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Physiologically Based Absorption Modeling to Explore the Impact of Food and Gastric pH Changes on the Pharmacokinetics of Alectinib


Alectinib, a lipophilic, basic, anaplastic lymphoma kinase (ALK) inhibitor with very low aqueous solubility, has received Food and Drug Administration-accelerated approval for the treatment of patients with ALK+ non-small-cell lung cancer. This paper describes the application of physiologically based absorption modeling during clinical development to predict and understand the impact of food and gastric pH changes on alectinib absorption. The GastroPlus software was used to develop an absorption model integrating in vitro and in silico data on drug substance properties. Oral pharmacokinetics was simulated by linking the absorption model to a disposition model fit to pharmacokinetic data obtained after an intravenous infusion. Simulations were compared to clinical data from a food effect study and a drug-drug interaction study with esomeprazole, a gastric acid-reducing agent. Prospective predictions of a positive food effect and negligible impact of gastric pH elevation were confirmed with clinical data, although the exact magnitude of the food effect could not be predicted with confidence. After optimization of the absorption model with clinical food effect data, a refined model was further applied to derive recommendations on the timing of dose administration with respect to a meal. The application of biopharmaceutical absorption modeling is an area with great potential to further streamline late stage drug development and with impact on regulatory questions.

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Non-small-cell lung cancer


Anaplastic lymphoma kinase


Sodium lauryl sulfate


Fed state simulated intestinal fluid


Fasted state simulated intestinal fluid


Physiologically based pharmacokinetics


Proton pump inhibitors

C max :

Maximal plasma concentration


Area under the curve


  1. Shaw AT, Solomon B. Targeting anaplastic lymphoma kinase in lung cancer. Clin Cancer Res. 2011;17(8):2081–6.

    Article  CAS  PubMed  Google Scholar 

  2. Morcos, P et al. Absorption, distribution, metabolism and excretion (ADME) of the ALK inhibitor alectinib: results from an absolute bioavailability and mass balance study in healthy subjects. Xenobiotica 2016: p. 1-13.

  3. Alecensa drug label. 2015; Available from:

  4. Jones HM et al. Physiologically based pharmacokinetic modeling in drug discovery and development: a pharmaceutical industry perspective. Clin Pharmacol Ther. 2015;97(3):247–62.

    Article  CAS  PubMed  Google Scholar 

  5. Parrott N, Lave T. Applications of physiologically based absorption models in drug discovery and development. Mol Pharm. 2008;5(5):760–75.

    Article  CAS  PubMed  Google Scholar 

  6. Takano R et al. Oral absorption of poorly water-soluble drugs: computer simulation of fraction absorbed in humans from a miniscale dissolution test. Pharm Res. 2006;23(6):1144–56.

    Article  CAS  PubMed  Google Scholar 

  7. Simulations Plus, I., GastroPlus user manual, 2015: Lancaster, California 93534-2902.

  8. Heikkinen AT et al. Application of PBPK modeling to predict human intestinal metabolism of CYP3A substrates—an evaluation and case study using GastroPlus. Eur J Pharm Sci. 2012;47:375–86.

    Article  CAS  PubMed  Google Scholar 

  9. Jones H et al. Predicting pharmacokinetic food effects using biorelevant solubility media and physiologically based modelling. Clin Pharmacokinet. 2006;45(12):1213–26.

    Article  CAS  PubMed  Google Scholar 

  10. Parrott, N. and T. Lave. Computer models for predicting drug absorption, in oral drug absorption, J. Dressman and C. Reppas, Editors. 2010, Informa.

  11. Hasselbalch KA. Die Berechnung der Wasserstoffzahl des Blutes aus der freien und gebunden Kohlensäure desselben, und die Sauerstoffbindung des Blutes als Funktion der Wasserstoffzahl. Die Biochem. 1916;78:112–44.

    CAS  Google Scholar 

  12. Simulations Plus, I., 1220 W. Avenue J, Lancaster, California 93534-2902, Available from:

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Porter CJH, Trevaskis NL, Charman WN. Lipids and lipid-based formulations: optimizing the oral delivery of lipophilic drugs. Nat Rev Drug Discov. 2007;6:231.

    Article  CAS  PubMed  Google Scholar 

  15. Mithani SD et al. Estimation of the increase in solubility of drugs as a function of bile salt concentration. Pharm Res. 1996;13(1):163–7.

    Article  CAS  PubMed  Google Scholar 

  16. Jantratid E et al. Dissolution media simulating conditions in the proximal human gastrointestinal tract: an update. Pharm Res. 2008;25(7):1663.

    Article  CAS  PubMed  Google Scholar 

  17. Kalantzi L et al. Characterization of the human upper gastrointestinal contents under conditions simulating bioavailability/bioequivalence studies. Pharm Res. 2006;23(1):165–76.

    Article  CAS  PubMed  Google Scholar 

  18. Zhang, L. et al. pH-dependent drug-drug interactions for weak base drugs: potential implications for new drug development. Clin Pharmacol Ther. 2014.

  19. Tolman, KG. et al. The effects of oral doses of lansoprazole and omeprazole on gastric pH.

  20. Rasmussen L et al. The effects of omeprazole on intragastric pH, intestinal motility, and gastric emptying rate. Scand J Gastroenterol. 1999;7:671–5.

    Google Scholar 

  21. Morcos, P.N., L. Yu, and K. Nieforth. Absorption, distribution, metabolism, and excretion (ADME) of the ALK inhibitor alectinib: results from an absolute bioavailability/mass balance study in healthy subjects. Clin Pharmacol Ther, 2016. 99: p. Abstract PI-118.

