LC–MS/MS Estimation of Rociletinib Levels in Human Liver Microsomes: Application to Metabolic Stability Estimation

References

• JemalA, SiegelR, WardE, et al. Cancer statistics. CA Cancer J Clin. 2008;58(2):71–96.18287387
   PubMed Web of Science ®Google Scholar
• BarinagaM. From bench top to bedside. Am Assoc Adv Sci. 1997;278:1036–1039. doi:10.1126/science.278.5340.1036
   Web of Science ®Google Scholar
• FerlayJ, SoerjomataramI, DikshitR, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015;136(5):E359–E386. doi:10.1002/ijc.2921025220842
   PubMed Web of Science ®Google Scholar
• EttingerDS, AkerleyW, BeplerG, et al. Non–small cell lung cancer. J Natl Compr Canc Netw. 2010;8(7):740–801. doi:10.6004/jnccn.2010.005620679538
   PubMed Web of Science ®Google Scholar
• LarsenJE, CasconeT, GerberDE, HeymachJV, MinnaJD. Targeted therapies for lung cancer: clinical experience and novel agents. Cancer J. 2011;17(6):512. doi:10.1097/PPO.0b013e31823e701a22157296
   PubMed Web of Science ®Google Scholar
• SharmaSV, BellDW, SettlemanJ, HaberDA. Epidermal growth factor receptor mutations in lung cancer. Nat Rev Cancer. 2007;7(3):169–181. doi:10.1038/nrc208817318210
   PubMed Web of Science ®Google Scholar
• MokTS, WuY-L, ThongprasertS, et al. Gefitinib or carboplatin–paclitaxel in pulmonary adenocarcinoma. N Engl J Med. 2009;361(10):947–957. doi:10.1056/NEJMoa081069919692680
   PubMed Web of Science ®Google Scholar
• RosellR, CarcerenyE, GervaisR, et al. Erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised Phase 3 trial. Lancet Oncol. 2012;13(3):239–246. doi:10.1016/S1470-2045(11)70393-X22285168
   PubMed Web of Science ®Google Scholar
• SequistL, YangJ, YamamotoN, et al. Phase III study of afatinib or cisplatin/pemetrexed in metastatic lung adenocarcinoma patients with epidermal growth factor receptor mutations. J Clin Oncol. 2013;31:3327–3334. doi:10.1200/JCO.2012.44.280623816960
   PubMed Web of Science ®Google Scholar
• SequistLV, WaltmanBA, Dias-SantagataD, et al. Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci Transl Med. 2011;3(75):75ra26–75ra26. doi:10.1126/scitranslmed.3002003
   PubMed Web of Science ®Google Scholar
• HelenaAY, ArcilaME, RekhtmanN, et al. Analysis of tumor specimens at the time of acquired resistance to EGFR-TKI therapy in 155 patients with EGFR-mutant lung cancers. Clin Cancer Res. 2013;19(8):2240–2247. doi:10.1158/1078-0432.CCR-12-224623470965
   PubMed Web of Science ®Google Scholar
• WalterAO, SjinRTT, HaringsmaHJ, et al. Discovery of a mutant-selective covalent inhibitor of EGFR that overcomes T790M-mediated resistance in NSCLC. Cancer Discov. 2013;3(12):1404–1415. doi:10.1158/2159-8290.CD-13-031424065731
   PubMed Web of Science ®Google Scholar
• AmerSM, KadiAA, DarwishHW, AttwaMW. Liquid chromatography tandem mass spectrometry method for the quantification of vandetanib in human plasma and rat liver microsomes matrices: metabolic stability investigation. Chem Cent J. 2017;11(1):45. doi:10.1186/s13065-017-0274-429086823
   PubMedGoogle Scholar
• RowlandM, BenetLZ, GrahamGG. Clearance concepts in pharmacokinetics. J Pharmacokinet Biopharm. 1973;1(2):123–136. doi:10.1007/BF010596264764426
   PubMedGoogle Scholar
• WilkinsonGR, ShandDG. A physiological approach to hepatic drug clearance. Clin Pharmacol Ther. 1975;18(4):377–390. doi:10.1002/cpt19751843771164821
   PubMed Web of Science ®Google Scholar
• HoustonJB. Utility of in vitro drug metabolism data in predicting in vivo metabolic clearance. Biochem Pharmacol. 1994;47(9):1469–1479. doi:10.1016/0006-2952(94)90520-78185657
   PubMed Web of Science ®Google Scholar
• ObachRS, BaxterJG, ListonTE, et al. The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data. J Pharmacol Exp Ther. 1997;283(1):46–58.9336307
