In vitro-in vivo correlations of self-emulsifying drug delivery systems combining the dynamic lipolysis model and neuro-fuzzy networks

European Journal of Pharmaceutics and Biopharmaceutics

Volumn 69, Issue 3, 2008, Pages 887-898

  Fatouros, Dimitrios G ^a   Nielsen, Flemming Seier ^a   Douroumis, Dionysios ^b   Hadjileontiadis, Leontios J ^c   Mullertz, Anette ^a  

^a UNIVERSITY OF COPENHAGEN   (Denmark)

^b UNIVERSITY OF GREENWICH   (United Kingdom)

^c ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

In vitro dynamic lipolysis model; In vitro in vivo correlations (IVIVC); Mathematical modelling; Neuron fuzzy networks; Self emulsifying drug delivery systems

Indexed keywords

CREMOPHOR; LIPID; PHOSPHATIDYLCHOLINE; PROBUCOL;

ANIMAL EXPERIMENT; AQUEOUS SOLUTION; AREA UNDER THE CURVE; ARTICLE; COMPLEX FORMATION; DRUG ABSORPTION; DRUG BIOAVAILABILITY; DRUG BLOOD LEVEL; DRUG DELIVERY SYSTEM; DRUG FORMULATION; DRUG RELEASE; EMULSION; IN VITRO STUDY; IN VIVO STUDY; LIPOLYSIS; MALE; MICELLE; MINIPIG; MODEL; NONHUMAN; SIMULATION;

ALGORITHMS; ANIMALS; ANTICHOLESTEREMIC AGENTS; ARTIFICIAL INTELLIGENCE; BIOLOGICAL AVAILABILITY; CHEMISTRY, PHARMACEUTICAL; DRUG DELIVERY SYSTEMS; EMULSIONS; EXCIPIENTS; FUZZY LOGIC; LIPASE; LIPIDS; LIPOLYSIS; MALE; MICELLES; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); OILS; PROBUCOL; SODIUM HYDROXIDE; SWINE;

EID: 48149100781     PISSN: 09396411     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejpb.2008.01.022     Document Type: Article

References (50)

