Dose Finding in Single Dose Studies by Allometric Scaling

  • Zheng LuEmail author
  • Rüdiger Kaspera
  • Yoichi Naritomi
  • Tianli Wang
Living reference work entry


This chapter reviews common methodologies and applications of scaling for clearance (CL), oral bioavailability (F), volume of distribution (Vd) and half-life (t1/2) with respect to its procedures, evaluation, performance and modifications for the dose finding in single dose studies. Methods of allometric scaling have been well established in drug development to predict the dose for single dose studies for first in human trials from preclinical data, generally from one to three or more species such as mouse, rat, dog or monkey. Allometric scaling is the study of body size to diverse biological characteristics, like clearance. The clearance and other PK parameters are proportional to the body weight among different species. Dose finding in single dose studies by allometric scaling can be either by dose-by-factor approach or pharmacokinetically-guided approach. Besides traditional simple allometry and allometric scaling based on the rule of exponents, many newly proposed methods based on the allometric scaling with different correction factors have been shown either to improve the accuracy of predications or to explore the possibilities of predictions for protein therapeutics. Although the allometric scaling approaches have been widely used to predict human PK parameters of small molecules which is critical to next dose finding step for single ascending dose study, there is a need to have more mechanistic methods based on the allometric scaling, especially for protein therapeutics or some formulations, like liposomal, to improve the predictabilities of first-in-human dose in single ascending dose study.

