Abstract
The aims of the proposed study were to develop and verify a quantitative model-based framework to anticipate the in vivo bioequivalence of ibuprofen immediate release formulations. This stepwise approach integrated virtual bioequivalence trials to simulate the test to reference (T/R) ratio for positive (i.e., bioequivalent) and negative (i.e., non-bioequivalent) control formulations containing ibuprofen, approximated distribution of interoccasion variability (IOV) on ibuprofen peak (Cmax) and extent of exposure (AUC) by bootstrapping resampling methods, post hoc incorporation of IOV to simulated T/R ratios, and power curve analysis. After post hoc incorporation of the bootstrapped IOV to the simulated Cmax T/R geometric mean ratios, the resulting 90% confidence intervals overlapped with the in vivo observations for both pairwise comparisons. On the other hand, simulated and observed AUC TNBE/R geometric mean ratios differed, likely due to the lack of propagating clearance-related IOV to the simulations. This approach is in line with modern regulatory initiatives that advocate leveraging quantitative methods and modeling to modernize generic drug development and review.
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References
Amidon GL, Lennernäs H, Shah VP, Crison JR. Theoretical basis for a biopharmaceutic drug classification: the correlation of in vitro drug product dissolution and in vivo bioavailability. Pharm Res. 1995;12:413–20.
Loftsson T, Brewster ME. Pharmaceutical applications of cyclodextrins: basic science and product development. J Pharm Pharmacol. 2010;62:1607–21.
Grimm M, Koziolek M, Kühn JP, Weitschies W. Interindividual and intraindividual variability of fasted state gastric fluid volume and gastric emptying of water. Eur J Pharm Biopharm. 2018;127:309–17.
U.S. Food & Drug Administration (FDA). Bioequivalence studies with pharmacokinetic endpoints for drugs submitted under an ANDA — Guidance for Industry. 2013. https://www.fda.gov/files/drugs/published/Bioequivalence-Studies-With-Pharmacokinetic-Endpoints-for-Drugs-Submitted-Under-an-Abbreviated-New-Drug-Application.pdf. Accessed 03 March 2020.
U.S. Food & Drug Administration (FDA). Guidance for Industry SUPAC-MR: modified release solid oral dosage forms scale-up and postapproval changes: Chemistry, Manufacturing, and Controls; In Vitro Dissolution Testing and In Vivo Bioequivalence Documentation. 1997. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/supac-mr-modified-release-solid-oral-dosage-forms-scale-and-postapproval-changes-chemistry. Accessed 03 March 2020.
European Medicines Agency (EMA). Guideline On The Investigation of Bioequivalence. 2010. https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-investigation-bioequivalence-rev1_en.pdf. Accessed 03 March 2020.
U.S. Food & Drug Administration (FDA). Statistical approaches to establishing bioequivalence. 2001. https://www.fda.gov/media/70958/download. Accessed 19 June 2020.
Moreno I, Ochoa D, Román M, Cabaleiro T, Abad-Santos F. Utility of pilot studies for predicting ratios and intrasubject variability in high-variability drugs. Basic Clin Pharmacol Toxicol. 2016;119:215–21.
Heimbach T, Suarez-Sharp S, Kakhi M, Holmstock N, Olivares-Morales A, Pepin X, et al. Dissolution and translational modeling strategies toward establishing an in vitro-in vivo link-a workshop summary report. AAPS J. 2019;21(2):29.
Fang L, Kim MJ, Li Z, Wang Y, DiLiberti CE, Au J, et al. Model-informed drug development and review for generic products: summary of FDA public workshop. Clin Pharmacol Ther. 2018;104:27–30.
Butler J, Hens B, Vertzoni M, Brouwers J, Berben P, Dressman J, et al. In vitro models for the prediction of in vivo performance of oral dosage forms: recent progress from partnership through the IMI OrBiTo collaboration. Eur J Pharm Biopharm. 2019;136:70–83.
Loisios-Konstantinidis I, Cristofoletti R, Fotaki N, Turner DB, Dressman J. Establishing virtual bioequivalence and clinically relevant specifications using in vitro biorelevant dissolution testing and physiologically-based population pharmacokinetic modeling. case example: Naproxen. Eur J Pharm Sci. 2020. https://doi.org/10.1016/j.ejps.2019.105170.
Sumner T, et al. Methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling. J R Soc Interface. 2012;9:2156–66.
Cristofoletti R, Dressman JB. Bridging the gap between in vitro dissolution and the time course of ibuprofen-mediating pain relief. J Pharm Sci. 2016;105(12):3658–67.
Morris MD. Factorial sampling plans for preliminary computational experiments. Technimetrics. 1999;33(2):161–74.
Cristofoletti R, Dressman JB. FaSSIF-V3, but not compendial media, appropriately detects differences in the peak and extent of exposure between reference and test formulations of ibuprofen. Eur J Pharm Biopharm. 2016;105:134–40.
Fuchs A, Leigh M, Kloefer B, Dressman JB. Advances in the design of fasted state simulating intestinal fluids: FaSSIF-V3. Eur J Pharm Biopharm. 2015;94:229–40.
Pathak SM, Ruff A, Kostewicz ES, Patel N, Turner DB, Jamei M. Model-based analysis of biopharmaceutic experiments to improve mechanistic oral absorption modeling: an integrated in vitro in vivo extrapolation perspective using ketoconazole as a model drug. Mol Pharm. 2017;14:4305–20.
