The AAPS Journal

, 11:602 | Cite as

Practical Anticipation of Human Efficacious Doses and Pharmacokinetics Using In Vitro and Preclinical In Vivo Data

  • Tycho HeimbachEmail author
  • Suresh B. Lakshminarayana
  • Wenyu Hu
  • Handan He
Research Article Theme: Towards Integrated ADME Prediction: Past, Present, and Future Directions


Accurate predictions of human pharmacokinetic and pharmacodynamic (PK/PD) profiles are critical in early drug development, as safe, efficacious, and “developable” dosing regimens of promising compounds have to be identified. While advantages of successful integration of preclinical PK/PD data in the “anticipation” of human doses (AHD) have been recognized, pharmaceutical scientists have faced difficulties with practical implementation, especially for PK/PD profile projections of compounds with challenging absorption, distribution, metabolism, excretion and formulation properties. In this article, practical projection approaches for formulation-dependent human PK/PD parameters and profiles of Biopharmaceutics Classification System classes I-IV drugs based on preclinical data are described. Case examples for “AHD” demonstrate the utility of preclinical and clinical PK/PD modeling for formulation risk identification, lead candidate differentiation, and prediction of clinical outcome. The application of allometric scaling methods and physiologically based pharmacokinetic approaches for clearance or volume of distribution projections is described using GastroPlus™. Methods to enhance prediction confidence such as in vitroin vivo extrapolations in clearance predictions using in vitro microsomal data are discussed. Examples for integration of clinical PK/PD and formulation data from frontrunner compounds via “reverse pharmacology strategies” that minimize uncertainty with PK/PD predictions are included. The use of integrated softwares such as GastroPlus™ in combination with established PK projection methods allow the projection of formulation-dependent preclinical and human PK/PD profiles required for compound differentiation and development risk assessments.