References and Further Reading

  1. Amantana A, Chen Y, Tyavanagimatt SR, Jones KF, Jordan R, Chinsangaram J, Bolken TC, Leeds JM, Hruby DE (2013) Pharmacokinetics and interspecies allometric scaling of ST-246, an oral antiviral therapeutic for treatment of orthopoxvirus infection. PLoS One 8(4):e61514CrossRefPubMedPubMedCentralGoogle Scholar
  2. Boxenbaum H (1984) Interspecies pharmacokinetic scaling and the evolutionary-comparative paradigm. Drug Metab Rev 15(5–6):1071–1121CrossRefPubMedGoogle Scholar
  3. Caldwell GW, Masucci JA, Yan Z, Hageman W (2004) Allometric scaling of pharmacokinetic parameters in drug discovery: can human CL, Vss and t1/2 be predicted from in-vivo rat data? Eur J Drug Metab Pharmacokinet 29(2):133–143CrossRefPubMedGoogle Scholar
  4. Caron WP, Clewell H, Dedrick R, Ramanathan RK, Davis WL, Yu N, Tonda M, Schellens JH, Beijnen JH, Zamboni WC (2011) Allometric scaling of pegylated liposomal anticancer drugs. J Pharmacokinet Pharmacodyn 38(5):653–669CrossRefPubMedGoogle Scholar
  5. Deng R, Iyer S, Theil FP, Mortensen DL, Fielder PJ, Prabhu S (2011) Projecting human pharmacokinetics of therapeutic antibodies from nonclinical data: what have we learned? MAbs 3(1):61–66CrossRefPubMedPubMedCentralGoogle Scholar
  6. Expert Scientific Group (2006) Expert scientific group on phase one clinical trials final report. Stationery Office, NorwichGoogle Scholar
  7. Estimating the safe starting dose in clinical trials for therapeutics in adult healthy volunteers (2002) U.S. Department of Health and Human Services Food and Drug Administration, Centre for Drug Evaluation and Research (CDER), Centre for Biologics Evaluation and Research (CBER)Google Scholar
  8. Hosea NA, Collard WT, Cole S, Maurer TS, Fang RX, Jones H, Kakar SM, Nakai Y, Smith BJ, Webster R, Beaumont K (2009) Prediction of human pharmacokinetics from preclinical information: comparative accuracy of quantitative prediction approaches. J Clin Pharmacol 49(5):513–533CrossRefPubMedGoogle Scholar
  9. Keumhan N, Wonku K (2017) Calculation of a first-in-man dose of 7-O-Succinyl Macrolactin A based on allometric scaling of data from mice, rats and dogs. Biomol Ther, pp 1–11Google Scholar
  10. Lave T, Dupin S, Schmitt C, Chou RC, Jaeck D, Coassolo P (1997) Integration of in vitro data into allometric scaling to predict hepatic metabolic clearance in man: application to 10 extensively metabolized drugs. J Pharm Sci 86(5):584–590CrossRefPubMedGoogle Scholar
  11. Ling J, Zhou H, Jiao Q, Davis HM (2009) Interspecies scaling of therapeutic monoclonal antibodies: initial look. J Clin Pharmacol 49(12):1382–1402CrossRefPubMedGoogle Scholar
  12. Lombardo F, Waters NJ, Argikar UA, Dennehy MK, Zhan J, Gunduz M, Harriman SP, Berellini G, Liric Rajlic I, Obach RS (2013a) Comprehensive assessment of human pharmacokinetic prediction based on in vivo animal pharmacokinetic data, part 2: clearance. J Clin Pharmacol 53(2):178–191CrossRefPubMedGoogle Scholar
  13. Lombardo F, Waters NJ, Argikar UA, Dennehy MK, Zhan J, Gunduz M, Harriman SP, Berellini G, Rajlic IL, Obach RS (2013b) Comprehensive assessment of human pharmacokinetic prediction based on in vivo animal pharmacokinetic data, part 1: volume of distribution at steady state. J Clin Pharmacol 53(2):167–177CrossRefPubMedGoogle Scholar
  14. Lombardo F, Berellini G, Labonte LR, Liang G, Kim S (2016) Systematic evaluation of Wajima superposition (steady-state concentration to mean residence time) in the estimation of human intravenous pharmacokinetic profile. J Pharm Sci 105(3):1277–1287CrossRefPubMedGoogle Scholar
  15. Mahmood I (1998) Interspecies scaling: predicting volumes, mean residence time and elimination half-life. Some suggestions. J Pharm Pharmacol 50(5):493–499CrossRefPubMedGoogle Scholar
  16. Mahmood I (1999) Prediction of clearance, volume of distribution and half-life by allometric scaling and by use of plasma concentrations predicted from pharmacokinetic constants: a comparative study. J Pharm Pharmacol 51(8):905–910CrossRefPubMedGoogle Scholar
  17. Mahmood I (2005) Interspecies pharmacokinetic scaling: principles and application of allometric scaling. Pine House Publishers, RockvilleGoogle Scholar
  18. Mahmood I (2009) Pharmacokinetic allometric scaling of coagulation factors and tissue-type plasminogen activators. Haemophilia 15(5):1109–1117CrossRefPubMedGoogle Scholar
  19. Mahmood I, Balian JD (1996) Interspecies scaling: predicting clearance of drugs in humans. Three different approaches. Xenobiotica 26(9):887–895CrossRefPubMedGoogle Scholar
  20. Miyamoto M, Iwasaki S, Chisaki I, Nakagawa S, Amano N, Hirabayashi H (2017) Comparison of predictability for human pharmacokinetics parameters among monkeys, rats, and chimeric mice with humanised liver. Xenobiotica 47(12):1052–1063CrossRefPubMedGoogle Scholar
