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Article

In Silico Prediction of Plasma Concentrations of Fluconazole Capsules with Different Dissolution Profiles and Bioequivalence Study Using Population Simulation

by
Marcelo Dutra Duque
1,2,*,
Daniela Amaral Silva
1,3,
Michele Georges Issa
1,
Valentina Porta
1,
Raimar Löbenberg
3 and
Humberto Gomes Ferraz
1
1
Department of Pharmacy, Faculty of Pharmaceutical Sciences, Universidade de São Paulo—USP, Av. Prof. Lineu Prestes, 580, São Paulo—SP 05508-000, Brazil
2
Department of Pharmaceutical Sciences, Institute of Environmental, Chemical and Pharmaceutical Sciences, Universidade Federal de São Paulo—UNIFESP, Rua São Nicolau, 210, Centro, Diadema—SP 09913-030, Brazil
3
Faculty of Pharmacy & Pharmaceutical Sciences, Katz Group-Rexall Centre for Pharmacy & Health Research, University of Alberta, 11361 – 87 Avenue, Edmonton, AB T6G 2E1, Canada
*
Author to whom correspondence should be addressed.
Pharmaceutics 2019, 11(5), 215; https://doi.org/10.3390/pharmaceutics11050215
Submission received: 26 February 2019 / Revised: 25 March 2019 / Accepted: 29 March 2019 / Published: 5 May 2019

Abstract

:
A biowaiver is accepted by the Brazilian Health Surveillance Agency (ANVISA) for immediate-release solid oral products containing Biopharmaceutics Classification System (BCS) class I drugs showing rapid drug dissolution. This study aimed to simulate plasma concentrations of fluconazole capsules with different dissolution profiles and run population simulation to evaluate their bioequivalence. The dissolution profiles of two batches of the reference product Zoltec® 150 mg capsules, A1 and A2, and two batches of other products (B1 and B2; C1 and C2), as well as plasma concentration–time data of the reference product from the literature, were used for the simulations. Although products C1 and C2 had drug dissolutions < 85% in 30 min at 0.1 M HCl, simulation results demonstrated that these products would show the same in vivo performance as products A1, A2, B1, and B2. Population simulation results of the ln-transformed 90% confidence interval for the ratio of Cmax and AUC0–t values for all products were within the 80–125% interval, showing to be bioequivalent. Thus, even though the in vitro dissolution behavior of products C1 and C2 was not equivalent to a rapid dissolution profile, the computer simulations proved to be an important tool to show the possibility of bioequivalence for these products.

