Skip to main content
SpringerLink
Log in

Physiologically Based Pharmacokinetic (PBPK) Modeling Application on Food Effect Assessment

  • Chapter
  • First Online:
Advances in Pharmacokinetics and Pharmacodynamics

Part of the book series: AAPS Introductions in the Pharmaceutical Sciences ((AAPSINSTR,volume 9))

  • 436 Accesses

Abstract

Food–drug interaction is one of the major factors that impact clinical pharmacokinetics in drug development. Unfortunately, the available in vitro and preclinical models do not appropriately predict food effects due to the complex mechanisms. It is recognized by the FDA that a food effect study should be conducted in the early clinical stage to inform the dosing paradigm and establish food effects risks in patients. Physiologically based biopharmaceutics modeling (PBBM) is a powerful tool to predict clinical PK by incorporating physiology-related and drug product-related factors in the mechanistic absorption model. PBBM has been utilized in various applications in drug development, such as biopharmaceutics risk assessment, bioequivalence safe space setup, and pH-mediated drug–drug interaction evaluation. The application of utilizing PBBM for food effect assessment has been tested and validated through many published case studies. In this chapter, an overview of food effects including current assessment practice, various food–drug interaction mechanisms, and clinical considerations is included. Thorough instruction on using PBBM to evaluate food effects is provided, followed by two detailed case studies. Though PBBM has shown potential in food effect prediction, it is still an evolving area, and current gaps and future directions are discussed.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Wu F et al (2021) Biopharmaceutics applications of physiologically based pharmacokinetic absorption modeling and simulation in regulatory submissions to the US food and drug administration for new drugs. AAPS J 23(2):1–14

    Article  Google Scholar 

  2. K, Y., et al., Applications of PBPK/PBBM modeling in generic product development: An industry perspective. J Drug Deliv Sci Technol, 2022. 69: p. 103152.

    Google Scholar 

  3. U.S. FDA (2020) The use of physiologically based pharmacokinetic analyses—biopharmaceutics applications for oral drug product development, manufacturing changes, and controls. https://www.fda.gov/media/142500/download

  4. Huang W, Lee SL, Yu LX (2009) Mechanistic approaches to predicting oral drug absorption. AAPS J 11(2):217–224

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. O’Shea JP et al (2019) Food for thought: formulating away the food effect—a PEARRL review. J Pharm Pharmacol 71(4):510–535

    Article  PubMed  Google Scholar 

  6. U.S. FDA (2020) Assessing the effects of food on drugs in INDs and NDAs. https://www.fda.gov/media/121313/download

  7. Goncalves P et al (2012) Inhibition of butyrate uptake by the primary bile salt chenodeoxycholic acid in intestinal epithelial cells. J Cell Biochem 113(9):2937–2947

    Article  CAS  PubMed  Google Scholar 

  8. Xiao J et al (2020) Biliary excretion–mediated food effects and prediction. AAPS J 22(6):124

    Article  CAS  PubMed  Google Scholar 

  9. Mwebaza N et al (2013) Comparable lumefantrine oral bioavailability when co-administered with oil-fortified maize porridge or milk in healthy volunteers. Basic Clin Pharmacol Toxicol 113(1):66–72

    Article  CAS  PubMed  Google Scholar 

  10. Veerman GDM et al (2021) Influence of cow’s milk and esomeprazole on the absorption of erlotinib: a randomized, crossover pharmacokinetic study in lung cancer patients. Clin Pharmacokinet 60(1):69–77

    Article  CAS  PubMed  Google Scholar 

  11. Gleeson JP et al (2018) Sodium caprate enables the blood pressure-lowering effect of Ile-pro-pro and Leu-Lys-pro in spontaneously hypertensive rats by indirectly overcoming PepT1 inhibition. Eur J Pharm Biopharm 128:179–187

    Article  CAS  PubMed  Google Scholar 

  12. Morimoto K et al (2011) Effect of milk on the pharmacokinetics of oseltamivir in healthy volunteers. J Pharm Sci 100(9):3854–3861

