Skip to main content

Advertisement

SpringerLink
Log in

The Role of Permeability in Drug ADME/PK, Interactions and Toxicity—Presentation of a Permeability-Based Classification System (PCS) for Prediction of ADME/PK in Humans

  • Research Paper
  • Published:
Pharmaceutical Research Aims and scope Submit manuscript

Abstract

Purpose

The objective was to establish in vitro passive permeability (P e) vs in vivo fraction absorbed (f a)-relationships for each passage through the human intestine, liver, renal tubuli and brain, and develop a P e-based ADME/PK classification system (PCS).

Materials and Methods

P e- and intestinal f a-data were taken from an available data set. Hepatic f a was calculated based on extraction ratios of the unbound fraction of drugs (with support from animal in vivo uptake data). Renal f a (reabsorption) was estimated using renal pharmacokinetic data, and brain f a was predicted using animal in vitro and in vivo brain P e-data. Hepatic and intestinal f a-data were used to predict bile excretion potential.

Results

Relationships were established, including predicted curves for bile excretion potential and minimum oral bioavailability, and a 4-Class PCS was developed: I (very high P e; elimination mainly by metabolism); II (high P e) and III (intermediate P e and incomplete f a); IV (low P e and f a). The system enables assessment of potential drug–drug transport interactions, and drug and metabolite organ trapping.

Conclusions

The PCS and high quality P e-data (with and without active transport) are believed to be useful for predictions and understanding of ADME/PK, elimination routes, and potential interactions and organ trapping/toxicity in humans.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

Abbreviations

ADME/PK:

AbsorptionDistributionMetabolismExcretion/Pharmacokinetics

a.s.:

active secretion

BBB:

blood–brain barrier

BCS:

Biopharmaceutics Classification System

BDDCS:

Biopharmaceutics Drug Disposition Classification System

BUI:

brain uptake index

Cbl/Cpl :

blood-to-plasma concentration ratio

CL:

clearance

CLH :

hepatic CL

CLint :

intrinsic CL

CLint,secr :

renal tubular secretion CLint

CLR :

renal CL

E H :

hepatic extraction ratio

EHC:

enterohepatic circulation

E u,H :

E H for unbound drug

E max,bile :

maximum bile excretion potential

E u,R :

renal extraction ratio for unbound drug

E 1st-pass :

first-pass extraction ratio

F :

oral bioavailability

f a :

fraction absorbed

f a,B :

brain f a

f a,H :

hepatic f a

f a,I :

intestinal f a

f e :

fraction of intravenous dose excreted unchanged in urine

F min :

minimum F

fra :

fraction reabsorbed

f ra,bile :

fraction reabsorbed from the intestines following bile excretion

f ra,R :

fraction reabsorbed in the renal tubuli

f u :

unbound fraction

f u,bl :

f u in blood

f u,pl :

f u in plasma

GFR:

glomerular filtration rate

GI:

gastrointestinal

MDCK:

Madin–Darby canine kidney cells

MW:

molecular weight

P e :

permeability

PCS:

P e-based Classification System

P e S :

uptake CL (permeability–surface area product)

P e50 :

P e corresponding to a f a (or f ra) of 0.50

PSA:

polar surface area

Q :

blood flow rate

Q B :

brain Q

Q H :

hepatic Q

Q R :

renal Q

S :

surface area

S B :

brain S

TT:

transit time

\(t_{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-\nulldelimiterspace} 2}} ,\) :

half-life

λ :

slope factor

References

  1. U. Fagerholm, D. Nilsson, L. Knutson, and H. Lennernäs. Jejunal permeability in humans in vivo and rats in situ: investigation of molecular size selectivity and solvent drag. Acta Physiol. Scand. 165:315–324 (1999).

    Article  PubMed  CAS  Google Scholar 

  2. U. Fagerholm. In Characteristics of intestinal permeability in humans in vivo and rats in situ. Doctoral thesis, Uppsala University, Sweden (1997).

  3. U. Fagerholm, and H. Lennernäs. Experimental estimation of the effective unstirred water layer thickness in the human jejunum, and its importance in oral drug absorption. Eur. J. Pharm. Sci. 3:247–253 (1995).

    Article  CAS  Google Scholar 

  4. Y. Shibata, H. Takahashi, M. Chiba, and Y. Ishii. Prediction of hepatic clearance and availability by cryopreserved human hepatocytes: an application of serum incubation method. Drug Met. Disp. 30:892–896 (2002).