Key words

formulation human dose prediction modeling PBPK PK/PD 


  1. 1.
    Lowe PJ, Hijazi Y, Luttringer O, Yin H, Sarangapani R, Howard D. On the anticipation of the human dose in first-in-man trials from preclinical and prior clinical information in early drug development. Xenobiotica. 2007;37:1331–54.PubMedCrossRefGoogle Scholar
  2. 2.
    Thomas VH, Bhattachar S, Hitchingham L, Zocharski P, Naath M, Surendran N, et al. The road map to oral bioavailability: an industrial perspective. Expert Opin Drug Metab Toxicol. 2006;2:591–608.PubMedCrossRefGoogle Scholar
  3. 3.
    Miller R, Ewy W, Corrigan Brian W, Ouellet D, Hermann D, Kowalski Kenneth G, et al. How modeling and simulation have enhanced decision making in new drug development. J Pharmacokinet Pharmacodyn. 2005;32:185–97.PubMedCrossRefGoogle Scholar
  4. 4.
    Huang C, Zheng M, Yang Z, Rodrigues AD, Marathe P. Projection of exposure and efficacious dose prior to first-in-human studies: how successful have we been? Pharm Res. 2008;25:713–26.PubMedCrossRefGoogle Scholar
  5. 5.
    Amidon GL, Lennernaes H, Shah VP, Crison JR. A theoretical basis for a biopharmaceutic drug classification: the correlation of in vitro drug product dissolution and in vivo bioavailability. Pharm Res. 1995;12:413–20.PubMedCrossRefGoogle Scholar
  6. 6.
    Custodio JM, Wu C-Y, Benet LZ. Predicting drug disposition, absorption/elimination/transporter interplay and the role of food on drug absorption. Adv Drug Deliv Rev. 2008;60:717–33.PubMedCrossRefGoogle Scholar
  7. 7.
    Li S, He H, Parthiban LJ, Yin H, Serajuddin ATM. IV–IVC considerations in the development of immediate-release oral dosage form. J Pharm Sci. 2005;94:1396–417.PubMedCrossRefGoogle Scholar
  8. 8.
    Lipinski CA. Drug-like properties and the causes of poor solubility and poor permeability. J Pharmacol Toxicol Methods. 2001;44:235–49.CrossRefGoogle Scholar
  9. 9.
    Kasim NA, Whitehouse M, Ramachandran C, Bermejo M, Lennernaes H, Hussain AS, et al. Molecular properties of WHO essential drugs and provisional biopharmaceutical classification. Mol Pharm. 2004;1:85–96.PubMedCrossRefGoogle Scholar
  10. 10.
    Gabrielsson J, Dolgos H, Gillberg PG, Bredberg U, Benthem B, Duker G. Early integration of pharmacokinetic and dynamic reasoning is essential for optimal development of lead compounds: strategic considerations. Drug Discov Today. 2009;14:358–72.PubMedCrossRefGoogle Scholar
  11. 11.
    Mahmood I. Prediction of human drug clearance from animal data: application of the rule of exponents and ‘fu corrected intercept method’ (FCIM). J Pharm Sci. 2006;95:1810–21.PubMedCrossRefGoogle Scholar
  12. 12.
    Mahmood I, Yuan R. A comparative study of allometric scaling with plasma concentrations predicted by species-invariant time methods. Biopharm Drug Dispos. 1999;20:137–44.PubMedCrossRefGoogle Scholar
  13. 13.
    Tang H, Mayersohn M. A novel model for prediction of human drug clearance by allometric scaling. Drug Metab Dispos. 2005;33:1297–303.PubMedCrossRefGoogle Scholar
  14. 14.
    Mahmood I. Interspecies pharmacokinetic scaling: allometric principles and applications. Rockville: Pine House; 2005.Google Scholar
  15. 15.
    Obach RS, Baxter JG, Liston TE, Silber BM, Jones BC, Macintyre F, et al. The prediction of human pharmacokinetic parameters from preclinical and in vitro metabolism data. J Pharmacol Exp Ther. 1997;283:46–58.PubMedGoogle Scholar
  16. 16.
    Obach RS, Lombardo F, Waters NJ. Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds. Drug Metab Dispos. 2008;36:1385–405.PubMedCrossRefGoogle Scholar
  17. 17.
    Hosea N, Collard WT, Cole S, Maurer TS, Fang RX, Jones H, et al. Prediction of human pharmacokinetics from preclinical information: comparative accuracy of quantitative prediction approaches. J Clin Pharm. 2009;49:513.CrossRefGoogle Scholar
  18. 18.
    Oie S, Tozer TN. Effect of altered plasma protein binding on apparent volume of distribution. J Pharm Sci. 1979;68:1203–5.PubMedCrossRefGoogle Scholar
  19. 19.