   PubMed Web of Science ®Google Scholar
• BaranczewskiP, StanczakA, SundbergK, et al. Introduction to in vitro estimation of metabolic stability and drug interactions of new chemical entities in drug discovery and development. Pharmacol Rep. 2006;58(4):453.16963792
   PubMed Web of Science ®Google Scholar
• DarwishHW, AttwaMW, KadiAA. Rapid validated liquid chromatographic method coupled with Tandem mass spectrometry for quantification of nintedanib in human plasma. Trop J Pharm Res. 2016;15(11):2467–2473. doi:10.4314/tjpr.v15i11.23
   Web of Science ®Google Scholar
• DarwishHW, KadiAA, AttwaMW, AlmutairiHS. Investigation of metabolic stability of the novel ALK inhibitor brigatinib by liquid chromatography tandem mass spectrometry. Clin Chim Acta. 2018;480:180–185. doi:10.1016/j.cca.2018.02.01629458050
   PubMed Web of Science ®Google Scholar
• AttwaMW, KadiAA, DarwishHW, AmerSM, AlrabiahH. A reliable and stable method for the determination of foretinib in human plasma by LC-MS/MS: application to metabolic stability investigation and excretion rate. Eur J Mass Spectrometry. 2018;24(4):344–351. doi:10.1177/1469066718768327
   Web of Science ®Google Scholar
• TyzackJD, KirchmairJ. Computational methods and tools to predict cytochrome P450 metabolism for drug discovery. Chem Biol Drug Des. 2019;93(4):377–386. doi:10.1111/cbdd.1344530471192
   PubMed Web of Science ®Google Scholar
• AttwaMW, KadiAA, AbdelhameedAS, AlhazmiHA. Metabolic stability assessment of new PARP inhibitor talazoparib using validated LC-MS/MS methodology: in silico metabolic vulnerability and toxicity studies. Drug Des Devel Ther. 2020;14:783–793. doi:10.2147/DDDT.S239458
   PubMed Web of Science ®Google Scholar
• AttwaMW, KadiAA, AbdelhameedAS. Phase I metabolic profiling and unexpected reactive metabolites in human liver microsome incubations of X-376 using LC-MS/MS: bioactivation pathway elucidation and in silico toxicity studies of its metabolites. RSC Adv. 2020;10(9):5412–5427. doi:10.1039/C9RA09115G
   PubMed Web of Science ®Google Scholar
• AlsubiTA, AttwaMW, BakheitAH, DarwishHW, AbuelizzHA, KadiAA. In silico and in vitro metabolism of ribociclib: a mass spectrometric approach to bioactivation pathway elucidation and metabolite profiling. RSC Adv. 2020;10(38):22668–22683. doi:10.1039/D0RA01624A
   Web of Science ®Google Scholar
• U.S. Food and Drugs Adminstration. Bioanalytical method validation, guidance for industry; 2018. Available from:https://www.fda.gov/media/70858/download. Accessed 207, 2021.
   Google Scholar
• KadianN, RajuKSR, RashidM, MalikMY, TanejaI, WahajuddinM. Comparative assessment of bioanalytical method validation guidelines for pharmaceutical industry. J Pharm Biomed Anal. 2016;126:83–97. doi:10.1016/j.jpba.2016.03.05227179186
   PubMed Web of Science ®Google Scholar
• AttwaMW, KadiAA, DarwishHW, AmerSM, Al-shakliahNS. Identification and characterization of in vivo, in vitro and reactive metabolites of vandetanib using LC–ESI–MS/MS. Chem Cent J. 2018;12(1):99. doi:10.1186/s13065-018-0467-530251155
   PubMedGoogle Scholar
• AbdelhameedAS, AttwaMW, KadiAA. An LC–MS/MS method for rapid and sensitive high‐throughput simultaneous determination of various protein kinase inhibitors in human plasma. Biomed Chromatography. 2017;31(2):e3793. doi:10.1002/bmc.3793
   Web of Science ®Google Scholar
• AlRabiahH, KadiAA, AljoharHI, et al. A new validated HPLC-MS/MS method for quantification and pharmacokinetic evaluation of dovitinib, a multi-kinase inhibitor, in mouse plasma. Drug Des Devel Ther. 2020;14:407. doi:10.2147/DDDT.S223573
   PubMed Web of Science ®Google Scholar
• AttwaMW, KadiAA, AbdelhameedAS. Detection and characterization of olmutinib reactive metabolites by LC–MS/MS: elucidation of bioactivation pathways. J Sep Sci. 2020;43(4):708–718. doi:10.1002/jssc.20190081831788977
