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PBPK Modelling of Intracellular Drug Delivery Through Active and Passive Transport Processes

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Intracellular Delivery III

Part of the book series: Fundamental Biomedical Technologies ((FBMT))

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Abstract

Physiologically based pharmacokinetic (PBPK) models describe adsorption, distribution, metabolisation and excretion (ADME) of drugs in the body of an organism based on a large amount of prior anatomical and physiological knowledge. In contrast to compartmental pharmacokinetic modeling which uses rather empirical model structures, PBPK models aim for a detailed mechanistic representation of physiological processes underlying drug pharmacokinetics within the body. That means that the relevant organs or tissues of an organism are explicitly represented in a PBPK model. Organs in PBPK models are usually divided in subcompartments such as plasma, interstitial space, intracellular space and red blood cells. Mass transfer between the different compartments which ultimately governs intracellular drug delivery is quantified either by so-called distribution models for the calculation of organ-plasma partition coefficients or by permeability-surface area products quantifying passive diffusion, respectively. Notably, both types of calculation methods are parameterized based upon the physicochemical properties of the investigated drug, respectively. These properties include amongst others lipophilicity and the molecular weight of the compound. Additional physiological information ranging from the whole body level (e.g. organ volumes, blood flow rates, tissue composition) to relative tissue-specific protein abundance is explicitly provided in the model. PBPK models are nowadays routinely used to analyze pharmacokinetics in drug development Due to the large amount of mechanistic information which is implicitly provided in the structural equations, PBPK models are in particular well-suited for both in-depth analyses of ADME processes underlying drug pharmacokinetics as well as for extrapolation to novel indications, patient populations or treatment designs. In this review we will present and discuss calculation methods used in PBPK model to describe and to quantify intracellular drug delivery.

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Abbreviations

ABCB11 :

ATP-binding cassette sub-family B member 11

ADME:

Adsorption distribution, metabolisation and excretion

ABCG2 :

ATP-binding cassette sub-family G member 2

P × SA:

Permeability surface area products

PBPK:

Physiologically-based pharmacokinetic modelling

PD:

Pharmacodynamic

PK:

Pharmacokinetic

Vmax:

catalytic activity [μmol/l/min]

kcat:

catalytic efficiency [1/min] and the total concentration of the catalyzing proteinE 0 E0 total concentration of the catalyzing protein [μmol/l] at the organism level

erel,j :

relative protein expression in in tissue j

SLC22A8 :

Solute carrier family 22 member 8e carrier family 22 member 8

OATP1B3 :

organic anion-transporting polypeptide 1B3

References

  • Agoram B, Woltosz WS, Bolger MB (2001) Predicting the impact of physiological and biochemical processes on oral drug bioavailability. Adv Drug Deliv Rev 50(Suppl 1):S41–S67

    Article  CAS  PubMed  Google Scholar 

  • Berezhkovskiy LM (2004) Volume of distribution at steady state for a linear pharmacokinetic system with peripheral elimination. J Pharm Sci 93(6):1628–1640. doi:10.1002/jps.20073

    Article  CAS  PubMed  Google Scholar 

  • Blakey GE, Nestorov IA, Arundel PA, Aarons LJ, Rowland M (1997) Quantitative structure-pharmacokinetics relationships: I. Development of a whole-body physiologically based model to characterize changes in pharmacokinetics across a homologous series of barbiturates in the rat. J Pharmacokinet Biopharm 25(3):277–312

    Article  CAS  PubMed  Google Scholar 

  • Cao Y, Jusko WJ (2012) Applications of minimal physiologically-based pharmacokinetic models. J Pharmacokinet Pharmacodyn 39(6):711–723. doi:10.1007/s10928-012-9280-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Cao Y, Balthasar JP, Jusko WJ (2013) Second-generation minimal physiologically-based pharmacokinetic model for monoclonal antibodies. J Pharmacokinet Pharmacodyn 40(5):597–607. doi:10.1007/s10928-013-9332-2

    Article  CAS  PubMed  Google Scholar 

  • Edginton AN, Willmann S (2008) Physiology-based simulations of a pathological condition: prediction of pharmacokinetics in patients with liver cirrhosis. Clin Pharmacokinet 47(11):743–752. doi:10.2165/00003088-200847110-00005

    Article  PubMed  Google Scholar 

  • Eissing T, Kuepfer L, Becker C et al (2011) A computational systems biology software platform for multiscale modeling and simulation: integrating whole-body physiology, disease biology, and molecular reaction networks. Front Physiol 2:4. doi:10.3389/fphys.2011.00004