    Article  CAS  PubMed  Google Scholar 

  13. Singh BN (1999) Effects of food on clinical pharmacokinetics. Clin Pharmacokinet 37(3):213–255

    Article  CAS  PubMed  Google Scholar 

  14. Neuvonen PJ (1976) Interactions with the absorption of Tetracyclines. Drugs 11(1):45–54

    Article  CAS  PubMed  Google Scholar 

  15. Stebler T, Guentert TW (1990) Binding of drugs in milk: the role of casein in milk protein binding. Pharm Res 7(6):633–637

    Article  CAS  PubMed  Google Scholar 

  16. Bailey DG et al (1991) Interaction of citrus juices with felodipine and nifedipine. Lancet 337(8736):268–269

    Article  CAS  PubMed  Google Scholar 

  17. Bailey DG et al (1989) Ethanol enhances the hemodynamic effects of felodipine. Clin Invest Med 12(6):357–362

    CAS  PubMed  Google Scholar 

  18. Lown KS et al (1997) Grapefruit juice increases felodipine oral availability in humans by decreasing intestinal CYP3A protein expression. J Clin Invest 99(10):2545–2553

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. de Castro WV et al (2007) Grapefruit juice—drug interactions: grapefruit juice and its components inhibit P-glycoprotein (ABCB1) mediated transport of talinolol in Caco-2 cells. J Pharm Sci 96(10):2808–2817

    Article  PubMed  Google Scholar 

  20. Fagerberg JH, Sjögren E, Bergström CAS (2015) Concomitant intake of alcohol may increase the absorption of poorly soluble drugs. Eur J Pharm Sci 67:12–20

    Article  CAS  PubMed  Google Scholar 

  21. Keemink J et al (2019) Does the intake of ethanol affect oral absorption of poorly soluble drugs? J Pharm Sci 108(5):1765–1771

    Article  CAS  PubMed  Google Scholar 

  22. Laisi U et al (1979) Pharmacokinetic and pharmacodynamic interactions of diazepam with different alcoholic beverages. Eur J Clin Pharmacol 16(4):263–270

    Article  CAS  Google Scholar 

  23. Parlesak A et al (2000) Increased intestinal permeability to macromolecules and endotoxemia in patients with chronic alcohol abuse in different stages of alcohol-induced liver disease∗*dedicated to Dr. Dr. Herbert Falk, director of the Falk Foundation, on the occasion of his 75th birthday. J Hepatol 32(5):742–747

    Article  CAS  PubMed  Google Scholar 

  24. Leclercq S et al (2012) Role of intestinal permeability and inflammation in the biological and behavioral control of alcohol-dependent subjects. Brain Behav Immun 26(6):911–918

    Article  CAS  PubMed  Google Scholar 

  25. Abdel-Rahman SM et al (2007) Considerations in the rational design and conduct of phase I/II pediatric clinical trials: avoiding the problems and pitfalls. Clin Pharmacol Ther 81(4):483–494

    Article  CAS  PubMed  Google Scholar 

  26. Lee HS et al (2020) Sprinkle formulations—a review of commercially available products. Asian J Pharm Sci 15(3):292–310

    Article  PubMed  Google Scholar 

  27. Grimm M et al (2018) Interindividual and intraindividual variability of fasted state gastric fluid volume and gastric emptying of water. Eur J Pharm Biopharm 127:309–317

    Article  PubMed  Google Scholar 

  28. Pentafragka C et al (2020) Disposition of two highly permeable drugs in the upper gastrointestinal lumen of healthy adults after a standard high-calorie, high-fat meal. Eur J Pharm Sci 149:105351

    Article  CAS  PubMed  Google Scholar 

  29. Davis SS, Hardy JG, Fara JW (1986) Transit of pharmaceutical dosage forms through the small intestine. Gut 27(8):886–892

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Mudie DM et al (2014) Quantification of gastrointestinal liquid volumes and distribution following a 240 mL dose of water in the fasted state. Mol Pharm 11(9):3039–3047

    Article  CAS  PubMed  Google Scholar 

  31. Koziolek M et al (2014) Intragastric volume changes after intake of a high-caloric, high-fat standard breakfast in healthy human subjects investigated by MRI. Mol Pharm 11(5):1632–1639

