds containing distinct natural isotopes (such as Cl and Br) but also compounds that contain synthetically incorporated isotopes (13C, 15N, etc) generating a distinct isotope pattern. The ability to detect and identify metabolites from nonradiolabeled studies will be extremely beneficial to achieve compliance with FDA's most recent guidance on metabolites in safety testing (MIST).

Quantitative-qualitative data acquisition using a benchtop Orbitrap mass spectrometer

Current approaches to discovery-stage drug metabolism studies (pharmacokinetics, microsomal stability, etc.) typically use triple-quadrupole-based approaches for quantitative analysis. This necessitates the optimization of parameters such as Q1 and Q3 m/z values, collision energy, and interface voltages. These studies detect only the specified compound and information about other components, such as metabolites, is lost. The ability to perform full-scan acquisition for quantitative analysis would eliminate the need for compound optimization while enabling the detection of metabolites and other non-drug-related endogenous components. Such an instrument would have to provide sensitivity, selectivity, dynamic range, and scan speed suitable for discovery-stage quantitative studies. In this study, a prototype benchtop Orbitrap-based mass analyzer was used to collect both quantitative and qualitative data from human microsomal incubation samples as well as rat plasma from pharmacokinetic studies. Instrumental parameters such as scan speed, resolution, and mass accuracy are discussed in relation to the requirements for a quantitative-qualitative workflow. The ability to perform highly selective quantitative analysis while simultaneously characterizing metabolites from both in vitro and in vivo studies is discussed.

Mass defect filter technique and its applications to drug metabolite identification by high-resolution mass spectrometry

Identification of drug metabolites by liquid chromatography/mass spectrometry (LC/MS) involves metabolite detection in biological matrixes and structural characterization based on product ion spectra. Traditionally, metabolite detection is accomplished primarily on the basis of predicted molecular masses or fragmentation patterns of metabolites using triple-quadrupole and ion trap mass spectrometers. Recently, a novel mass defect filter (MDF) technique has been developed, which enables high-resolution mass spectrometers to be utilized for detecting both predicted and unexpected drug metabolites based on narrow, well-defined mass defect ranges for these metabolites. This is a new approach that is completely different from, but complementary to, traditional molecular mass- or MS/MS fragmentation-based LC/MS approaches. This article reviews the mass defect patterns of various classes of drug metabolites and the basic principles of the MDF approach. Examples are given on the applications of the MDF technique to the detection of stable and chemically reactive metabolites in vitro and in vivo. Advantages, limitations, and future applications are also discussed on MDF and its combinations with other data mining techniques for the detection and identification of drug metabolites.