    Article  PubMed  PubMed Central  Google Scholar 

  • Hoehme S, Brulport M, Bauer A et al (2010) Prediction and validation of cell alignment along microvessels as order principle to restore tissue architecture in liver regeneration. Proc Natl Acad Sci U S A 107(23):10371–10376. doi:10.1073/pnas.0909374107

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Jones H, Rowland-Yeo K (2013) Basic concepts in physiologically based pharmacokinetic modeling in drug discovery and development. CPT Pharmacometrics Syst Pharmacol 2, e63. doi:10.1038/psp.2013.41

    Article  PubMed  PubMed Central  Google Scholar 

  • Jones HM, Gardner IB, Watson KJ (2009) Modelling and PBPK simulation in drug discovery. AAPS J 11(1):155–166. doi:10.1208/s12248-009-9088-1

    Article  PubMed  PubMed Central  Google Scholar 

  • Kawai R, Lemaire M, Steimer JL, Bruelisauer A, Niederberger W, Rowland M (1994) Physiologically based pharmacokinetic study on a cyclosporin derivative, SDZ IMM 125. J Pharmacokinet Biopharm 22(5):327–365

    Article  CAS  PubMed  Google Scholar 

  • Lippert J, Brosch M, von Kampen O et al (2012) A mechanistic, model-based approach to safety assessment in clinical development. CPT Pharmacometrics Syst Pharmacol 1, e13. doi:10.1038/psp.2012.14

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Liu X, Smith BJ, Chen C et al (2005) Use of a physiologically based pharmacokinetic model to study the time to reach brain equilibrium: an experimental analysis of the role of blood–brain barrier permeability, plasma protein binding, and brain tissue binding. J Pharmacol Exp Ther 313(3):1254–1262. doi:10.1124/jpet.104.079319

    Article  CAS  PubMed  Google Scholar 

  • Loidl-Stahlhofen A, Hartmann T, Schottner M et al (2001) Multilamellar liposomes and solid-supported lipid membranes (TRANSIL): screening of lipid-water partitioning toward a high-throughput scale. Pharm Res 18(12):1782–1788

    Article  CAS  PubMed  Google Scholar 

  • Maharaj AR, Edginton AN (2014) Physiologically based pharmacokinetic modeling and simulation in pediatric drug development. CPT Pharmacometrics Syst Pharmacol 3, e150. doi:10.1038/psp.2014.45

    Article  CAS  PubMed  Google Scholar 

  • Meyer M, Schneckener S, Ludewig B, Kuepfer L, Lippert J (2012) Using expression data for quantification of active processes in physiologically based pharmacokinetic modeling. Drug Metab Dispos 40(5):892–901. doi:10.1124/dmd.111.043174

    Article  CAS  PubMed  Google Scholar 

  • Niederalt C, Wendl T, Kuepfer L et al (2012) Development of a physiologically based computational kidney model to describe the renal excretion of hydrophilic agents in rats. Front Physiol 3:494. doi:10.3389/fphys.2012.00494

    PubMed  Google Scholar 

  • Peters SA (2012) Physiologically-Based Pharmacokinetic (PBPK) modeling and simulations: principles, methods, and applications in the pharmaceutical industry. Wiley, Hoboken

    Book  Google Scholar 

  • Ploeger BA, van der Graaf PH, Danhof M (2009) Incorporating receptor theory in mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling. Drug Metab Pharmacokinet 24(1):3–15

    Article  CAS  PubMed  Google Scholar 

  • Poulin P, Theil FP (2000) 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 89(1):16–35. doi:10.1002/(SICI)1520-6017(200001)89:1<16::AID-JPS3>3.0.CO;2-E

    Article  CAS  PubMed  Google Scholar 

  • Poulin P, Schoenlein K, Theil FP (2001) Prediction of adipose tissue: plasma partition coefficients for structurally unrelated drugs. J Pharm Sci 90(4):436–447

    Article  CAS  PubMed  Google Scholar 

  • Rodgers T, Rowland M (2006) Physiologically based pharmacokinetic modelling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions. J Pharm Sci 95(6):1238–1257. doi:10.1002/jps.20502

    Article  CAS  PubMed  Google Scholar 

  • Rodgers T, Leahy D, Rowland M (2005) Physiologically based pharmacokinetic modeling 1: predicting the tissue distribution of moderate-to-strong bases. J Pharm Sci 94(6):1259–1276. doi:10.1002/jps.20322

