1 / 32

K S Tan , K H Leong, L Y Chung, M I Noordin

K S Tan , K H Leong, L Y Chung, M I Noordin. Department of Pharmacy Faculty of Medicine University of Malaya Kuala Lumpur. Introduction. Optimization of pharmaceutical formulation Conventional trial-and-error approach Mathematical Modeling Method. Introduction.

ziven
Download Presentation

K S Tan , K H Leong, L Y Chung, M I Noordin

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. K S Tan, K H Leong, L Y Chung, M I Noordin Department of Pharmacy Faculty of Medicine University of Malaya Kuala Lumpur

  2. Introduction Optimization of pharmaceutical formulation • Conventional trial-and-error approach • Mathematical Modeling Method.

  3. Introduction • Furosemidehas a narrow absorption window (located at upper GI tract)1, 2 & 3. • Conventional oral formulation exhibits erratic bioavailability & unpredictable response4. Furosemide

  4. Introduction Absorption window

  5. Introduction Absorption window o [Concept adapted from Reference 1]

  6. Introduction Gastroretentive dosage form prolongs retention time in stomach & permits continuous drug release to optimal absorption site1, 2 & 5.

  7. Objectives • To optimize a formulation for furosemide characterized by a 12-hour gastroretentive and sustained release profile. • To demonstrate the usefulness of mathematical modeling method in optimization of formulation.

  8. Methods: Overview Determination of 13 model formulations (Formulae A - M) via simplex lattice design. Preparation of tablets (Formulae A – M) Tablet QC tests (Uniformity of weight, friability, tablet size, hardness) • In vitro dissolution tests (8 hours) • Enzyme-free simulated gastric fluid (SGF) pH 1.2 • USP paddle method (100 rpm) • Temperature 37±0.5˚C • Sample buffered to pH 5.8 & Assayed with UV spectrophotometry at 278 nm • In vitro tablet swelling tests • Enzyme-free simulated gastric fluid (SGF) pH 1.2 • USP paddle method (100 rpm) • Temperature 37±0.5˚C • Measurement of swelling tablet diameter (To be continued in next slide)

  9. Methods: Overview (Continued from previous slide) Data of in vitro tablet dissolution tests Data of in vitro tablet swelling tests • Multiple Linear Regression Analysis • Model-fitting • Determination of best-fit models for individual response • Multiple Linear Regression Analysis • Model-fitting • Determination of best-fit models for individual response Optimization of formulation Design-Expert® integrate all models built and solve simultaneously to search for optimal formulation based on the constraints imposed. Verification of optimal formulation (In vitro dissolution tests & tablet swelling test)

  10. Methods Mixture experimental design • Tablet excipients: • Iota-carrageenan, • Lambda-carrageenan • Acacia gum. • Simplex lattice design was employed to determine excipient composition of 13 model formulations. • Each 400 mg tablet contains 60 mg furosemide.

  11. Methods • Composition of tablet excipients for 13 model formulations.

  12. Results & Discussions In Vitro Tablet Dissolution Profiles of 13 model formulations (n = 6)

  13. Results & Discussions In Vitro Tablet Swelling Profiles of 13 model formulations (n = 6)

  14. Results & Discussions Formula D: Dissolution Profile Formula B: Dissolution Profile Formula D: Tablet Swelling Profile Formula B: Tablet Swelling Profile

  15. Results & Discussions Model-Fitting • The data of all response variables (tablet dissolution and swelling tests) for 13 formulations were fitted into various equations:

  16. Results & Discussions Models for Drug Release & Tablet Swelling Profiles

  17. Contour plots of individual response variable for in vitro tablet dissolution studies Y1.5h:% Drug released in 2 hour Y1.5h:% Drug released in 1.5 hour Y1h:% Drug released in 1 hour Y30 min:% Drug released in 30 minutes Y2h:% Drug released in 2 hours Y3h:% Drug released in 3 hours Y4h:% Drug released in 4 hours Y5h:% Drug released in 5 hours Y6h:% Drug released in 6 hours Y7h:% Drug released in 7 hours Y8h:% Drug released in 8 hours

