Looking beyond the SRM to high-resolution MS paradigm shift for DMPK studies
2013; Future Science Ltd; Volume: 5; Issue: 10 Linguagem: Inglês
10.4155/bio.13.95
ISSN1757-6199
Autores Tópico(s)Mass Spectrometry Techniques and Applications
ResumoBioanalysisVol. 5, No. 10 EditorialFree AccessLooking beyond the SRM to high-resolution MS paradigm shift for DMPK studiesDil M RamanathanDil M RamanathanKean University, New Jersey Center for Science, Technology & Mathematics, 1000 Morris Avenue, Union, NJ 07033, USA. Published Online:30 May 2013https://doi.org/10.4155/bio.13.95AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinkedInReddit Keywords: accurate massADMEbiotransformationdrug metabolismion mobilityLC–HRMSQ-ExactiveQ-TOFquan–qualSWATHA 1900 statement from Lord Kelvin to British physicists stated the following: "There is nothing new to be discovered in physics now. All that remains is more and more precise measurement"[101]. In a nutshell the SRM to HRMS paradigm shift revolves around precise or accurate measurement of mass using high-resolution MS (HRMS). Over the last few years, HRMS systems facilitated by new technological advances and user-friendly software have evolved from a specialist to a generalist analytical tool. The HRMS-based methods are now routinely used in most discovery DMPK bioanalytical and biotransformation laboratories and they are also slowly infiltrating some of the regulated bioanalytical laboratories. New additions to the HRMS workflow, such as MSe (where e represents collision energy) and sequential window acquisition of all theoretical fragments (SWATH) technologies, have started to pave the way to improved selectivity, specificity and signal-to-noise ratio of DMPK assays and are poised to help the paradigm shift come to completion.Success in drug R&D is critical for meeting the needs of medicine and patient care with the demands of running a growing, profitable business. For new drugs to be beneficial to patients, they must show improved efficacy and safety over existing treatments. For a drug to enter clinical trials and to become a product for patients, four separate but somewhat interrelated processes influence a drug's movement in the body: absorption (A), distribution (D), metabolism (M) and excretion (E). A drug's ADME properties are studied and optimized by pre-clinical and clinical drug metabolism and DMPK scientists. Over the past 20 years, LC–MS-based techniques have grown to replace every other technique and become the gold standard analytical technique for DMPK studies. The crystallization of the LC–MS technique as the gold standard DMPK analytical tool happened with the introduction of atmospheric pressure ionization (API) techniques, specifically, ESI and atmospheric-pressure chemical ionization (APCI). API techniques facilitated efficient coupling of LC separation technologies, which simplifies complex biological samples, before MS analysis.Since routine DMPK assays involve measuring m/z ratios of drugs and/or their metabolites present in complex biological samples, adequate sample clean-up and chromatographic separation are essential for quantification and characterization of these components. Two major chromatographic separation techniques used in DMPK studies are HPLC and UHPLC. Over the last 3–5 years, major developments in columns based on sub-2 µm porous particles, monoliths, and wide pore core-shell particles (2–3 µm) combined with the introduction of rugged UHPLC systems have improved the speed and throughput of small-molecule separations. Along with the developments in sample separation and preparation technologies, the evolutions of MS technologies have streamlined how DMPK studies are conducted.If you had to pinpoint it, the last paradigm shift in the bioanalytical sciences in support of DMPK studies happened in the late 1980s and early 1990s. And it revolved around shifting from LC–UV to LC–MS/MS for PK and TK quantitation [1] and the combined use of benchtop quodrupole ion trap and triple quadrupole for metabolite detection and characterization [2]. These shifts allowed DMPK scientists to bring bioanalysis into drug metabolism laboratories rather than be dependent on centralized MS facilities operated by a specialist. Furthermore, during this shift the ability to couple LC with sensitive MS/MS-based SRM methods allowed bioanalysts to improve the detection limits of PK assays from low µg/ml to low ng/ml and reduced the assay run time from 10–15 