  22. Morcos PN, Cleary Y, Dall G. Clinical drug–drug interactions (DDIs) through cytochrome P450 3A (CYP3A) for alectinib, a highly selective ALK inhibitor. Clin Pharmacol Ther, 2016. 99: p. Abstract PI-119.

  23. Morcos PN et al. Effect of food and the proton pump inhibitor (PPI) esomeprazole on the pharmacokinetics (PK) of alectinib, a highly selective ALK inhibitor, in healthy subjects. Clin Pharmacol Ther, 2016. 99: p. Abstract PI-120.

  24. Nakagawa K et al. Antitumor activity of alectinib (CH5424802/RO5424802) for ALK-rearranged NSCLC with or without prior crizotinib treatment in bioequivalence study, presented at the 50th Annual Meeting of the American Society of Clinical Oncology 2014: Chicago.

  25. Shepard T et al. Physiologically based models in regulatory submissions: output from the ABPI/MHRA forum on physiologically based modeling and simulation. CPT: Pharm Syst Pharmacol. 2015;4(4):221–5.

    CAS  Google Scholar 

  26. Wagner C et al. Application of physiologically based pharmacokinetic (PBPK) modeling to support dose selection: report of an FDA public workshop on PBPK. CPT: Pharm Syst Pharmacol. 2015;4(4):226–30.

    CAS  Google Scholar 

  27. Wagner C et al. Predicting the effect of cytochrome P450 inhibitors on substrate drugs: analysis of physiologically based pharmacokinetic modeling submissions to the US Food and Drug Administration. Clin Pharmacokinet. 2015;54(1):117–27.

    Article  CAS  PubMed  Google Scholar 

  28. Benet L, Broccatelli F, Oprea T. BDDCS applied to over 900 drugs. AAPS J. 2011;13(4):1–29.

    Article  Google Scholar 

  29. Patel N et al. Quantitative prediction of formulation-specific food effects and their population variability from in vitro data with the physiologically-based ADAM model: a case study using the BCS/BDDCS class II drug nifedipine. Eur J Pharm Sci. 2014;57:240–9.

    Article  CAS  PubMed  Google Scholar 

  30. Xia B et al. 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, 2013. 14(3).

  31. Dressman JB et al. Estimating drug solubility in the gastrointestinal tract. Adv Drug Deliv Rev. 2007;59(7):591–602.

    Article  CAS  PubMed  Google Scholar 

  32. Bergstrom CAS, Luthman K, Artursson P. Accuracy of calculated pH-dependent aqueous drug solubility. Eur J Pharm Sci. 2004;22(5):387–98.

    Article  CAS  PubMed  Google Scholar 

  33. Fuchs A, Dressman JB. Composition and physicochemical properties of fasted-state human duodenal and jejunal fluid: a critical evaluation of the available data. J Pharm Sci. 2014;103(11):3398–411.

    Article  CAS  PubMed  Google Scholar 

  34. Vertzoni M et al. Estimation of intragastric solubility of drugs: in what medium? Pharm Res. 2007;24(5):909–17.

    Article  CAS  PubMed  Google Scholar 

  35. Jinno J et al. Dissolution of ionizable water-insoluble drugs: the combined effect of pH and surfactant. 2000. p. 268-274.

  36. Granero GE, Ramachandran C, Amidon GL. Dissolution and solubility behavior of fenofibrate in sodium lauryl sulfate solutions. Drug Dev Ind Pharm. 2005;31:917–22.

    Article  CAS  PubMed  Google Scholar 

  37. Glomme AJ, März JB, Dressman. Predicting the intestinal solubility of poorly soluble drugs, in Pharmacokinetic Profiling in Drug Research, D.S.D.K. Prof. Bernard Testa, Prof. Heidi Wunderli-Allenspach, Prof. Gerd Folkers, Editor 2007, Wiley: Zürich. p. 259-280.

  38. Parrott N et al. Physiologically based absorption modelling to predict the impact of drug properties on pharmacokinetics of bitopertin. AAPS J. 2014;16(5):1077–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. EMA, Guideline on the investigation of drug interactions, CHMP, editor 2012.

  40. Yasui-Furukori N et al. Time effects of food intake on the pharmacokinetics and pharmacodynamics of quazepam. Br J Clin Pharmacol. 2003;55(4):382–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Research, F.a.D.A.C.f.D.E.a. Center For Drug Evaluation And Research. Application Number:208434orig1s000. Clinical Pharmacology And Biopharmaceutics Review(S). 2015 10- March-2016; Available from:

  42. Budha NR et al. Drug absorption interactions between oral targeted anticancer agents and PPIs: is pH-dependent solubility the Achilles heel of targeted therapy? Clin Pharm Ther. 2012;92(2):203–13.

    Article  CAS  Google Scholar 

  43. He, H. PBPK approaches in drug development and regulatory submissions: rewards and challenges, in AAPS 2015 2015: Orlando.

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Correspondence to Neil J Parrott.

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Parrott, N.J., Yu, L.J., Takano, R. et al. Physiologically Based Absorption Modeling to Explore the Impact of Food and Gastric pH Changes on the Pharmacokinetics of Alectinib. AAPS J 18, 1464–1474 (2016).

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  • biopharmaceutics
  • food effect
  • gastric acid-reducing agents
  • proton pump inhibitors