1. Charman S.A., Charman W.N., Rogge M.C., Wilson T.D., Dutko F.J., and Pouton C.W. Self-emulsifying drug delivery systems: formulation and biopharmaceutic evaluation of an investigational lipophilic compound. Pharm. Res. 9 (1992) 87-93
2. Pouton C.W. Lipid formulations for oral administration of drugs: non-emulsifying, self-emulsifying and 'self-microemulsifying' drug delivery systems. Eur. J. Pharm. Sci. 11 (2000) S93-S98
3. Charman W.N. Lipids, lipophilic drugs, and oral drug delivery - some emerging concepts. J. Pharm. Sci. 89 (2000) 967-978
4. Reymond J.P., and Sucker H. In vitro model for cyclosporin intestinal absorption in lipid vehicles. Pharm. Res. 5 (1988) 673-676
5. Zangenberg N.H., Mullertz A., Kristensen H.G., and Hovgaard L. A dynamic in vitro lipolysis model. I. Controlling the rate of lipolysis by continuous addition of calcium. Eur. J. Pharm. Sci. 14 (2001) 115-122
6. Zangenberg N.H., Mullertz A., Kristensen H.G., and Hovgaard L. A dynamic in vitro lipolysis model. II: Evaluation of the model. Eur. J. Pharm. Sci. 14 (2001) 237-244
7. Porter C.J., Kaukonen A.M., Taillardat-Bertschinger A., Boyd B.J., O'Connor J.M., Edwards G.A., and Charman W.N. Use of in vitro lipid digestion data to explain the in vivo performance of triglyceride-based oral lipid formulations of poorly water-soluble drugs: studies with halofantrine. J. Pharm. Sci. 93 (2004) 1110-1121
8. Porter C.J., Kaukonen A.M., Boyd B.J., Edwards G.A., and Charman W.N. Susceptibility to lipase-mediated digestion reduces the oral bioavailability of danazol after administration as a medium-chain lipid-based microemulsion formulation. Pharm. Res. 21 (2004) 1405-1412
9. Christensen J.O., Schultz K., Mollgaard B., Kristensen H.G., and Mullertz A. Solubilisation of poorly water-soluble drugs during in vitro lipolysis of medium- and long-chain triacylglycerols. Eur. J. Pharm. Sci. 23 (2004) 287-296
10. Sullivan T.J., Sakmar E., and Wagner J.G. Comparative bioavailability: a new type of in vitro-in vivo correlation exemplified by prednisone. J. Pharmacokinet. Biopharm. 4 (1976) 173-181
11. Graffner C., Nicklasson M., and Lindgren J.-E. Correlations between in vitro dissolution rate and bioavailability of alaproclate tablets. J. Pharmacokinet. Biopharm. 12 (1984) 367-380
12. Caramella C., Ferrari F., Bonferoni M.C., Sangalli M.E., De Bernardi Di Valserra M., Feletti F., and Galmozzi M.R. In vitro/in vivo correlation of prolonged release dosage forms containing diltiazem HCl. Biopharm. Drug Dispos. 14 (1993) 143-160
13. Sunesen V.H., Pedersen B.L., Kristensen H.G., and Mullertz A. In vivo in vitro correlations for a poorly soluble drug, danazol, using the flow-through dissolution method with biorelevant dissolution media. Eur. J. Pharm. Sci. 24 (2005) 305-313
14. Guidance for Industry, Extended Release Oral Dosage Forms, Development, evaluation, and application of in vitro/in vivo correlations, Ed. Food and Drug Administration, Rockville, MD, 1997.
15. Note for Guidance on Quality of Modified-Release Products, A: oral dosage forms, B: transdermal dosage forms section I Quality, Ed. Committee for Proprietary Medicinal Products, London, UK, 1999.
16. Guidance for Industry, SUPAC-MR, Modified-release solid oral dosage forms, Food and Drug Administration, Rockville, MD, 1997.
17. Wood R.W., Martis L., Gillum A.W., Roseman T.J., Lin L., and Bernardo P. In vitro dissolution and in vivo bioavailability of commercial levothyroxine sodium tablets in the hypothyroid dog model. J. Pharm. Sci. 79 (1990) 124-127
18. Barr W.H., Zola E.M., Candler E.L., Hwang S.-M., Tendolkar A.V., Shamburek R., Parker B., and Hilty M.D. Differential absorption of amoxicillin from the human small and large intestine. Clin. Pharmacol. Ther. 56 (1994) 279-285
19. Levy G., and Hollister L.E. Inter- and intra subject variations in drug absorption kinetics. J. Pharm. Sci. 53 (1964) 1446-1452
20. Gallant S.I. Neural Network Learning and Expert Systems (1993), The MIT Press, Cambridge, MA
21. Hagan M.T., Demuth H.B., and Beale M. Neural Network Design (1996), PWS Publishing, Boston, MA
22. Specht D.F. A general regression neural network. IEEE Trans. Neural Networks 2 (1991) 568-576
23. Erb R. The back-propagation neural network - a Bayesian classifier. Introduction and applicability to pharmacokinetics. Clin. Pharmacokinet. 29 (1995) 69-79