    Article  CAS  Google Scholar 

  5. C.-Y. Wu, and L. Benet. Predicting drug disposition via application of BCS: Transport/absorption/elimination interplay and development of a biopharmaceutics drug disposition classification system. Pharm. Res. 22:11–23 (2005).

    Article  PubMed  CAS  Google Scholar 

  6. U. Fagerholm. Evaluation and suggested improvements of the Biopharmaceutics Classification System (BCS). J. Pharm. Pharmacol. 59:751–757 (2007).

    Article  PubMed  CAS  Google Scholar 

  7. S. Willmann, W. Schmitt, J. Keldenich, J. Lippert, and J. B. Dressman. A physiological model for the estimation of the fraction dose absorbed in humans. J. Med. Chem. 47:4022–4031 (2004).

    Article  PubMed  CAS  Google Scholar 

  8. A. Goodman Gilman. In J. G. Hardman, L. E. Limbird, and A. Goodman Gilman (eds.) The pharmacological basis of therapeutics. McGraw-Hill (2001).

  9. R. S. Obach. Prediction of human clearance of twenty-nine drugs from hepatic microsomal intrinsic clearance data: an examination of in vitro half-life approach and nonspecific binding to microsomes. Drug Met. Disp. 27:1350–1359 (1999).

    CAS  Google Scholar 

  10. R. J. Riley, D. F. McGinnity, and R. P. Austin. A unified model for predicting human hepatic, metabolic clearance from in vitro intrinsic clearance data in hepatocytes and microsomes. Drug Met. Disp. 33:1304–1311 (2005).

    Article  CAS  Google Scholar 

  11. U. Fagerholm, M. Johansson, and H. Lennernäs. Comparison between permeability coefficients in rat and human jejunum. Pharm. Res. 13:1336–1342 (1996).

    Article  PubMed  CAS  Google Scholar 

  12. W. L. Chiou, and P. W. Beuhler. Comparison of oral absorption and bioavailability of drugs between monkey and human. Pharm. Res. 19:868–874 (2002).

    Article  PubMed  CAS  Google Scholar 

  13. J. Mordenti. Man vs beast: pharmacokinetic scaling in mammals. J. Pharm. Sci. 75:1028–1040 (1986).

    Article  PubMed  CAS  Google Scholar 

  14. S. L. Lindstedt, and P. J. Schaeffer. Use of allometry in predicting anatomical and physiological parameters of mammals. Lab. Animals. 36:1–19 (2002).

    Article  CAS  Google Scholar 

  15. R. W. Leggett, and L. R. Williams. A proposed blood circulation model for reference man. Health Physics. 69:187–201 (1995).

    Article  PubMed  CAS  Google Scholar 

  16. M. Rowland, and T. N. Tozer. In Clinical pharmacokinetics: concepts and applications. M. Rowland and T.N. Tozer (eds.). Williams and Wilkins (1995).

  17. S. Lundquist, M. Renftel, J. Brillault, L. Fenart, R. Cecchelli, and M.-P. Dehouck. Prediction of drug transport through the blood–brain barrier in vivo: a comparison between in vitro cell models. Pharm. Res. 19:976–981 (2002).

    Article  PubMed  CAS  Google Scholar 

  18. J. T. Goodwin, and D. E. Clark. In silico predictions of blood–brain barrier penetration: Considerations to “keep in mind”. J. Pharmacol. Exp. Ther. 315:477–483 (2005).

    Article  PubMed  CAS  Google Scholar 

  19. Y. Sawada, M. Hanano, Y. Sugiyama, H. Harashima, and T. Iga. Prediction of the volumes of distribution of basic drugs in humans based on data from animals. J. Pharmacokin. Biopharm. 12:587–596 (1984).

    Article  CAS  Google Scholar 

  20. Y. Sawada, M. Hanano, Y. Sugiyama, and T. Iga. Prediction of the disposition of nine weakly acidic and six weakly basic drugs in humans from pharmacokinetic parameters in rats. J. Pharmacokin. Biopharm. 13:477–492 (1985).

    Article  CAS  Google Scholar 

  21. P. Poulin, and F.-P. Theil. Prediction of pharmacokinetics prior to in vivo studies. 1. Mechanism-based prediction of volume of distribution. J. Pharm. Sci. 91:129–156 (2002).

    Article  PubMed  CAS  Google Scholar 

  22. U. Fagerholm, and M. A. Björnsson. Clinical pharmacokinetics of the cyclooxygenase-inhibiting nitric oxide donating donator (CINOD) AZD3582. J. Pharm. Pharmacol. 57:1539–1554 (2005).