    Article  CAS  PubMed  Google Scholar 

  • Sager JE, Yu J, Raguenau-Majlessi I, Isoherranen N (2015) Physiologically Based Pharmacokinetic (PBPK) modeling and simulation approaches: a systematic review of published models, applications and model verification. Drug Metab Dispos. doi:10.1124/dmd.115.065920

    PubMed  Google Scholar 

  • Schmitt W (2008) General approach for the calculation of tissue to plasma partition coefficients. Toxicol In Vitro 22(2):457–467. doi:10.1016/j.tiv.2007.09.010

    Article  CAS  PubMed  Google Scholar 

  • Tawhai MH, Bates JH (2011) Multi-scale lung modeling. J Appl Physiol (1985) 110(5):1466–72 doi:10.1152/japplphysiol.01289.2010

    Google Scholar 

  • Tawhai M, Clark A, Donovan G, Burrowes K (2011) Computational modeling of airway and pulmonary vascular structure and function: development of a “lung physiome”. Crit Rev Biomed Eng 39(4):319–336

    Article  PubMed  PubMed Central  Google Scholar 

  • Thelen K, Coboeken K, Willmann S, Burghaus R, Dressman JB, Lippert J (2011) Evolution of a detailed physiological model to simulate the gastrointestinal transit and absorption process in humans, part 1: oral solutions. J Pharm Sci 100(12):5324–5345. doi:10.1002/jps.22726

    Article  CAS  PubMed  Google Scholar 

  • Thelen K, Coboeken K, Willmann S, Dressman JB, Lippert J (2012) Evolution of a detailed physiological model to simulate the gastrointestinal transit and absorption process in humans, part II: extension to describe performance of solid dosage forms. J Pharm Sci 101(3):1267–1280. doi:10.1002/jps.22825

    Article  CAS  PubMed  Google Scholar 

  • Thiel C, Schneckener S, Krauss M et al (2015) A systematic evaluation of the use of physiologically based pharmacokinetic modeling for cross-species extrapolation. J Pharm Sci 104(1):191–206. doi:10.1002/jps.24214

    Article  CAS  PubMed  Google Scholar 

  • Thomas SR (2009) Kidney modeling and systems physiology. Wiley Interdiscip Rev Syst Biol Med 1(2):172–190. doi:10.1002/wsbm.14

    Article  CAS  PubMed  Google Scholar 

  • Willmann S, Lippert J, Sevestre M, Solodenko J, Fois F, Schmitt W (2003) PK-Sim®: a physiologically based pharmacokinetic ‘whole-body’ model. BioSilico 1(4):121–124

    Article  CAS  Google Scholar 

  • Willmann S, Lippert J, Schmitt W (2005) From physicochemistry to absorption and distribution: predictive mechanistic modelling and computational tools. Expert Opin Drug Metab Toxicol 1(1):159–168. doi:10.1517/17425255.1.1.159

    Article  CAS  PubMed  Google Scholar 

  • Zhao P, Rowland M, Huang SM (2012) Best practice in the use of physiologically based pharmacokinetic modeling and simulation to address clinical pharmacology regulatory questions. Clin Pharmacol Ther 92(1):17–20. doi:10.1038/clpt.2012.68

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Complex Systems Modelling, Bayer Technology Service GmbH, 51368, Leverkusen, Germany

    Lars Kuepfer, Christoph Niederalt, Thomas Wendl, Jan-Frederik Schlender, Michael Block, Thomas Eissing & Donato Teutonico

Authors
  1. Lars Kuepfer
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  2. Christoph Niederalt
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  3. Thomas Wendl
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  4. Jan-Frederik Schlender
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  5. Michael Block
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  6. Thomas Eissing
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  7. Donato Teutonico
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Correspondence to Lars Kuepfer .

Editor information

Editors and Affiliations

  1. Biomolecular and Chemical Engineering, Vanderbilt University Biomolecular and Chemical Engineering, Nashville, Tennessee, USA

    Aleš Prokop

  2. Pharmaceutical Sciences, Midwestern University Pharmaceutical Sciences, GLENDALE, Arizona, USA

    Volkmar Weissig

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Kuepfer, L. et al. (2016). PBPK Modelling of Intracellular Drug Delivery Through Active and Passive Transport Processes. In: Prokop, A., Weissig, V. (eds) Intracellular Delivery III. Fundamental Biomedical Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-43525-1_15

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