min to less than 5 min. On the metabolite identification front, it was no longer necessary to use 60–120 min runs to isolate and concentrate each metabolite for analysis by an MS specialist. Although ADME assays were being conducted by DMPK scientists rather than MS specialists, within the DMPK departments one dedicated group analyzed the samples in a targeted fashion for quantitation of parent drug and/or selected metabolites (quant group) and a different group analyzed the same samples in a non-targeted fashion for detection and characterization of metabolites, degradants and impurities (qual group).There is no doubt that LC–MS has changed how ADME assays are conducted, and without these techniques some life-saving medicines could not have been brought to the bedside of the patients. So, what has changed within the pharmaceutical industry that requires another paradigm shift? Overall, the pharmaceutical industry is looking to get more information with optimum resources and trying to satisfy new regulatory guidances on metabolite in safety testing (MIST) [3] and drug–drug interactions [102], while trying to run profitable drug discovery and development establishments. This desire of the pharmaceutical industry scientists to maximize information from a sample was fueled by the availability of technologies such as UHPLC and new MS hardware revolving around HRMS.As one of the proverb states: "The dog barks but the caravan moves on." Those who are not interested in being part of the change may bark all they want, but the caravan of change moves on. There are global and local forces already in place within the pharmaceutical industry that make change inevitable. The take-home message from the paper by Ramanathan et al. is the availability of non-targeted HRMS-based methods to simultaneously obtain quantitation of parent drug and detection and characterization of metabolites [4]. This paper, along with numerous presentations at national meetings and the 2012 Bioanalysis special focus issue on 'HRMS in DMPK', provided support for readiness of the hybrid HRMS hardware and software for acquiring information-rich datasets containing both LC–MS and LC–MS/MS from narrow LC peaks [5]. Overall, the HRMS method described requires minimum method development and detection of metabolites does not require any prior knowledge of parent drugs biotransformation or chemical formula or fragmentation pattern or collision energy. HRMS methods provide quantitative information for analytes of interest and also provide data on other metabolites present in the sample that might become of interest in the future during the course of drug development.Still, there are two types of hybrid mass analyzers available to provide high-resolution, high mass accuracy and full-scan speeds capable of accommodating UHPLC separation: quadrupole-TOF and quadrupole-Orbitrap (Q-Exactive). But what has changed since the Bioanalysis 2012 special focus issue is that the paradigm shift from SRM to HRMS is being explored for regulated bioanalysis, and at least three manuscripts in the 2013 HRMS in DMPK special issue are focusing on this new application. Unlike in discovery and nonregulated bioanalysis, in regulated bioanalyis the scope of the assay is carefully defined and assay parameters are validated for use over several years. Therefore, there are higher hurdles to apply non-targeted or undefined methods in the regulated environment. Experimental methods based on MSe have been shown to be a powerful approach for metabolite detection and characterization studies [6]. Although application of mass defect filtering methods allowed the elimination of endogenous interferences, deciphering and directly linking a particular fragment ion to a precursor ion was difficult and additional targeted MS/MS experiments were needed. Other workflows with a similar theme to MSe include the recently demonstrated FragAll or MSALL and SWATH [7]. Most recently, SWATH and SRMHR (aka MRMHR) were applied to improve the signal-to-noise ratio of quantitative bioanalysis as well as to screen for reactive metabolites [8,9]. SWATH and SRMHR methods are ideal for improving selectivity while maintaining sensitivity required for regulated bioanalytical methods used for quantitation of drugs and metabolites in clinical samples. Another feature that could easily improve productivity and provide a complete picture about a sample is within assay positive–negative switching, and recently