    Article  PubMed  CAS  Google Scholar 

  23. J. B. Dressmann, G. L. Amidon, C. Reppas, and V. P. Shah. Dissolution testing as a prognostic tool for oral drug absorption: immediate release dosage forms. Pharm. Res. 15:11–22 (1998).

    Article  Google Scholar 

  24. D. Hörter, and J. B. Dressmann. Influence of physicochemical properties on dissolution of drugs in the gastrointestinal tract. Adv. Drug Del. Rev. 46:75–87 (2001).

    Article  Google Scholar 

  25. A. Lindahl, A.-L. Ungell, L. Knutson, and H. Lennernäs. Characterization of fluids from the stomach and proximal jejunum in men and women. Pharm. Res. 14:497–502 (1997).

    Article  PubMed  CAS  Google Scholar 

  26. B. Abrahamsson. In Biopharmaceutical aspects of extended release tablets based on the hydrophilic matrix principle. Doctoral thesis, Uppsala University, Sweden (1997).

  27. M. F. Paine, D. D. Shen, K. L. Kunze, J. D. Perkins, C. L. Marsh, J. P. McVicar, D. M. Barr, B. S. Gillies, and K. E. Thummel. First-pass metabolism of midazolam by the human small intestine. Clin. Pharmacol. Ther. 60:14–24 (1996).

    Article  PubMed  CAS  Google Scholar 

  28. T. Mizuma, K. Kawashima, S. Sakai, S. Sakaguchi, and M. Hayashi. Differentiation of organ availability by sequential and simultaneous analyses: intestinal conjugative metabolism impacts on intestinal availability in humans. J. Pharm. Sci. 94:571–575 (2005).

    Article  PubMed  CAS  Google Scholar 

  29. L. Borgström, L. Nyberg, S. Jonsson, C. Lindberg, and J. Paulson. Pharmacokinetic evaluation in man of terbutaline given as separate enantiomers and as the racemate. Br. J. Clin. Pharmacol. 27:49–56 (1989).

    PubMed  Google Scholar 

  30. I. De Waziers, P. H. Cugnenc, C. S. Yang, J. P. Leroux, and P. H. Beaune. Cytochrome P450 isoenzymes, epoxide hydrolase and glutathione transferases in rat and human hepatic and extrahepatic tissues. J. Pharmacol. Exp. Ther. 253:387–394 (1990).

    PubMed  Google Scholar 

  31. X. Cao, S. T. Gibbs, L. Fang, H. A. Miller, C. P. Landowski, H.-C.Shin, H. Lennernäs, Y. Zhong, G. L. Amidon, L. X. Yu, and D. Sun. Why is it challenging to predict intestinal drug absorption and oral bioavailability in human using rat model? Pharm. Res. 23:1675–1686 (2006).

    Article  PubMed  CAS  Google Scholar 

  32. E. G. van de Kerkhof, A.-L. B. Ungell, Å. K. Sjöberg, M. H. Jager, C. Hilgendorf, I. A. M. de Graaf, and G. M. M. Groothuis. Innovative methods to study human intestinal drug metabolism in vitro: precision-cut slices compared with Ussing chamber preparations. Drug Met. Disp. 34:1893–1902 (2006).

    Article  CAS  Google Scholar 

  33. U. Fagerholm, A. Lindahl, and H. Lennernäs. Regional intestinal permeability in rats of compounds with different physicochemical properties and transport mechanisms. J. Pharm. Pharmacol. 49:687–690 (1997).

    PubMed  CAS  Google Scholar 

  34. S. S. Davis. Evaluation of the gastrointestinal transit of pharmaceutical dosage forms using the technique of gammascintigraphy. S.T.P Pharma. 2:1015–1022 (1986).

    Google Scholar 

  35. G. Alpini, R. A. Garrick, M. J. T. Jones, R. Nunes, and N. Tavoloni. Water and nonelectrolyte permeability of isolated rat hepatocytes. Am. J. Physiol. 251:C872–882 (1986).

    PubMed  CAS  Google Scholar 

  36. A. Blouin. Morphometry of liver sinusoidal cells. In E. Wisse, Knook, D. L. (eds.) Kupffer Cells and Other Liver Sinusoidal Cells (1977).

  37. C. A. Goresky, K. S. Pang, A. J. Schwab, F. Barker III, W. F. Cherry, and G. G. Bach. Uptake of a protein-bound polar compound, acetaminophen sulphate, by perfused rat liver. Hepatol. 16:173–190 (1992).

