Abstract
The purpose of this study was to examine absorption of basic drugs as a function of the composite solubility curve and intestinally relevant pH by using a gastrointestinal tract (GIT) absorption simulation based on the advanced compartmental absorption and transit model. Absorption simulations were carried out for virtual monobasic drugs having a range of pKa, log D, and dose values as a function of presumed solubility and permeability. Results were normally expressed as the combination that resulted in 25% absorption. Absorption of basic drugs was found to be a function of the whole solubility/pH relationship rather than a single solubility value at pH 7. In addition, the parameter spaces of greatest sensitivity were identified. We compared 3 theoretical scenarios: the GIT pH range overlapping (1) only the salt solubility curve, (2) the salt and base solubility curves, or (3) only the base curve. Experimental solubilities of 32 compounds were determined at pHs of 2.2 and 7.4, and they nearly all fitted into 2 of the postulated scenarios. Typically, base solubilities can be simulated in silico, but salt solubilities at low pH can only be measured. We concluded that quality absorption simulations of candidate drugs in most cases require experimental solubility determination at 2 pHs, to permit calculation of the whole solubility/pH profile.
KeyWords: GIT, absorption simulation, pH solubility curve, BCS, solid-state properties, solubility screening
References
- 1.Simulations Plus, Inc. Available at: http://www.simulationsplus.com.
- 2.Press WH. Numerical recipes. In: Teukolsky SA, Vetterling WT, Flannery BP, editors. The Art of Scientific Computing. New York, NY: Cambridge University Press; 1992. pp. 566–580. [Google Scholar]
- 3.Ungell A-L, Nylander S, Bergstrand S, Sjöberg Å, Lemernäs H. Membrane transport of drugs in different regions of the intestinal tract of the rat. J Pharm Sci. 1998;87(3):360–366. doi: 10.1021/js970218s. [DOI] [PubMed] [Google Scholar]
- 4.Adson A, Burton PS, Raub TJ, Barsuhn CL, Audus KL, Ho NF. Passive diffusion of weak organic electrolytes across Caco-2 cell monolayers: uncoupling the contributions of hydrodynamic, transcellular, and paracellular barriers. J Pharm Sci. 1995;84(10):1197–1204. doi: 10.1002/jps.2600841011. [DOI] [PubMed] [Google Scholar]
- 5.Selick HE, Beresford AP, Tarbit MH. The emerging importance of predictive ADME simulation in drug discovery. Drug Discov Today. 2002;7(2):109–116. doi: 10.1016/S1359-6446(01)02100-6. [DOI] [PubMed] [Google Scholar]
- 6.Amidon GL, Lennemas 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(3):423–420. doi: 10.1023/A:1016212804288. [DOI] [PubMed] [Google Scholar]
- 7.Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev. 1997;23(1–3):3–25. doi: 10.1016/S0169-409X(96)00423-1. [DOI] [PubMed] [Google Scholar]
- 8.Devane J. Oral drug delivery technology: addressing the solubility/permeability paradigm. Pharm Technol. 1998;Nov:68–80. [Google Scholar]
- 9.Hussein AS, Lesko LJ, Lo KY, Shah VP, Volpe D, Williams RL. The biopharmaceutics classification system: highlights of the FDA s draft guidance. Dissolution technologies. 1999; May, article 1. Available at: http://www.dissolutiontech.com/DTresour/599articles/Biopharm_Class2_copy.html.
- 10.Blume HH, Schug BS. The Biopharmaceutics Classification System (BCS): class III drugs—better candidates for BA/BE waiver? Eur J Pharm Sci. 1999;9:117–121. doi: 10.1016/S0928-0987(99)00076-7. [DOI] [PubMed] [Google Scholar]
- 11.Streng WH, His SK, Helms PE, Tan HGH. General treatment of pH-solubility profiles of weak acids and bases and the effects of different acids on the solubility of a weak base. J Pharm Sci. 1984;73(12):1679–1684. doi: 10.1002/jps.2600731203. [DOI] [PubMed] [Google Scholar]
- 12.Kramer SF, Flynn GL. Solubility of organic hydrochlorides. J Pharm Sci. 1972;61(12):1896–1904. doi: 10.1002/jps.2600611203. [DOI] [PubMed] [Google Scholar]
- 13.Jorgensen WL, Duffy EM. Prediction of drug solubility from structure. Adv Drug Deliv Rev. 2002;54:355–366. doi: 10.1016/S0169-409X(02)00008-X. [DOI] [PubMed] [Google Scholar]
- 14.Parshad H, Frydenvang K, Liljefors T, Larsen CS. Correlation of aqueous solubility of salts of benzylamine with experimentally and theoretically derived parameters: a multivariate data analysis approach. Int J Pharm. 2002;237:193–207. doi: 10.1016/S0378-5173(02)00042-X. [DOI] [PubMed] [Google Scholar]
- 15.Bergstrom CAS, Norinder U, Luthman K, Artursson P. Experimental and computational screening models for prediction of aqueous drug solubility. Pharm Res. 2002;19(2):182–188. doi: 10.1023/A:1014224900524. [DOI] [PubMed] [Google Scholar]
- 16.Maeda H, Wu J, Sawa T, Matsumura Y, Hori K. Tumor vascular permeability and the EPR effect in macromolecular therapeutics: a review. J Controlled Rel. 2000;65:271–284. doi: 10.1016/S0168-3659(99)00248-5. [DOI] [PubMed] [Google Scholar]
- 17.Gao H, Shanmugasundaram V, Lee P. Estimation of aqueous solubility of organic compounds with QSPR approach. Pharm Res. 2002;19(2):497–503. doi: 10.1023/A:1015103914543. [DOI] [PubMed] [Google Scholar]
- 18.Yoshida F, Topliss JG. QSAR model for drug human oral bioavailability. J Med Chem. 2000;43:2575–2585. doi: 10.1021/jm0000564. [DOI] [PubMed] [Google Scholar]
- 19.Balon K, Riebesehl BU, Muller BW. Drug liposome partioning as a tool for the prediction of human passive intestinal absorption. Pharm Res. 1999;16(6):882–888. doi: 10.1023/A:1018882221008. [DOI] [PubMed] [Google Scholar]
- 20.Wells JI. Pharmaceutical Preformulation. Chichester, England: Ellis Horwell Ltd; 1988. pp. 14–14. [Google Scholar]
- 21.“Clinical Pharmacology,” online at Gold Standard Multimedia. Available at: http://www.gsm.com.
- 22.ACD Labs, Toronto, Canada.