Graphical Abstract

1. Introduction

Bioavailability (BA) is the rate and extent of absorption of an active pharmaceutical ingredient from a dosage form when it becomes available at the site of action. Drug products that are pharmaceutical equivalents are considered bioequivalent and, therefore, interchangeable when BA is not statistically different between the two products after administration at the same dose and under similar experimental conditions in a bioequivalence (BE) study. For purposes of establishing BE, a test product must be compared to a reference product [1,2,3].
For highly soluble and highly permeable drugs, categorized as class I according to the Biopharmaceutics Classification System (BCS), the waiver of BE studies can be considered in immediate-release (IR) products [4]. In this case, the rate and extent of absorption are not dependent on drug dissolution but rather solely on gastric emptying [5]. In IR products containing BCS class I drugs with rapid (≥85% in 30 min) or very rapid (≥85% in 15 min) in vivo dissolution in relation to gastric emptying, BA is independent of drug dissolution or gastrointestinal transit time [4].
The Brazilian Health Surveillance Agency (ANVISA) guidance for biowaiver [6] allows the waiver of bioequivalence studies for BCS class I drugs that are described in a Normative Instruction [7], which was updated later [8]. For this purpose, the applicant should provide data demonstrating rapid drug dissolution from the IR dosage form, i.e., at least 85% of the drug dissolved within 30 min under all conditions tested for both test and reference products [6]. The dissolution test conditions accepted by ANVISA are suggested in the Pharmaceutical Equivalence and Comparative Studies of Dissolution Profiles guidance [9]: apparatus 1 at 100 rpm or apparatus 2 at 50 rpm; dissolution media pH 1.2 HCl or simulated gastric fluid without enzyme, pH 4.5 and pH 6.8 (or simulated intestinal fluid); 900 mL and temperature 37 ± 1 °C.
Fluconazole is a triazole antifungal agent indicated for superficial and systemic infections, and is available for oral administration in capsules containing 50–150 mg of the drug; it is generally well absorbed, showing a BA of about 90% [10]. Due to its clinical and biopharmaceutical characteristics, fluconazole is a candidate for BCS class I biowaiver [11,12]. This drug is described in the Brazilian Health Surveillance Agency’s Normative Instruction list of drug candidates for the waiver of bioequivalence studies according to BCS [8].
Currently, the prediction of intestinal absorption of drugs based on computer simulations using advanced compartmental absorption and transit (ACAT) and physiologically-based pharmacokinetic (PBPK) models is a reality [13,14,15,16,17,18,19,20,21]. Computer software can be used to predict oral absorption of drugs from IR products containing different dissolution profiles, helping formulation scientists to decide on the best dissolution test conditions or formulation, gaining time, and reducing costs in drug development [17]. Computer simulations have been demonstrated to also be important for biowaiver extension for BCS class II [14,22,23] and class III drugs [24].
The dissolution criterion for the biowaiver (rapid or very rapid dissolution) of IR products containing 32 BCS class I drugs was evaluated by [25], which showed that very rapid dissolution is not necessary to guarantee BE according to BCS. However, considering the importance of appropriate dissolution tests and the possibility of requesting a waiver of BE studies when in vitro dissolution data are available for BCS class I drugs [3,6], the objective of this article was to use computer simulations to predict the plasma concentrations of fluconazole capsules with different dissolution profiles using the software GastroPlus, comparing products with rapid or very rapid drug dissolution to products that do not meet this criterion, and evaluating whether they could be bioequivalent using simulated population studies.

2. Methods

2.1. Plasma Concentration Simulations

The software GastroPlus version 9.0 (Simulations Plus Inc., Lancaster, CA, USA) was used to predict the oral absorption of fluconazole 150 mg capsules from different manufacturers compared to the reference product in Brazil, Zoltec® 150 mg capsules (Laboratórios Pfizer Ltda, Guarulhos, Brazil).
For such, a fluconazole database was created in GastroPlus. Input data consisted of values taken from the literature, including but not limited to drug solubility, pKa, and the logarithm of the partition coefficient (Log P), as well as other parameters obtained using the ADMET Predictor (Absorption, Distribution, Metabolism, Elimination and Toxicity Predictor) (Simulations Plus, Lancaster, CA, USA) module in GastroPlus (Table 1).
Plasma concentrations of the reference product (Zoltec® 150 mg capsules) previously reported by [28] were extracted from the original figure using Web Plot Digitizer [30] and used in the PKPlus module in GastroPlus to build a compartmental pharmacokinetic (PK) model. PKPlus is an optional module in GastroPlus that uses intravenous or oral plasma concentration–time data to calculate the most appropriate modeling (one-, two-, or three-compartmental models) and generate PK parameters for simulations [31].
In the GastroPlus fluconazole database, records were created for two batches of three different products, namely A1, A2, B1, B2, C1, and C2, as previously described by [29]; A1 and A2 were batches #1 and #2, respectively, of the reference product Zoltec® 150 mg capsules, whereas B1, B2, C1, and C2 were batches #1 and #2 of two different products found in the Brazilian market. The dissolution tests were performed using the United States Pharmacopeia (USP) apparatus 1 (basket) with 900 mL of 0.1 M HCl at 37 ± 0.5 °C and 100 rpm for 30 min and yielded results (n = 6 for each product) [29] that were used in the software to simulate the plasma concentration for each product (A1, A2, B1, B2, C1, and C2).
The simulations were run in GastroPlus in order to obtain the predicted values of the plasma concentration. Concentration curves were compared to that of the reference product (Ref) with respect to regression parameters generated by the software: coefficient of determination (R2), sum of square error (SSE), root mean square error (RMSE), and mean absolute error (MAE).
The pharmacokinetic parameters %F (% bioavailable), which is the percent of drug that reached the systemic circulation, Tmax, Cmax, and AUC (Area Under the Curve) were generated by GastroPlus.