Cristofoletti R, Hens B, Patel N, Esteban VV, Schmidt S, Dressman J. Integrating drug- and formulation-related properties with gastrointestinal tract variability using a product-specific particle size approach: case example ibuprofen. J Pharm Sci. 2019;108:3842–7.
Le VNP, et al. Influence of granulation and compaction on the particle size of ibuprofen--development of a size analysis method. Int J Pharm. 2006;321:72–7.
Jamei M, Marciniak S, Feng K, Barnett A, Tucker G, Rostami-Hodjegan A. The Simcyp population-based ADME simulator. Expert Opin Drug Metab Toxicol. 2009;5:211–23.
Kolewe ME, Roberts SC, Henson MA. A population balance equation model of aggregation dynamics in Taxus suspension cell cultures. Biotechnol Bioeng. 2012;109:472–82.
Martin W, Koselowske G, Töberich H, Kerkmann T, Mangold B, Augustin J. Pharmacokinetics and absolute bioavailability of ibuprofen after oral administration of ibuprofen lysine in man. Biopharm Drug Dispos. 1990;11(3):265–78.
Abduljalil K, Cain T, Humphries H, Rostami-Hodjegan A. Deciding on success criteria for predictability of pharmacokinetic parameters from in vitro studies: an analysis based on in vivo observations. Drug Metab Dispos. 2014;42(9):1478–84.
Guest EJ, Aarons L, Houston JB, Rostami-Hodjegan A, Galetin A. Critique of the two-fold measure of prediction success for ratios: application for the assessment of drug-drug interactions. Drug Metab Dispos. 2011;39(2):170–3.
R Core Team. R: A language and environment for statistical computing. 2019. https://www.R-project.org/. Accessed 03 March 2020.
Legg TJ, Laurent AL, Leyva R, Kellstein D. Ibuprofen sodium is absorbed faster than standard ibuprofen tablets: results of two open-label, randomized, crossover pharmacokinetic studies. Drugs R D. 2014;14(4):283–90.
Troconiz IF, Armenteros S, Planelles MV, Benitez J, Calvos R, Dominguez R. Pharmacokinetic-pharmacodynamic modelling of the antipyretic effect of two oral formulations of ibuprofen. Clin Pharmacokinet. 2001;38(6):505–18.
Sugano K, Terada K. Rate- and extent-limiting factors of oral drug absorption: theory and applications. J Pharm Sci. 2015;104(9):2777–88.
Blume H, Mutschler E. Bioaquivalenz, Qualitatsbewertung wirkstoffgleicher Fertigarzneimittel, Teil I/II, Isosorbiddinitrat 6. Erg¨anzungslieferung, Govi-Verlag Pharmazeutischer Verlag, Frankfurt/Main-Eschborn; 1996.
Lozoya-Agullo I, Araújo F, González-Álvarez I, Merino-Sanjuán M, González-Álvarez M, Bermejo M, et al. PLGA nanoparticles are effective to control the colonic release and absorption on ibuprofen. Eur J Pharm Sci. 2018;115:119–25.
Atkinson HC, Stanescu I, Frampton C, Salem II, Beasley CPH, Robson R. Pharmacokinetics and bioavailability of a fixed-dose combination of ibuprofen and paracetamol after intravenous and Oral administration. Clin Drug Investig. 2015;35:625–32.
Davit BM, Nwakama PE, Buehler GJ, Conner DP, Haidar SH, Patel DT, et al. Comparing generic and innovator drugs: a review of 12 years of bioequivalence data from the United States Food and Drug Administration. Ann Pharmacother. 2009;43:1583–97.
Mitra A. Maximizing the role of physiologically based Oral absorption modeling in generic drug development. Clin Pharmacol Ther. 2019;105:307–9.
Lionberger RA. Innovation for generic drugs: science and research under the generic drug user fee amendments of 2012. Clin Pharmacol Ther. 2019;105:878–85.
Lionberger RA. Decision science for generic drug development and review. J Clin Pharmacol. 2019;59:1249–51.
Manolis E, Musuamba FT, Karlsson KE. Regulatory considerations for building an in silico clinical pharmacology backbone by 2030. Clin Pharmacol Ther. 2020;107:746–8. https://doi.org/10.1002/cpt.1772.
Acknowledgments
The authors thank Simcyp® Limited for providing an academic license of the Simcyp® Simulator v18.2 and 19.1 as well as the license of the SIVA® toolkit v3 to the Center for Pharmacometrics and Systems Pharmacology, University of Florida without charge. Bart Hens acknowledges the Flemish Research Council (FWO: applicant number 12R2119N). Ioannis Loisios-Konstantinidis would like to thank the European Union’s Horizon 2020 Research and Innovation Program under grant agreement No 674909 (PEARRL).
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I.L.K., B.H, A.M., S.K., C.C., and R.C. wrote the manuscript; R.C. designed the research; I.L.K., B.H. and R.C. performed the research; I.L.K., B.H., S.K., C.C., and R.C. analyzed the data.
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Loisios-Konstantinidis, I., Hens, B., Mitra, A. et al. Using Physiologically Based Pharmacokinetic Modeling to Assess the Risks of Failing Bioequivalence Criteria: a Tale of Two Ibuprofen Products. AAPS J 22, 113 (2020). https://doi.org/10.1208/s12248-020-00495-4
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DOI: https://doi.org/10.1208/s12248-020-00495-4