    Article  CAS  Google Scholar 

  38. A. J. Schwab, F. Barker III, C. A. Goresky, and K. S. Pang. Transfer of enalaprilat across rat liver cell membranes is barrier limited. Am. J. Physiol. 258:G461–475 (1990).

    PubMed  CAS  Google Scholar 

  39. G. D. Mellick, and M. S. Roberts. The disposition of aspirin and salicylic acid in the isolated perfused rat liver: The effect of normal and retrograde flow on availability and mean transit time. J. Pharmacy Pharmacol. 48:738–743 (1996).

    CAS  Google Scholar 

  40. H. Boxenbaum. Interspecies variation in liver weight, hepatic blood flow, and antipyrine intrinsic clearance: Extrapolation of data to benzodiazepines and phenytoin. J. Pharmacokin. Biopharm. 8:165–176 (1980).

    Article  CAS  Google Scholar 

  41. E. R. Weibel, W. Staubli, H. R. Gnagi, and F. A. Hess. Correlated morphometric and biochemical studies on the liver cell. Morphometric model, and normal morphometric data for rat liver. J. Cell Biol. 42:68–91 (1969).

    Article  PubMed  CAS  Google Scholar 

  42. P. J. Meier, E. S. Sztul, A. Reuben, and J. L. Boyer. Structural and functional polarity of canalicular and basolateral plasma membrane vesicles isolated in high yield from rat liver. J. Cell Biol. 98:991–1000 (1984).

    Article  PubMed  CAS  Google Scholar 

  43. TP-search transport database (http://www.TP-search.jp/). Y. Sugiyama, H. Kusuhara, K. Maeda and Y. Nozaki (accessed 04/11/07).

  44. M. S. Roberts, B. M. Magnusson, F. J. Burczynski, and M. Weiss. Enterohepatic circulation. Physiological, pharmacokinetic and clinical implications. Clin. Pharmacokin. 41:751–790 (2002).

    Article  CAS  Google Scholar 

  45. D. Raušl, N. Fotaki, R. Zanoški, M. Vertzoni, B. Cetina-Èimek, M. Z. I. Khan, and C. Reppas. Intestinal permeability and excretion into bile control the arrival of amlodipine into the systemic circulation after oral administration. J. Pharm. Pharmacol. 58:827–836 (2006).

    Article  PubMed  CAS  Google Scholar 

  46. Y. Shitara, H. Sato, and Y. Sugiyama. Evaluation of drug–drug interaction in the hepatobiliary and renal transport of drugs. Annu. Rev. Pharmacol.Toxicol. 45:689–723 (2005).

    Article  PubMed  CAS  Google Scholar 

  47. R. Masereeuw, and F. G. M. Russel. Mechanisms and clinical implications of renal drug excretion. Drug Met. Rev. 33:299–351 (2001).

    Article  CAS  Google Scholar 

  48. J. D. Irvine, L. Takahashi, K. Lackhart, J. Cheong, J. W. Tolan, H. E. Selick, and J. R. Grove. MDCK (Madin–Darby canine kidney) cells: a tool for membrane permeability screening. J. Pharm. Sci. 88:29–33 (1999).

    Article  Google Scholar 

  49. M. Rowland, and T. N. Tozer. In Clinical pharmacokinetics: concepts and applications. Lea and Febiger (1989).

  50. H. van de Waterbeemd, G. Camenisch, G. Folkers, J. R. Chretien, and O. A. Raevsky. Estimation of blood–brain barrier crossing of drugs using molecular size and shape, and h-bonding descriptors. J. Drug Targ. 6:151–165 (1998).

    Article  Google Scholar 

  51. J. Kelder, P. D. J. Grootenhuis, D. M. Bayada, L. P. C. Delbressine, and J.-P. Ploemen. Polar molecular surface as a dominating determinant for oral absorption and brain penetration of drugs. Pharm. Res. 16:1514–1519 (1999).

    Article  PubMed  CAS  Google Scholar 

  52. W. M. Pardridge. Blood–brain barrier drug targeting: the future of brain drug development. Molec. Intervent. 3:90–105 (2003).

    Article  CAS  Google Scholar 

  53. W. P. Pardridge. The blood–brain barrier: bottleneck in brain drug development. NeuroRx. 2:3–14 (2005).

    Article  PubMed  Google Scholar 

  54. D. J. Begley. The blood–brain barrier: principles for targeting peptides and drugs to the central nervous system. J. Pharm. Pharmacol. 48:136–146 (1996).