   PubMed Web of Science ®Google Scholar
• AttwaMW, DarwishHW, AlhazmiHA, KadiAA. Investigation of metabolic degradation of new ALK inhibitor: entrectinib by LC-MS/MS. Clinica Chimica Acta. 2018;485:298–304. doi:10.1016/j.cca.2018.07.009
   PubMed Web of Science ®Google Scholar
• DaviesB, MorrisT. Physiological parameters in laboratory animals and humans. Pharm Res. 1993;10(7):1093–1095. doi:10.1023/A:10189436131228378254
   PubMed Web of Science ®Google Scholar
• BarterZE, BaylissMK, BeaunePH, et al. Scaling factors for the extrapolation of in vivo metabolic drug clearance from in vitro data: reaching a consensus on values of human micro-somal protein and hepatocellularity per gram of liver. Curr Drug Metab. 2007;8(1):33–45. doi:10.2174/13892000777931505317266522
   PubMed Web of Science ®Google Scholar
• IwatsuboT, SuzukiH, SugiyamaY. Prediction of species differences (rats, dogs, humans) in the in vivo metabolic clearance of YM796 by the liver from in vitro data. J Pharmacol Exp Ther. 1997;283(2):462–469.9353358
   PubMed Web of Science ®Google Scholar
• TanL, KirchmairJ. Software for metabolism prediction. In: Kirchmair J, editor. Drug Metabolism Prediction. Wiley‐VCH Verlag GmbH & Co. KGaA; 2014:27–52. doi:10.1002/9783527673261
   Google Scholar
• HuntPA, SegallMD, TyzackJD. WhichP450: a multi-class categorical model to predict the major metabolising CYP450 isoform for a compound. J Comput Aided Mol Des. 2018;32(4):537–546. doi:10.1007/s10822-018-0107-029464466
   PubMed Web of Science ®Google Scholar
• ShinGY, LeH, KhojastehC. Comparison of metabolic soft spot predictions of CYP3A4, CYP2C9 and CYP2D6 substrates using metasite and stardrop. Comb Chem High Throughput Screen. 2011;14(9):811–823. doi:10.2174/13862071179695717021605066
   PubMed Web of Science ®Google Scholar
• AttwaMW, KadiAA, AbdelhameedAS. Reactive intermediates and bioactivation pathways characterization of avitinib by LC–MS/MS: in vitro metabolic investigation. J Pharm Biomed Anal. 2019;164:659–667. doi:10.1016/j.jpba.2018.11.03330472584
   PubMed Web of Science ®Google Scholar
• KadiAA, AbdelhameedAS, DarwishHW, AttwaMW, Al‐ShakliahNS. A highly efficient and sensitive LC‐MS/MS method for the determination of afatinib in human plasma: application to a metabolic stability study. Biomed Chromatography. 2016;30(8):1248–1255. doi:10.1002/bmc.3674
   Web of Science ®Google Scholar
• ScottWJ, HentemannMF, RowleyRB, et al. Discovery and SAR of novel 2, 3‐dihydroimidazo [1, 2‐c] quinazoline PI3K inhibitors: identification of copanlisib (BAY 80‐6946). ChemMedChem. 2016;11(14):1517. doi:10.1002/cmdc.20160014827310202
   PubMed Web of Science ®Google Scholar
• Attwa MohamedW, KadiAA, DarwishHW, AbdelhameedAS. Investigation of the metabolic stability of olmutinib by validated LC-MS/MS: quantification in human plasma. RSC Adv. 2018;8(70):40387–40394. doi:10.1039/C8RA08161A
   PubMed Web of Science ®Google Scholar
• KadiAA, DarwishHW, AttwaMW, AmerSM. Validated LC-MS/MS method for the quantification of ponatinib in plasma: application to metabolic stability. PLoS One. 2016;11(10):e0164967. doi:10.1371/journal.pone.016496727764191
   PubMed Web of Science ®Google Scholar
• ManzoA, MontaninoA, CostanzoR, et al. Chapter 33 - EGFR mutations: best results from second- and third-generation tyrosine kinase inhibitors. In: DammaccoF, SilvestrisF, editors. Oncogenomics. Academic Press; 2019. 477–486.
   Google Scholar
• LeahyDE. Integrating in vitro ADMET data through generic physiologically based pharmacokinetic models. Expert Opin Drug Metab Toxicol. 2006;2(4):619–628. doi:10.1517/17425255.2.4.61916859409
   PubMed Web of Science ®Google Scholar