Prediction of Tumor-to-Plasma Ratios of Basic Compounds in Subcutaneous Xenograft Mouse Models
- 81 Downloads
Predicting target site drug concentrations is of key importance for rank ordering compounds before proceeding to chronic pharmacodynamic models. We propose generic tumor-specific correlation-based regression equations to predict tumor-to-plasma ratios (tumor-Kps) in slow- and fast-growing xenograft mouse models.
Disposition of 14 basic small molecules was investigated extensively in mouse plasma, tissues and tumors after a single oral dose administration. Linear correlation was assessed and compared between tumor-Kp and normal tissue-to-plasma ratio (tissue-Kps) separately for each tumor xenograft. The developed regression equations were validated by leave-one-out cross-validation (LOOCV) method.
Both slow- and fast-growing tumor-Kps showed good correlation (r 2 ≥ 0.7) with majority of the normal tissue-Kps. Substantial difference was observed in the slopes of developed equations between two xenografts, which was in line with observed difference in tumor distribution. The linear correlations between tumor-Kp and skin- or spleen-Kp were within the acceptable statistical criteria (LOOCV) across xenografts and the class of compounds evaluated. Since > 70% of tumor-Kps from the test data sets were predicted within a factor of twofold for both slow- and fast-growing xenograft mouse models, the results validate the applicability of the developed equations across xenografts.
Tumor-specific correlation-based regression equations were developed and their applicability was adequately validated across xenografts. These equations could be successfully translated to predict tumor concentrations in order to preclude experimental tumor-Kp determination.
We are grateful for the support of senior management of Lupin Limited (Research Park), Pune, India, and technical assistance of Mr. Tariq Bhat and Dr. Praveen Kumar during development of human xenograft mouse models.
The present work was supported by and conducted at Lupin Ltd (Research Park), Pune.
Compliance with Ethical Standards
Conflict of interest
Prashant B. Nigade, Jayasagar Gundu, K. Sreedhara Pai and Kumar V.S. Nemmani have no conflict of interest.
In vivo studies were performed at the AAALAC accredited facility (Lupin Limited, Pune, India) in accordance with the CPCSEA (Committee for the Purpose of Control and Supervision of Experiments on Animals) guidelines and as per Institutional Animal Ethics Committee (IAEC) approved experimental protocols numbers: IAEC/PK/534, IAEC/PK/619 and IAEC/PK/620.
- 15.Poulin P, Dambach DM, Hartley DH, Ford K, Theil FP, Harstad E, Halladay J, Choo E, Boggs J, Liederer BM, Dean B, Diaz D. An algorithm for evaluating potential tissue drug distribution in toxicology studies from readily available pharmacokinetic parameters. J Phar Sci. 2013;102(10):3816–29.CrossRefGoogle Scholar
- 18.Patrick P, Chen YH, Ding X, Gould SE, Hop CE, Messick K, Oeh J, Liederer BM. Prediction of drug distribution in subcutaneous xenografts of human tumor cell lines and healthy tissues in mouse: application of the tissue composition-based model to antineoplastic drugs. J Pharm Sci. 2015;104(4):1508–21.CrossRefGoogle Scholar
- 19.Williamson MJ, Silva MD, Terkelsen J, Robertson R, Yu L, Xia C, Hatsis P, Bannerman B, Babcock T, Cao Y, Kupperman E. The relationship among tumor architecture, pharmacokinetics, pharmacodynamics, and efficacy of bortezomib in mouse xenograft models. Mol Cancer Ther. 2009;8(12):3234–43.CrossRefPubMedGoogle Scholar
- 21.Moore DS, Notz WI, Flinger MA. The basic practice of statistics. 6th ed. New York: W. H. Freeman and Company; 2013. p. 138.Google Scholar
- 23.The Report From the Expert Group on (Quantitative) Structure-Activity Relationships [(Q)Sars] on the Principles for the Validation Of (Q)Sars. OECD Environment Health and Safety Publications Series on Testing and Assessment No. 49. OECD: Paris, 2004.Google Scholar
- 24.Guidance Document on the Validation of (Quantitative) Structure-Activity Relationship [(Q)SAR] Models. OECD Environment Health and Safety Publications Series on Testing and Assessment No. 69. OECD: Paris, 2007.Google Scholar
- 31.Bradshaw-Pierce EL, Pitts TM, Tan AC, McPhillips K, West M, Gustafson DL, Halsey C, Nguyen L, Lee NV, Kan JL, Murray BW, Eckhardt SG. Tumor p-glycoprotein correlates with efficacy of PF-3758309 in in vitro and in vivo models of colorectal cancer. Front Pharmacol. 2013;4:22. https://doi.org/10.3389/fphar.2013.00022.CrossRefPubMedPubMedCentralGoogle Scholar