  18. Contour plots of individual response variable for in vitro tablet swelling studies Z15min: Tablet diameter at 15th min Z30min: Tablet diameter at 30th min Z45min: Tablet diameter at 45th min Zih: Tablet diameter at 1st hour Zi.5h: Tablet diameter at 1.5th hour Z2h: Tablet diameter at 2nd hour Z3h: Tablet diameter at 3rd hour Z4h: Tablet diameter at 4th hour Z6h: Tablet diameter at 6th hour Z5h: Tablet diameter at 5th hour Z7h: Tablet diameter at 7th hour Z8h: Tablet diameter at 8th hour

  19. Results & Discussions Optimization of Formulation • Constraints imposed on: • Drug release at 2hr (12-16%), 4hr (24-32%), 6hr (42-52%) & 8 hr (70-100%). • Tablet swelling: 13-19 mm (maximizing). • Optimized formula:

  20. Results & Discussions Optimized formulation Tablet dissolution profile (A) and swelling profile (B) of optimal formulation predicted by the model. B A

  21. Results & Discussions Verification of Optimal Formulation Tablet dissolution profile (A) and swelling profile (B) of optimal formulation (Comparing observed vs. predicted data) B A (Paired-samples T-test, p > 0.05) (Paired-samples T-test, p > 0.05)

  22. Results & Discussions In Vitro Tablet Dissolution Profiles The optimal formulation exhibits a zero-order release kinetic. (Fitted into Korsmeyer-Peppas model, n = 0.94)

  23. Results & Discussions In Vitro Tablet Dissolution Profiles Commercial Product: furosemide 60 mg (Wakelkamp et al 1999) GRDF: A gastroretentive dosage form, furosemide 60 mg developed by Klausner et al (2003)5 OF: The optimal formulation obtained in this study.

  24. Conclusions • Optimal formulation with desirable release profile & tablet swelling characteristics was obtained. • An efficient optimization process: omitting the cost- and time-consuming procedures as in the conventional trial-and-error approach. • Mathematical modeling permits the characterization of drug release kinetics during the optimization process. • Graphical optimization allows evaluation of excipient’s functionality in the dosage form.

  25. References • Chawla, G, Gupta, P, Koradia, V & Bansal, AK 2003, ‘Gastroretention a means to address regional variability in intestinal drug absorption’, Pharmaceutical Technology, vol. 27, no. 7, pp. 50-68. • Davis, SS 2006, ‘Formulation strategies for absorption windows’, Drug Discovery Today, vol. 10, no. 4, pp. 249-257. • Rouge, N, Buri, P & Doelker, E 1996, ‘Drug absorption sites in the gastrointestinal tract and dosage forms for site-specific delivery’, International Journal of Pharmaceutics, vol. 136, pp. 117-139. • Ponto, LLB & Schoenwald, RD 1990, ‘Furosemide (frusemide): a pharmacokinetic/pharmacodynamic review (part I)’, Clinical Pharmacokinetics, vol. 18, no. 5, pp. 381-408. • Klausner, EA, Lavy, E, Stepensky, D, Cserepes, E, Barta, M, Friedmann, M & Hoffman, A 2003b, ‘Furosemide pharmacokinetics and pharmacodynamics following gastroretentive dosage form administration to healthy volunteers’, Journal of Clinical Pharmacology, vol. 43, pp. 711-720. • Wakelkamp, M, Blechert, Å, Eriksson, M, Gjellan, K & Graffner, C 1999, ‘The influence of frusemide formulation on diuretic effect and efficiency’, British Journal of Clinical Pharmacology, vol. 48, pp. 361-366.

  26. Results & Discussions Model-fitting Summary for Tablet Dissolution Profiles

  27. Results & Discussions Model-fitting Summary for Tablet Swelling Profiles

  28. Results & Discussions • Experimental dissolution data of optimal formula fitted into Korsmeyer-Peppas model. Korsmeyer-Peppas model:

  29. Tan K S - Aug 2007

  30. Tan K S - Aug 2007

More Related