    PubMed  CAS  Google Scholar 

  55. T. J. Abbruscato, S. A. Thomas, V. J. Hruby, and T. P. Davis. Blood–brain barrier permeability and bioavailability of a highly potent and μ-selective opioid receptor antagonist, CTAP: comparison with morphine. J. Pharmacol. Exp. Ther. 280:402–409 (1997).

    PubMed  CAS  Google Scholar 

  56. J. Kawakami, K. Yamamoto, Y. Sawada, and T. Iga. Prediction of brain delivery of ofloxacin, a new quinolone, in the human from animal data. J. Pharmacokin. Biopharm. 22:207–227 (1994).

    Article  CAS  Google Scholar 

  57. S. Syvänen, G. Blomquist, M. Sprycha, A. U. Höglund, M. Roman, O. Eriksson, M. Hammarlund-Udenaes, B. Långström, and M. Bergström. Duration and degree of cyclosporin induced P-glycoprotein inhibition in the rat blood–brain barrier can be studied with PET. NeuroImage. 32:1134–1141 (2006).

    Article  PubMed  Google Scholar 

  58. J. van Asperen, U. Mayer, O. van Tellingen, and J. H. Beijnen. The functional role of P-glycoprotein in the blood–brain barrier. J. Pharm. Sci. 86:881–884 (1997).

    Article  PubMed  Google Scholar 

  59. D. E. Clark. Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 2. Prediction of blood–brain barrier penetration. J. Pharm. Sci. 88:815–821 (1999).

    Article  PubMed  CAS  Google Scholar 

  60. I. Tamai, and A. Tsuji. Transporter-mediated permeation of drugs across the blood–brain barrier. J. Pharm. Sci. 11:1371–1388 (2000).

    Article  Google Scholar 

  61. V. Berezowski, C. Landry, S. Lundquist, L. Dehouck, R. Cecchelli, M. P. Dehouck, and L. Fenart. Transport of drug cocktails through an in vitro blood–brain barrier: is it a good strategy for increasing the throughput of the discovery pipeline? Pharm. Res. 21:756–760 (2004).

    Article  PubMed  CAS  Google Scholar 

  62. S. A. Thomas, T. J. Abbruscato, V. S. Hau, T. J. Gillespie, J. Zsigo, V. J. Hruby, and T. P. Davis. Structure-activity relationships of a series of [d-Ala2]deltorphin I and II analogues; in vitro blood–brain barrier permeability and stability. J. Pharmacol. Exp. Ther. 281:817–825 (1997).

    PubMed  CAS  Google Scholar 

  63. A. Kakee, T. Terasaki, and Y. Sugiyama. Brain efflux index as a novel method of analyzing efflux transport at the blood–brain barrier. J. Pharmacol. Exp. Ther. 277:1550–1559 (1996).

    PubMed  CAS  Google Scholar 

  64. M.-P. Dehouck, R. Cecchelli, A. R. Green, M. Renftel, and S. Lundquist. In vitro blood–brain barrier permeability and cerebral endothelial cell uptake if the neuroprotective nitrone compound NXY-059 in normoxic, hypoxic and ischemic conditions. Brain Res. 955:229–235 (2002).

    Article  PubMed  CAS  Google Scholar 

  65. H. Fischer, R. Gottschlich, and A. Seelig. Blood–brain barrier permeation: molecular parameters governing passive diffusion. J. Membr. Biol. 165:201–211 (1998).

    Article  PubMed  CAS  Google Scholar 

  66. J. Karlsson, and P. Artursson. A new diffusion chamber system for the determination of drug permeability coefficients across the human intestinal epithelium that are independent on the unstirred water layer. Biochim. Biophys. Acta. 1111:204–210 (1992).

    Article  PubMed  CAS  Google Scholar 

  67. Y. Su, and P. J. Sinko. Drug delivery across the blood–brain barrier: why is it difficult? how to measure and improve it? Expert Opin. Drug Del. 3:419–435 (2006).

    Article  CAS  Google Scholar 

  68. E. Boström, U. S. H. Simonsson, and M. Hammarlund-Udenaes. In vivo blood–brain barrier transport of oxycodone in the rat: Indications for active influx and implications for pharmacokinetics/pharmacodynamics. Drug Met. Disp. 34:1624–1631 (2006).

    Article  CAS  Google Scholar 

  69. H. Lennernäs. Human jejunal effective permeability and its correlation with preclinical drug absorption models. J. Pharm. Pharmacol. 49:627–638 (1997).