    Article  CAS  PubMed  Google Scholar 

  32. Grimm M et al (2018) Gastric emptying and small bowel water content after administration of grapefruit juice compared to water and Isocaloric solutions of glucose and fructose: a four-way crossover MRI pilot study in healthy subjects. Mol Pharm 15(2):548–559

    Article  CAS  PubMed  Google Scholar 

  33. SCHILLER C et al (2005) Intestinal fluid volumes and transit of dosage forms as assessed by magnetic resonance imaging. Aliment Pharmacol Ther 22(10):971–979

    Article  CAS  PubMed  Google Scholar 

  34. Fordtran JS, Locklear TW (1966) Ionic constituents and osmolality of gastric and small-intestinal fluids after eating. Am J Dig Dis 11(7):503–521

    Article  CAS  PubMed  Google Scholar 

  35. Pentafragka C et al (2018) The impact of food intake on the luminal environment and performance of oral drug products with a view to in vitro and in silico simulations: a PEARRL review. J Pharm Pharmacol 71(4):557–580

    Article  PubMed  Google Scholar 

  36. Baxevanis F, Kuiper J, Fotaki N (2016) Fed-state gastric media and drug analysis techniques: current status and points to consider. Eur J Pharm Biopharm 107:234–248

    Article  CAS  PubMed  Google Scholar 

  37. Vertzoni M et al (2012) Luminal lipid phases after administration of a triglyceride solution of danazol in the fed state and their contribution to the flux of danazol across Caco-2 cell monolayers. Mol Pharm 9(5):1189–1198

    Article  CAS  PubMed  Google Scholar 

  38. Kalantzi L et al (2006) Characterization of the human upper gastrointestinal contents under conditions simulating bioavailability/bioequivalence studies. Pharm Res 23(1):165–176

    Article  CAS  PubMed  Google Scholar 

  39. Klein S (2010) The use of biorelevant dissolution media to forecast the in vivo performance of a drug. AAPS J 12(3):397–406

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Moreno MPDLC et al (2010) Characterization of fasted-state human intestinal fluids collected from duodenum and jejunum. J Pharm Pharmacol 58(8):1079–1089

    Article  Google Scholar 

  41. Persson EM et al (2005) The effects of food on the dissolution of poorly soluble drugs in human and in model small intestinal fluids. Pharm Res 22(12):2141–2151

    Article  CAS  PubMed  Google Scholar 

  42. Dahlgren D et al (2021) Fasted and fed state human duodenal fluids: characterization, drug solubility, and comparison to simulated fluids and with human bioavailability. Eur J Pharm Biopharm 163:240–251

    Article  CAS  PubMed  Google Scholar 

  43. Medwid S et al (2021) Organic anion transporting polypeptide 2B1 (OATP2B1) genetic variants: in vitro functional characterization and association with circulating concentrations of endogenous substrates. Front Pharmacol 12

    Google Scholar 

  44. Tikkanen A et al (2020) Food additives as inhibitors of intestinal drug transporter OATP2B1. Mol Pharm 17(10):3748–3758

    Article  CAS  PubMed  Google Scholar 

  45. Ma K, Hu Y, Smith DE (2012) Influence of fed-fasted state on intestinal PEPT1 expression and in vivo pharmacokinetics of glycylsarcosine in wild-type and Pept1 knockout mice. Pharm Res 29(2):535–545

    Article  CAS  PubMed  Google Scholar 

  46. Deferme S, Augustijns P (2003) The effect of food components on the absorption of P-gp substrates: a review. J Pharm Pharmacol 55(2):153–162

    Article  CAS  PubMed  Google Scholar 

  47. Abuznait AH et al (2011) Induction of expression and functional activity of P-glycoprotein efflux transporter by bioactive plant natural products. Food Chem Toxicol 49(11):2765–2772

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Yan J-H (2017) Food effect on oral bioavailability: old and new questions. Clin Pharmacol Drug Dev 6(4):323–330