24. Hussain A.S., Johnson R.D., Vachharajani N.N., and Ritschel W.A. Feasibility of developing a neural network for prediction of human pharmacokinetic parameters from animal data. Pharm. Res. 10 (1993) 466-469
25. Brier M.E., Zurada J.M., and Aronoff G.R. Neural network predicted peak and trough gentamicin concentrations. Pharm. Res. 12 (1995) 406-412
26. Veng-Pedersen P., and Modi N.B. Application of neural networks to pharmacodynamics. J. Pharm. Sci. 82 (1993) 918-926
27. Hussain A.S., Yu X.Q., and Johnson R.D. Application of neural computing in pharmaceutical product development. Pharm. Res. 8 (1991) 1248-1252
28. Dowell J.A., Hussain A., Devane J., and Young D. Artificial neural networks applied to the in vitro-in vivo correlation of an extended-release formulation: initial trials and experience. J. Pharm. Sci. 88 (1999) 154-160
29. Gelman A., Bois F., and Jiang J. Physiological pharmacokinetic analysis using population modeling and informative prior distributions. J. Am. Stat. Assoc. 91 (1996) 1400-1412
30. Kortejärvi H., Malkki J., Marvola M., Urtti A., Yliperttula M., and Pajunen P. Level A in vitro-in vivo correlation (IVIVC) model with Bayesian approach to formulation series. J. Pharm. Sci. 95 (2006) 1595-1605
31. Jang J.-S.R. ANFIS: adaptive-network-based fuzzy inference systems. IEEE Trans. Sys. Man Cyber. 23 (1993) 665-685
32. SGS-Thomson Microelectronics, http://www.st.com.
33. Zadeh L.A. Fuzzy sets. Inf. Control 8 (1965) 338-353
34. Pannier A.K., Brand R.M., and Jones D.D. Fuzzy modeling of skin permeability coefficients. Pharm. Res. 20 (2003) 143-148
35. Ross T.J. Fuzzy logic with engineering applications (1995), McGraw-Hill Inc., New York
36. Bernd T., Kleutges M., and Kroll A. Nonlinear black box modeling-fuzzy networks versus neural networks. Neural Comput. & Appl. 8 (1999) 151-162
37. Kroll A. Identification of functional fuzzy models using multidimensional reference fuzzy sets. Fuzzy Sets Sys. 80 (1996) 149-158
38. Nielsen F.S., Gibault E., Ljusberg-Wahren H., Arleth L., Pedersen J.S., and Müllertz A. Formulation design and characterization of prototype self-microemulsifying formulations of lipophilic compounds. J. Pharm. Sci. 96 (2007) 876-892
39. Pedersen B.L., Brondsted H., Lennernas H., Christensen F.N., Müllertz A., and Kristensen H.G. Dissolution of hydrocortisone in human and simulated intestinal fluids. Pharm. Res. 17 (2000) 183-189
40. Gargouri Y., Moreau H., and Verger R. Gastric lipases: biochemical and physiological studies. Biochim. Biophys. Acta 1006 (1989) 255-271
41. Dressman J.B., Berardi R.R., Dermentzoglou C.L., Russell T.L., Schmaltz S.P., Barnett J.L., and Jarvenpaa K.M. Upper gastrointestinal (GI) pH in young, healthy men and women. Pharm. Res. 7 (1990) 756-761
42. The United States Pharmacopoeia/The National Formulary, (USP 26/NF21), United States Pharmacopeia Convection, Inc., Rockville, USP 26, 2003.
43. MacGregor K.J., Embleton J.K., Lacy J.E., Perry A.E., Solomon L.J., Seager H., and Pouton C.W. Influence of lipolysis on drug absorption from the gastro-intestinal tract. Adv. Drug Deliv. Rev. 25 (1997) 33-46
44. Nielsen F.S., Petersen K.B., and Müllertz A. Bioavailability of probucol from lipid and surfactant based formulations in minipigs: influence of particle size and dietary state. Eur. J. Pharm. Biopharm. 69 (2008) 553-562
45. Fayyad U.M., Piatetsky-Sapiro G., and Smyth P. From data mining to knowledge discovery: an overview. In: Fayyad U.M., Piatetsky-Sapiro G., Smyth P., and Uthurusamy R. (Eds). Advances in Knowledge Discovery and Data Mining (1996), AAAI Press/MIT Press, Menlo Park, CA 37-54
46. Tsoukalas L.H. Fuzzy and Neural Approaches in Engineering (1997), Wiley & Sons, Inc., New York
47. Yamaguchi T., Imasaki N., and Haruchi K. Fuzzy rule realization on associative memory system. Proc. IJCNN '90 2 (1990) 720-723
48. Rumelhart D.E., McClelland J.L., and PDP Research Group. Parallel Distributed Processing (1986), MIT Press, Cambridge, MA
49. Horikawa S., Furuhashi T., and Uchikawa Y. On fuzzy modeling using fuzzy neural networks with the back-propagation algorithm. IEEE Trans. Neural. Networks 3 5 (1992) 801-806
50. Jang J.S.R., Sun C.T., and Mizutani E. Neuro-Fuzzy and Soft Computing - A Computational Approach to Learning and Machine Intelligence (1997), Prentice Hall Eaglewood Cliffs, NJ