within-assay positive–negative switching was used to increase throughput of a full-scan HRMS based drug–drug interaction assay [10]. These new additions to the HRMS workflow, such as MRMHR, SWATH and within-assay positive–negative switching, have started to pave the path to improve the selectivity, specificity and signal-to-noise ratio of DMPK assays and are poised to help the paradigm shift come to a completion.Financial & competing interests disclosureThe author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscript.References1 Korfmacher WA, Cox KA, Bryant MS et al. HPLC–API/MS/MS: a powerful tool for integrating drug metabolism into the drug discovery process. Drug Discov. Today2,532–537 (1997).Crossref, CAS, Google Scholar2 Clarke NJ, Rindgen D, Korfmacher WA, Cox KA. Systematic LC–MS metabolite identification in drug discovery. Anal. Chem.73(15),430A–439A (2001).Crossref, Medline, CAS, Google Scholar3 Gao H, Obach RS. Addressing MIST (metabolites in safety testing): bioanalytical approaches to address metabolite exposures in humans and animals. Curr. Drug Metab.12(6),578–86 (2011).Crossref, Medline, CAS, Google Scholar4 Ramanathan R, Jemal M, Ramagiri S et al. It is time for a paradigm shift in drug discovery bioanalysis: from SRM to HRMS. J. Mass Spectrom.46(6),595–601 (2011).Crossref, Medline, CAS, Google Scholar5 Josephs JL. HRMS: current usage, future directions and the promise of integration with unified data streams suited to post-acquisition mining. Bioanalyis4(5),501–503 (2012).Link, Google Scholar6 Bateman KP, Castro-Perez J, Wrona M et al. MSE with mass defect filtering for in vitro and in vivo metabolite identification. Rapid Commun. Mass Spectrom.21(9),1485–1496 (2007).Crossref, Medline, CAS, Google Scholar7 Hopfgartner G, Tonoli D, Varesio E. High-resolution mass spectrometry for integrated qualitative and quantitative analysis of pharmaceuticals in biological matrices. Anal. Bioanal. Chem.402(8),2587–2596 (2012).Crossref, Medline, CAS, Google Scholar8 Gu X, Ramanathan R, Shu YZ, Humphreys WG. Application of SWATH for detection of glutathione-trapped reactive metabolites and in vivo metabolite profile in biological samples. CPSA, Shanghai, China (2012).Google Scholar9 Ramanathan R, Ramagiri S, Yuska B et al. SWATH based pharmacokinetic quantification to increase selectivity, specificity and signal-to-noise ratio with the benefits of non-targeted approach on UHPLC–HRMS. Presented at: 61st ASMS Conference on Mass Spectrometry and Allied Topics. MN, USA, 9–13 June 2013.Google Scholar10 Ramanathan R, Yuska B, Comstock K et al. Evaluation of LC–HRMS full scan with positive-negative switching for increasing throughput of human in vitro cocktail drug–drug interaction assay. Presented at: 61st ASMS Conference on Mass Spectrometry and Allied Topics. MN, USA, 9–13 June 2013.Google Scholar101 Lord William Thomson Kelvin Biography. http://scienceworld.wolfram.com/biography/Kelvin.htmlGoogle Scholar102 US FDA. Guidance for Industry: Safety Testing of Drug Metabolites. www.fda.gov/cder/guidance/6897fnl.pdfGoogle ScholarFiguresReferencesRelatedDetailsCited ByHRMS in DMPKWalter Korfmacher & Ragu Ramanathan3 August 2016 | Bioanalysis, Vol. 8, No. 16Ranking Fragment Ions Based on Outlier Detection for Improved Label-Free Quantification in Data-Independent Acquisition LC–MS/MS14 October 2015 | Journal of Proteome Research, Vol. 14, No. 11Evaluation of peripheral blood microsampling techniques in combination with liquid chromatography-high resolution mass spectrometry for the determination of drug pharmacokinetics in clinical studies20 November 2013 | Drug Testing and Analysis, Vol. 6, No. 6Bioanalysis annual round-up: The Bioanalysis Editorial team is delighted to welcome you to this mid-year round-up23 September 2013 | Bioanalysis, Vol. 5, No. 18Preface to the 2013 Special Focus Issue of Bioanalysis on high-resolution MSWalter Korfmacher & Ragu Ramanathan30 May 2013 | Bioanalysis, Vol. 5, No. 10 Vol. 5, No. 10 Follow us on social media for the latest updates Metrics History Published online 30 May 2013 Published in print May 2013 Information© Future Science LtdKeywordsaccurate massADMEbiotransformationdrug metabolismion mobilityLC–HRMSQ-ExactiveQ-TOFquan–qualSWATHFinancial & competing interests disclosureThe author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.No writing assistance was utilized in the production of this manuscript.PDF download
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