    Article  CAS  PubMed  Google Scholar 

  49. Olanoff LS et al (1986) Food effects on propranolol systemic and oral clearance: support for a blood flow hypothesis. Clin Pharmacol Ther 40(4):408–414

    Article  CAS  PubMed  Google Scholar 

  50. Gu C-H et al (2007) Predicting effect of food on extent of drug absorption based on physicochemical properties. Pharm Res 24(6):1118–1130

    Article  CAS  PubMed  Google Scholar 

  51. Fleisher D et al (1999) Drug, meal and formulation interactions influencing drug absorption after oral administration. Clin Pharmacokinet 36(3):233–254

    Article  CAS  PubMed  Google Scholar 

  52. Wu C-Y, Benet LZ (2005) Predicting drug disposition via application of BCS: transport/absorption/elimination interplay and development of a biopharmaceutics drug disposition classification system. Pharm Res 22(1):11–23

    Article  CAS  PubMed  Google Scholar 

  53. Zhang T, Wells E (2020) A review of current methods for food effect prediction during drug development. Curr Pharmacol Rep 6(5):267–279

    Article  Google Scholar 

  54. Lentz KA (2008) Current methods for predicting human food effect. AAPS J 10(2):282–288

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Henze LJ et al (2021) Combining species specific in vitro & in silico models to predict in vivo food effect in a preclinical stage—case study of Venetoclax. Eur J Pharm Sci 162:105840

    Article  CAS  PubMed  Google Scholar 

  56. Mithani SD et al (1996) Estimation of the increase in solubility of drugs as a function of bile salt concentration. Pharm Res 13(1):163–167

    Article  CAS  PubMed  Google Scholar 

  57. Li M et al (2021) Understanding in vivo dissolution of immediate release (IR) solid ORAL drug products containing weak acid BCS class 2 (BCS class 2a) drugs. AAPS J 23(6):1–13

    Article  Google Scholar 

  58. Pepin XJH et al (2016) Justification of drug product dissolution rate and drug substance particle size specifications based on absorption PBPK modeling for lesinurad immediate release tablets. Mol Pharm 13(9):3256–3269

    Article  CAS  PubMed  Google Scholar 

  59. Lin W et al (2022) Applications, challenges, and outlook for PBPK modeling and simulation: a regulatory, vol 39. Ind Acad Perspect, Pharm Res, p 1701

    Google Scholar 

  60. Li M et al (2018) Predictive performance of physiologically based pharmacokinetic models for the effect of food on oral drug absorption: current status. CPT Pharmacometrics Syst Pharmacol 7(2):82–89

    Article  CAS  PubMed  Google Scholar 

  61. Kesisoglou F (2020) Can PBPK modeling streamline food effect assessments? J Clin Pharmacol 60(S1):S98–S104

    Article  CAS  PubMed  Google Scholar 

  62. U.S. FDA (1997) Extended release oral dosage forms: development, evaluation, and application of in vitro/in vivo correlations

    Google Scholar 

  63. Dong Z et al (2020) Application of physiologically-based pharmacokinetic modeling to predict gastric pH-dependent drug–drug interactions for weak base drugs. CPT Pharmacometrics Syst Pharmacol 9(8):456–465

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Gajewska M et al (2020) Physiologically based pharmacokinetic modeling of oral absorption, pH, and food effect in healthy volunteers to drive Alpelisib formulation selection. AAPS J 22(6):134

    Article  CAS  PubMed  Google Scholar 

  65. Pharmaceuticals N (2015) Study assessing the efficacy and safety of alpelisib plus fulvestrant in men and postmenopausal women with advanced breast cancer which progressed on or after aromatase inhibitor treatment (SOLAR-1). https://clinicaltrials.gov/ct2/show/NCT02437318

  66. Boxenbaum H, Ronfeld R (1983) Interspecies pharmacokinetic scaling and the dedrick plots. Am J Phys Regul Integr Comp Phys 245(6):R768–R775

    CAS  Google Scholar 

  67. Vuppugalla R et al (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):4111–4126

    Article  CAS  PubMed  Google Scholar 

  68. Sutton SC, Nause R, Gandelman K (2017) The impact of gastric pH, volume, and emptying on the food effect of ziprasidone oral absorption. AAPS J 19(4):1084–1090