  21. Poulin P1, Jones RD, Jones HM, Gibson CR, Rowland M, Chien JY, Ring BJ, Adkison KK, Ku MS, He H, Vuppugalla R, Marathe P, Fischer V, Dutta S, Sinha VK, Björnsson T, Lavé T, Yates JW (2011) PHRMA CPCDC initiative on predictive models of human pharmacokinetics, part 5: prediction of plasma concentration-time profiles in human by using the physiologically-based pharmacokinetic modeling approach. J Pharm Sci 100(10):4127–4157CrossRefPubMedGoogle Scholar
  22. Ring BJ, Chien JY, Adkison KK, Jones HM, Rowland M, Jones RD, Yates JW, MS K, Gibson CR, He H, Vuppugalla R, Marathe P, Fischer V, Dutta S, Sinha VK, Björnsson T, Lavé T, Poulin P (2011) PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 3: comparative assessement of prediction methods of human clearance. J Pharm Sci 100(10):4090–4110CrossRefPubMedGoogle Scholar
  23. Sanoh S, Naritomi Y, Fujimoto M, Sato K, Kawamura A, Horiguchi A, Sugihara K, Kotake Y, Ohshita H, Tateno C, Horie T, Kitamura S, Ohta S (2015) Predictability of plasma concentration-time curves in humans using single-species allometric scaling of chimeric mice with humanized liver. Xenobiotica 45(7):605–614CrossRefPubMedGoogle Scholar
  24. Sinha VK, Vaarties K, De Buck SS, Fenu LA, Nijsen M, Gilissen RA, Sanderson W, Van Uytsel K, Hoeben E, Van Peer A, Mackie CE, Smit JW (2011) Towards a better prediction of peak concentration, volume of distribution and half-life after oral drug administration in man, using allometry. Clin Pharmacokinet 50(5):307–318CrossRefPubMedGoogle Scholar
  25. Stepensky D (2011) The Øie-Tozer model of drug distribution and its suitability for drugs with different pharmacokinetic behavior. Expert Opin Drug Metab Toxicol 7(10):1233–1243CrossRefPubMedGoogle Scholar
  26. Stoner CL, Cleton A, Johnson K, DM O, Hallak H, Brodfuehrer J, Surendran N, Han HK (2004) Integrated oral bioavailability projection using in vitro screening data as a selection tool in drug discovery. Int J Pharm 269(1):241–249CrossRefPubMedGoogle Scholar
  27. Tang H, Mayersohn M (2005) A novel model for prediction of human drug clearance by allometric scaling. Drug Metab Dispos 33(9):1297–1303CrossRefPubMedGoogle Scholar
  28. Vuppugalla R, Marathe P, He H, Jones RD, Yates JW, Jones HM, Gibson CR, Chien JY, Ring BJ, Adkison KK, MS K, Fischer V, Dutta S, Sinha VK, Björnsson T, Lavé T, Poulin P (2011) PhRMA CPCDC initiative on predictive models of human pharmacokinetics, part 4: prediction of plasma concentration-time profiles in human from in vivo preclinical data by using the Wajima approach. J Pharm Sci 100(10):4111–4126CrossRefPubMedGoogle Scholar
  29. Wajima T, Fukumura K, Yano Y, Oguma T (2003) Prediction of human pharmacokinetics from animal data and molecular structural parameters using multivariate regression analysis: oral clearance. J Pharm Sci 92(12):2427–2440CrossRefPubMedGoogle Scholar
  30. Wang J, Iyer S, Fielder PJ, Davis JD, Deng R (2016a) Projecting human pharmacokinetics of monoclonal antibodies from nonclinical data: comparative evaluation of prediction approaches in early drug development. Biopharm Drug Dispos 37(2):51–65CrossRefPubMedGoogle Scholar
  31. Wang L, Qiang W, Cheng Z (2016b) Allometric scaling of therapeutic monoclonal antibodies using antigen concentration as a correction factor: application to the human clearance prediction. J Pharm Sci 105(3):1335–1340CrossRefPubMedGoogle Scholar
  32. Ward KW, Smith BR (2004) A comprehensive quantitative and qualitative evaluation of extrapolation of intravenous pharmacokinetic parameters from rat, dog, and monkey to humans. I. Clearance. Drug Metab Dispos 32(6):603–611CrossRefPubMedGoogle Scholar
  33. Waters NJ, Lombardo F (2010) Use of the Øie-Tozer model in understanding mechanisms and determinants of drug distribution. Drug Metab Dispos 38(7):1159–1165CrossRefPubMedGoogle Scholar
  34. West LJ, Pierce CM, Thomas WD (1962) Lysergic acid diethylamide: its effects on a male Asiatic elephant. Science 138(3545):1100–1103CrossRefPubMedGoogle Scholar
  35. Zou P, Yu Y, Zheng N, Yang Y, Paholak HJ, LX Y, Sun D (2012a) Applications of human pharmacokinetic prediction in first-in-human dose estimation. AAPS J 14(2):262–281CrossRefPubMedPubMedCentralGoogle Scholar
  36. Zou P, Zheng N, Yang Y, LX Y, Sun D (2012b) Prediction of volume of distribution at steady state in humans: comparison of different approaches. Expert Opin Drug Metab Toxicol 8(7):855–872CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Zheng Lu
    • 1
    Email author
  • Rüdiger Kaspera
    • 2
  • Yoichi Naritomi
    • 3
  • Tianli Wang
    • 1
  1. 1.Clinical Pharmacology and Exploratory DevelopmentAstellas Pharma, NorthbrookILUSA
  2. 2.Clinical Pharmacology and Exploratory DevelopmentAstellas Pharma Europe B.V.LeidenThe Netherlands
  3. 3.Analysis and Pharmacokinetics Research Labs.Astellas Pharma Inc.IbarakiJapan

Personalised recommendations