    De Buck SS, Sinha VK, Fenu LA, Nijsen MJ, Mackie CE, Gilissen RAHJ. Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs. Drug Metab Dispos. 2007;35:1766–80.PubMedCrossRefGoogle Scholar
  20. 20.
    Jones HM, Parrott N, Jorga K, Lave T. A novel strategy for physiologically based predictions of human pharmacokinetics. Clin Pharmacokinet. 2006;45:511–42.PubMedCrossRefGoogle Scholar
  21. 21.
    Luttringer O, Theil F-P, Poulin P, Schmitt-Hoffmann AH, Guentert TW, Lave T. Physiologically based pharmacokinetic (PBPK) modeling of disposition of epiroprim in humans. J Pharm Sci. 2003;92:1990–2007.PubMedCrossRefGoogle Scholar
  22. 22.
    Parrott N, Jones H, Paquereau N, Lave T. Application of full physiological models for pharmaceutical drug candidate selection and extrapolation of pharmacokinetics to man. Basic Clin Pharmacol Toxicol. 2005;96:193–9.PubMedCrossRefGoogle Scholar
  23. 23.
    Fura A, Vyas V, Humphreys W, Chimalokonda A, Rodrigues D. Prediction of human oral pharmacokinetics using nonclinical data: examples involving four proprietary compounds. Biopharm Drug Dispos. 2008;29:455–68.PubMedCrossRefGoogle Scholar
  24. 24.
    Stoner CL, Cleton A, Johnson K, Oh D-M, Hallak H, Brodfuehrer J, et al. Integrated oral bioavailability projection using in vitro screening data as a selection tool in drug discovery. Int J Pharm. 2004;269:241–9.PubMedCrossRefGoogle Scholar
  25. 25.
    Sinha VK, De Buck SS, Fenu LA, Smit JW, Nijsen M, Gilissen AHJ, et al. Predicting oral clearance in humans: how close can we get with allometry? Clin Pharmacokinet. 2008;47:35–45.PubMedCrossRefGoogle Scholar
  26. 26.
    Wajima T, Yano Y, Fukumura K, Oguma T. Prediction of human pharmacokinetic profile in animal scale up based on normalizing time course profiles. J Pharm Sci. 2004;93:1890–900.PubMedCrossRefGoogle Scholar
  27. 27.
    Dannenfelser R-M, He H, Joshi Y, Bateman S, Serajuddin ATM. Development of clinical dosage forms for a poorly water soluble drug I: application of polyethylene glycol-polysorbate 80 solid dispersion carrier system. J Pharm Sci. 2004;93:1165–75.PubMedCrossRefGoogle Scholar
  28. 28.
    Kesisoglou F, Wu Y. Understanding the effect of API properties on bioavailability through absorption modeling. AAPS J. 2008;10:516–25.PubMedCrossRefGoogle Scholar
  29. 29.
    Tang H, Hussain A, Leal M, Mayersohn M, Fluhler E. Interspecies prediction of human drug clearance based on scaling data from one or two animal species. Drug Metab Dispos. 2007;35:1886–93.PubMedCrossRefGoogle Scholar
  30. 30.
    Tang H, Mayersohn M. A mathematical description of the functionality of correction factors used in allometry for predicting human drug clearance. Drug Metab Dispos. 2005;33:1294–6.PubMedCrossRefGoogle Scholar
  31. 31.
    Agoram B, Woltosz WS, Bolger MB. Predicting the impact of physiological and biochemical processes on oral drug bioavailability. Adv Drug Delivery Rev. 2001;50:S41–67.CrossRefGoogle Scholar
  32. 32.
    FDA. Estimating the safe starting dose in clinical trials for therapeutics in adult healthy volunteers (draft guidance), 2002.Google Scholar
  33. 33.
    Jamei M, Turner D, Yang J, Neuhoff S, Polak S, Rostami-Hodjegan A, et al. Population-based mechanistic prediction of oral drug absorption. AAPS J. 2009;11:225–37.PubMedCrossRefGoogle Scholar
  34. 34.
    Yu LX, Lipka E, Crison JR, Amidon GL. Transport approaches to the biopharmaceutical design of oral drug delivery systems: prediction of intestinal absorption. Adv Drug Deliv Rev. 1996;19:359–76.PubMedCrossRefGoogle Scholar
  35. 35.
    Gabrielsson J, Weiner D. Pharmacokinetic and pharmacodynamic data analysis: concepts and applications. 4th ed. Baco Raton: CRC; 2000.Google Scholar
  36. 36.
    Davies B, Morris T. Physiological parameters in laboratory animals and humans. Pharm Res. 1993;10:1093–5.PubMedCrossRefGoogle Scholar
  37. 37.
    Lukacova V, Parrott NJ, Lavè T, Fraczkiewicz G, Bolger MB, Woltosz WS. Role of fraction unbound in plasma in calculations of tissue: plasma partition coefficients. AAPS National Meeting, Atlanta, Georgia, 2008.Google Scholar
  38. 38.