    Article  CAS  PubMed  Google Scholar 

  69. Kakuda TN, Falcon RW (2006) Effect of food and ranitidine on saquinavir pharmacokinetics and gastric pH in healthy volunteers. Pharmacotherapy 26(8):1060–1068

    Article  CAS  PubMed  Google Scholar 

  70. Wagner C et al (2021) Use of physiologically based pharmacokinetic modeling for predicting drug–food interactions: recommendations for improving predictive performance of low confidence food effect models. AAPS J 23(4):85

    Article  CAS  PubMed  Google Scholar 

  71. Tadken T et al (2016) Trospium chloride is absorbed from two intestinal “absorption windows” with different permeability in healthy subjects. Int J Pharm 515(1):367–373

    Article  CAS  PubMed  Google Scholar 

  72. U.S. FDA (2003) Clinical pharmacology and biopharmaceutics review—trospium chloride. https://www.accessdata.fda.gov/drugsatfda_docs/nda/2004/21-595_Sanctura_BioPharmr_P1.pdf

  73. U.S. FDA (2007) Clinical pharmacology and biopharmaceutics review—trospium chloride modified release. https://www.accessdata.fda.gov/drugsatfda_docs/nda/2007/022103s000_ClinPharmR.pdf

  74. Schladitz-Keil G, Spahn H, Mutschler E (1986) Determination of the bioavailability of the quaternary compound trospium chloride in man from urinary excretion data. Arzneimittelforschung 36(6):984–987

    CAS  PubMed  Google Scholar 

  75. Radwan A, Amidon GL, Langguth P (2012) Mechanistic investigation of food effect on disintegration and dissolution of BCS class III compound solid formulations: the importance of viscosity. Biopharm Drug Dispos 33(7):403–416

    Article  CAS  PubMed  Google Scholar 

  76. Riedmaier AE et al (2020) Use of physiologically based pharmacokinetic (PBPK) modeling for predicting drug-food interactions: an industry perspective. AAPS J 22(6):123

    Article  CAS  PubMed  Google Scholar 

  77. Zhang X et al (2020) Application of PBPK modeling and simulation for regulatory decision making and its impact on US prescribing information: an update on the 2018-2019 submissions to the US FDA’s Office of Clinical Pharmacology. J Clin Pharmacol 60(S1):S160–S178

    Article  CAS  PubMed  Google Scholar 

  78. Di Wu MS, Kollipara S, Ahmed T, Saini AK, Heimbach T (2022) Physiologically based pharmacokinetics modeling in biopharmaceutics: case studies for establishing the bioequivalence safe space for generic and innovator drugs (submitted). Pharm Res 40:337

    Article  PubMed  Google Scholar 

  79. Mudie DM, Amidon GL, Amidon GE (2010) Physiological parameters for oral delivery and in vitro testing. Mol Pharm 7(5):1388–1405

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Mudie DM et al (2020) Selection of in vivo predictive dissolution media using drug substance and physiological properties. AAPS J 22(2):34–34

    Article  CAS  PubMed  Google Scholar 

  81. Pepin XJ et al (2021) Understanding mechanisms of food effect and developing reliable pbpk models using a middle-out approach. AAPS J 23(1):1–14

    Article  Google Scholar 

  82. Parrott N et al (2009) Predicting pharmacokinetics of drugs using physiologically based modeling—application to food effects. AAPS J 11(1):45–53

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Heimbach T et al (2013) Case studies for practical food effect assessments across BCS/BDDCS class compounds using in silico, in vitro, and preclinical in vivo data. AAPS J 15(1):143–158

    Article  CAS  PubMed  Google Scholar 

  84. Andreas CJ et al (2017) Mechanistic investigation of the negative food effect of modified release zolpidem. Eur J Pharm Sci 102:284–298

    Article  CAS  PubMed  Google Scholar 

  85. Tistaert C et al (2019) Food effect projections via physiologically based pharmacokinetic modeling: predictive case studies. J Pharm Sci 108(1):592–602