    PubMed  Google Scholar 

  70. D. K. Hansen, D. O. Scott, K. W. Otis, and S. M. Lunte. Comparison of in vitro BBMEC permeability and in vivo CNS uptake by microdialysis sampling. J. Pharmaceut. Biomed. Anal. 27:945–958 (2002).

    Article  CAS  Google Scholar 

  71. L. S. Schanker, P. A. Nafpliotis, and J. M. Johnson. Passage of organic bases into human red cells. J. Pharmacol. Ther. 133:325–331 (1961).

    CAS  Google Scholar 

  72. P. Naccache, and R. I. Sha’afi. Patterns of nonelectrolyte permeability in human red blood cell membrane. J. Gen. Physiol. 62:714–736 (1973).

    Article  PubMed  CAS  Google Scholar 

  73. R. Sandström, A. Karlsson, L. Knutson, and H. Lennernäs. Jejunal absorption and metabolism of R/S-verapamil in humans. Pharm. Res. 15:856–862 (1998).

    Article  PubMed  Google Scholar 

  74. A. Tsuji, and I. Tamai. Blood–brain barrier function of P-glycoprotein. Adv. Drug Del. Rev. 25:287–298 (1997).

    Article  CAS  Google Scholar 

  75. A. J. M. Sadeque, C. Wandel, H., He, S. Shah, and A. J. J. Wood. Increased drug delivery to the brain by P-glycoprotein inhibition. Clin. Pharmacol. Ther. 68:231–237 (2000).

    Article  PubMed  CAS  Google Scholar 

  76. S. Hirata, S. Izumi, S. T. Furukubo, M. Ota, M. Fujita, T. Yamakawa, I. Hasegawa, H. Ohtani, and Y. Sawada. Int. J. Clin. Pharmacol. Ther. 43:30–36 (2005).

    PubMed  CAS  Google Scholar 

  77. J. Rengelshausen, C. Goggelmann, J. Burhenne, K. D. Reidel, J. Ludwig, J. Weiss, G. Mikus, I. Walter-Sack, and W. E. Haefeli. Contribution of increased oral bioavailability and reduced nonglomerular renal clearance of digoxin to the digoxin–clarithromycin interaction. Br. J. Clin. Pharmacol. 56:32–38 (2003).

    Article  PubMed  CAS  Google Scholar 

  78. R. H. Ho, and R. B. Kim. Transporters and drug therapy: implications for drug disposition and disease. Clin. Pharmacol. Ther. 78:260–277 (2005).

    Article  PubMed  CAS  Google Scholar 

  79. FASS web-site http://www.fass.se.

  80. G. A. Siebert, D. Y. Hung, P. Chang, and M. S. Roberts. Ion-trapping, microsomal binding, and unbound drug distribution in the hepatic retention of basic drugs. J. Pharmacol. Exp. Ther. 308:228–235 (2004).

    Article  PubMed  CAS  Google Scholar 

  81. U. Fagerholm, M. Johansson, and H. Lennern. Comparison between permeability coefficients in rat and human jejunum. Pharm. Res. 13:1336–1342 (1996).

    Article  PubMed  CAS  Google Scholar 

  82. U. Fagerholm. Prediction of human pharmacokinetics-Gastrointestinal absorption. J. Pharm. Pharmacol. 59:905–916 (2007).

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

The author greatly acknowledges Professor Per Artursson at Uppsala University, Sweden, Associate Professor Anna-Lena Ungell at AstraZeneca R&D Mölndal, Sweden, and Doctors Lovisa Afzelius and Janet Hoogstraate at AstraZeneca R&D Södertälje, Sweden, for reviewing the manuscript, for valuable comments and advise, and for support.

Author information

Authors and Affiliations

  1. Clinical Pharmacology, AstraZeneca R&D Södertälje, S-151 85, Södertälje, Sweden

    Urban Fagerholm

Authors
  1. Urban Fagerholm
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Urban Fagerholm.

Additional information

This paper includes personal opinions of the author, which do not necessarily represent the views or policies of AstraZeneca.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Fagerholm, U. The Role of Permeability in Drug ADME/PK, Interactions and Toxicity—Presentation of a Permeability-Based Classification System (PCS) for Prediction of ADME/PK in Humans. Pharm Res 25, 625–638 (2008). https://doi.org/10.1007/s11095-007-9397-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11095-007-9397-y

Key words

Search

Navigation