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      LC-MS/MS Estimation of the Anti-Cancer Agent Tandutinib Levels in Human Liver Microsomes: Metabolic Stability Evaluation Assay

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          Abstract

          Purpose

          Tandutinib (MLN518 or CT 53518) (TND) is a novel, oral, small-molecule inhibitor of type III receptor tyrosine kinases utilized for the treatment of acute myeloid leukemia (AML).

          Materials and Methods

          In silico prediction of hepatic drug metabolism for TND was determined using the StarDrop® WhichP450™ module to confirm its metabolic liability. Second, an efficient and accurate LC-MS/MS method was established for TND quantification to evaluate metabolic stability. TND and entrectinib (ENC) (internal standard; IS) were resolved using an isocratic elution system with a reversed stationary phase (C 8 column).

          Results

          The established LC-MS/MS method exhibited linearity (5–500 ng/mL) with r 2 ≥0.9999 in the human liver microsomes matrix. The method sensitivity was indicated by the limit of quantification (3.8 ng/mL), and reproducibility was revealed by inter- and intraday precision and accuracy (below 10.5%). TND metabolic stability estimation was calculated using intrinsic clearance (22.03 µL/min/mg) and in vitro half-life (29.0 min) values.

          Conclusion

          TND exhibited a moderate extraction ratio indicative of good bioavailability. According to the literature, the approach developed in the present study is the first established LC-MS/MS method for assessing TND metabolic stability.

          Most cited references39

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          Cell signaling by receptor tyrosine kinases.

          Recent structural studies of receptor tyrosine kinases (RTKs) have revealed unexpected diversity in the mechanisms of their activation by growth factor ligands. Strategies for inducing dimerization by ligand binding are surprisingly diverse, as are mechanisms that couple this event to activation of the intracellular tyrosine kinase domains. As our understanding of these details becomes increasingly sophisticated, it provides an important context for therapeutically countering the effects of pathogenic RTK mutations in cancer and other diseases. Much remains to be learned, however, about the complex signaling networks downstream from RTKs and how alterations in these networks are translated into cellular responses.
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            Physiological parameters in laboratory animals and humans.

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              The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data.

              We describe a comprehensive retrospective analysis in which the abilities of several methods by which human pharmacokinetic parameters are predicted from preclinical pharmacokinetic data and/or in vitro metabolism data were assessed. The prediction methods examined included both methods from the scientific literature as well as some described in this report for the first time. Four methods were examined for their ability to predict human volume of distribution. Three were highly predictive, yielding, on average, predictions that were within 60% to 90% of actual values. Twelve methods were assessed for their utility in predicting clearance. The most successful allometric scaling method yielded clearance predictions that were, on average, within 80% of actual values. The best methods in which in vitro metabolism data from human liver microsomes were scaled to in vivo clearance values yielded predicted clearance values that were, on average, within 70% to 80% of actual values. Human t1/2 was predicted by combining predictions of human volume of distribution and clearance. The best t1/2 prediction methods successfully assigned compounds to appropriate dosing regimen categories (e.g., once daily, twice daily and so forth) 70% to 80% of the time. In addition, correlations between human t1/2 and t1/2 values from preclinical species were also generally successful (72-87%) when used to predict human dosing regimens. In summary, this retrospective analysis has identified several approaches by which human pharmacokinetic data can be predicted from preclinical data. Such approaches should find utility in the drug discovery and development processes in the identification and selection of compounds that will possess appropriate pharmacokinetic characteristics in humans for progression to clinical trials.
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                Author and article information

                Journal
                Drug Des Devel Ther
                Drug Des Devel Ther
                dddt
                dddt
                Drug Design, Development and Therapy
                Dove
                1177-8881
                23 October 2020
                2020
                : 14
                : 4439-4449
                Affiliations
                [1 ]1 Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University , Riyadh, Saudi Arabia
                Author notes
                Correspondence: Ali S Abdelhameed Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University , P.O. Box 2457, Riyadh11451, Saudi ArabiaTel +966 1146 70237Fax +966 1146 76220 Email asaber@ksu.edu.sa
                Author information
                http://orcid.org/0000-0002-1147-4960
                http://orcid.org/0000-0002-5910-2832
                Article
                274118
                10.2147/DDDT.S274118
                7591096
                a4f39c56-322a-42ae-80a2-18757d365bcd
                © 2020 Attwa et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                : 04 August 2020
                : 09 October 2020
                Page count
                Figures: 5, Tables: 7, References: 42, Pages: 11
                Categories
                Original Research

                Pharmacology & Pharmaceutical medicine
                tandutinib,metabolic stability assessment,in vitro half-life,validated lc-ms/ms methodology

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