    Article  CAS  PubMed  Google Scholar 

  86. Kushwah V et al (2021) On absorption modeling and food effect prediction of rivaroxaban, a BCS II drug orally administered as an immediate-release tablet. Pharmaceutics 13(2):283

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Shono Y et al (2009) Prediction of food effects on the absorption of celecoxib based on biorelevant dissolution testing coupled with physiologically based pharmacokinetic modeling. Eur J Pharm Biopharm 73(1):107–114

    Article  CAS  PubMed  Google Scholar 

  88. Shono Y et al (2010) Forecasting in vivo oral absorption and food effect of micronized and nanosized aprepitant formulations in humans. Eur J Pharm Biopharm 76(1):95–104

    Article  CAS  PubMed  Google Scholar 

  89. Xia B et al (2013) Utility of physiologically based modeling and preclinical in vitro/in vivo data to mitigate positive food effect in a BCS class 2 compound. AAPS PharmSciTech 14(3):1255–1266

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Cristofoletti R, Patel N, Dressman JB (2016) Differences in food effects for 2 weak bases with similar BCS drug-related properties: what is happening in the intestinal lumen? J Pharm Sci 105(9):2712–2722

    Article  CAS  PubMed  Google Scholar 

  91. Parrott NJ et al (2016) Physiologically based absorption modeling to explore the impact of food and gastric pH changes on the pharmacokinetics of alectinib. AAPS J 18(6):1464–1474

    Article  CAS  PubMed  Google Scholar 

  92. Rose RH et al (2017) Incorporation of the time-varying postprandial increase in splanchnic blood flow into a PBPK model to predict the effect of food on the pharmacokinetics of orally administered high-extraction drugs. AAPS J 19(4):1205–1217

    Article  CAS  PubMed  Google Scholar 

  93. Radwan A et al (2019) Evaluation of food effect on the oral absorption of clarithromycin from immediate release tablet using physiological modelling. Biopharm Drug Dispos 40(3–4):121–134

    Article  CAS  PubMed  Google Scholar 

  94. Lloyd RS et al (2020) Negative food effect of Danirixin: use of PBPK modelling to explore the effect of formulation and meal type on clinical PK. Pharm Res 37(12):233

    Article  CAS  PubMed  Google Scholar 

  95. Arora S et al (2020) Biopharmaceutic in vitro in vivo extrapolation (IVIV_E) informed physiologically-based pharmacokinetic model of ritonavir Norvir tablet absorption in humans under fasted and fed state conditions. Mol Pharm 17(7):2329–2344

    Article  CAS  PubMed  Google Scholar 

  96. Emami Riedmaier A et al (2018) Mechanistic physiologically based pharmacokinetic modeling of the dissolution and food effect of a biopharmaceutics classification system IV compound—the Venetoclax story. J Pharm Sci 107(1):495–502

    Article  CAS  PubMed  Google Scholar 

  97. Zhang H et al (2014) Application of physiologically based absorption modeling to formulation development of a low solubility, low permeability weak base: mechanistic investigation of food effect. AAPS PharmSciTech 15(2):400–406

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Pharmaceutical Sciences and Clinical Supply, Merck & Co., Inc., Rahway, NJ, USA

    Di Wu, John P. Gleeson & Filippos Kesisoglou

Authors
  1. Di Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. John P. Gleeson
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Filippos Kesisoglou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Filippos Kesisoglou .

Editor information

Editors and Affiliations

  1. ATHENA Research Center, PharmaInformatics Unit, National & Kapodistrian University of Athens, Faculty of Pharmacy, Athens, Greece

    Panos Macheras

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Wu, D., Gleeson, J.P., Kesisoglou, F. (2023). Physiologically Based Pharmacokinetic (PBPK) Modeling Application on Food Effect Assessment. In: Macheras, P. (eds) Advances in Pharmacokinetics and Pharmacodynamics. AAPS Introductions in the Pharmaceutical Sciences, vol 9. Springer, Cham. https://doi.org/10.1007/978-3-031-29541-6_2

Download citation

Publish with us

Policies and ethics

Search

Navigation