    Rodgers T, Leahy D, Rowland M. Physiologically based pharmacokinetic modeling: predicting the tissue distribution of moderate-to-strong bases. [Erratum to document cited in CA143:221762]. J Pharm Sci. 2007;96:3151–2.CrossRefGoogle Scholar
  39. 39.
    Rodgers T, Rowland M. Physiologically-based pharmacokinetic modeling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions. J Pharm Sci. 2007;96:3153–4.CrossRefGoogle Scholar
  40. 40.
    Meibohm B, Derendorf H. Basic concepts of pharmacokinetic/pharmacodynamic (PK/PD) modelling. Int J Clin Pharmacol Ther. 1997;35:401–13.PubMedGoogle Scholar
  41. 41.
    Kwan KC. Oral bioavailability and first-pass effects. Drug Metab Dispos. 1997;25:1329–36.PubMedGoogle Scholar
  42. 42.
    Gao P, Morozowich W. Case studies: rational development of self-emulsifying formulations for improving the oral bioavailability of poorly soluble, lipophilic drugs. Drugs Pharm Sci. 2007;170:273–302.Google Scholar
  43. 43.
    Lave T, Coassolo P, Reigner B. Prediction of hepatic metabolic clearance based on interspecies allometric scaling techniques and in vitroin vivo correlations. Clin Pharmacokinet. 1999;36:211–31.PubMedCrossRefGoogle Scholar
  44. 44.
    Hellriegel ET, Bjornsson TD, Hauck WW. Interpatient variability in bioavailability is related to the extent of absorption: implications for bioavailability and bioequivalence studies. Clin Pharmacol Ther. 1996;60:601–7.PubMedCrossRefGoogle Scholar
  45. 45.
    Dressman J, Reppas C. Drug solubility: how to measure it, how to improve it. Adv Drug Deliv Rev. 2007;59:531–2.CrossRefGoogle Scholar
  46. 46.
    Jusko WJ, Ko HC. Physiologic indirect response models characterize diverse types of pharmacodynamic effects. Clin Pharmacol Ther. 1994;56:406–19.PubMedGoogle Scholar
  47. 47.
    Adolph EF. Quantitative relations in the physiological constitution of mammals. Science. 1949;109:579–85.PubMedCrossRefGoogle Scholar
  48. 48.
    Chiou WL, Barve A. Linear correlation of the fraction of oral dose absorbed of 64 drugs between humans and rats. Pharm Res. 1998;15:1792–5.PubMedCrossRefGoogle Scholar
  49. 49.
    Dedrick RL, Bischoff KB, Zaharko DS. Interspecies correlation of plasma concentration history of methotrexate (NSC-740). Cancer Chemother Rep. 1970;54:95–101.PubMedGoogle Scholar
  50. 50.
    Gibson CR, Bergman A, Lu P, Kesisoglou F, Denney WS, Mulrooney E. Prediction of phase I single-dose pharmacokinetics using recombinant cytochromes P450 and physiologically based modelling. Xenobiotica. 2009;1–12.
  51. 51.
    Ito K, Houston JB. Prediction of human drug clearance from in vitro and preclinical data using physiologically based and empirical approaches. Pharm Res. 2005;22:103–12.PubMedCrossRefGoogle Scholar
  52. 52.
    Poulin P, Schoenlein K, Theil F-P. Prediction of adipose tissue:plasma partition coefficients for structurally unrelated drugs. J Pharm Sci. 2001;90:436–47.PubMedCrossRefGoogle Scholar
  53. 53.
    Poulin P, Theil F-P. A priori prediction of tissue:plasma partition coefficients of drugs to facilitate the use of physiologically-based pharmacokinetic models in drug discovery. J Pharm Sci. 2000;89:16–35.PubMedCrossRefGoogle Scholar
  54. 54.
    Rodgers T, Leahy D, Rowland M. Physiologically based pharmacokinetic modeling: predicting the tissue distribution of moderate-to-strong bases. J Pharm Sci. 2005;94:1259–76.PubMedCrossRefGoogle Scholar
  55. 55.
    Jones HM, Parrott N, Ohlenbusch G, Lave T. Predicting pharmacokinetic food effects using biorelevant solubility media and physiologically based modelling. Clin Pharmacokinet. 2006;45:1213–26.PubMedCrossRefGoogle Scholar

Copyright information

© American Association of Pharmaceutical Scientists 2009

Authors and Affiliations

  • Tycho Heimbach
    • 1
    Email author
  • Suresh B. Lakshminarayana
    • 2
  • Wenyu Hu
    • 1
  • Handan He
    • 1
  1. 1.DMPK—Translational SciencesNovartis Institutes for BioMedical ResearchEast HanoverUSA
  2. 2.Novartis Institute for Tropical Diseases LtdSingaporeSingapore

Personalised recommendations