2.2. Population Simulations

Population Simulator is one of the simulation modes present in GastroPlus. This mode allows the user to run simulated clinical trials for virtual subjects, combining physiology and pharmacokinetic variability within populations and considering formulation variables used as input data in the software. In this mode, Monte Carlo simulations are used to randomly generate each subject to have a unique set of parameters (gastrointestinal transit time and pH; pharmacokinetic parameters; plasma protein binding; small intestine, stomach, caecum and colon dimensions; and hepatic blood flow rate). Variations in each parameter are randomly generated for each simulated virtual subject [31].
In this way, population simulations were run in GastroPlus for each product (A1, A2, B1, B2, C1, and C2) considering in the Population Simulator mode the number of output data points to be saved for each virtual subject as 25. The number of virtual subjects chosen for the simulations was 28. This was the same number of volunteers enrolled in the bioequivalence study described by reference #28. Bioequivalence between each product and the reference Zoltec® 150 mg capsules [28] from population simulation results were presented as 90% confidence interval (CI) for the ratio of Cmax and AUC0–t using ln-transformed data. GastroPlus automatically set in green the values of 90% CI for Cmax and AUC0–t that are within the 80–125% interval, according to regulatory agencies [32,33]. The end time used for the simulations was 96 h and the average AUC0–t/AUC0–inf ratio was calculated.

3. Results and Discussion

After adding plasma concentrations of the reference product, Zoltec® 150 mg capsules, in the software GastroPlus and selecting compartmental PK modeling, the PKPlus module calculated the most appropriate compartmental model (one, two, or three compartments) considering the administration of fluconazole 150 mg as IR capsules to subjects with an average weight of 61 kg under fasting conditions. Compartmental models were compared by evaluating R2 and the Akaike Information Criterion (AIC). As shown in Table 2, the two-compartmental model presented the best fit due to the highest R2 and lowest AIC value. Table 3 presents the PK parameters predicted using the selected model.
Mean (± standard deviation, SD) clearance (CL) and central compartment volume (Vc) values for fluconazole in healthy subjects are reported in the literature as 1.272 ± 0.219 L/h and 46.3 ± 7.9 L (38.4 to 54.2 L), respectively [34], whereas T1/2 of fluconazole is about 30 h [10]. Thus, the CL value calculated using PKPlus is in accordance with the literature, and the calculated Vc is near to the lowest (38.4 L) value reported by [34].
Figure 1 shows the percent of fluconazole dissolved over time during dissolution tests of products A1, A2, B1, B2, C1, and C2 [29].
Products A1, A2, B1, B2, C1, and C2 had 91.4%, 74.9%, 100.7%, 99.9%, 17.1%, and 35.4% of drug dissolved in 15 min, respectively. Although product A2 have shown less than 85% of the drug dissolved in 15 min, only products C1 and C2 had values that did not reach 85% of drug dissolved at the end of the test (Figure 1). Considering these findings, products C1 and C2 are not expected to be bioequivalent to the reference product.
Fluconazole is a high solubility and high permeability (BCS class I) drug, which is not expected to present problems in dissolution tests. However, Charoo et al. [35] described the influence of the polymorphism of fluconazole on dissolution. This drug exhibits the polymorphic forms I, II, III, and monohydrate. The solubility values of forms I and monohydrate were reported as 4.96 and 4.21 mg/mL, respectively, and form II as 6.59 mg/mL in water at 25 °C [36,37]. Low intrinsic dissolution rate was also reported for the form I [38,39]; the tendency of form II to convert into forms I and monohydrate in the presence of high humidity values have also been reported [40]. It is possible that products C1 and C2 contain polymorphic form I or monohydrate due to the lower in vitro dissolution rate in comparison to the other products, as shown in Figure 1.
GastroPlus was used to simulate plasma concentration–time curves for all the products, including C1 and C2, and the resulting profiles were then compared to the reference product (Ref) curve plotted with experimental values (Figure 2) in order to evaluate in vivo performance.
According to the predicted plasma concentration–time curves (Figure 2), all products would show in vivo performance equivalent to that of the reference product.
Statistical parameters (R2, SSE, RMSE e MAE) generated by the software for each predicted profile in comparison to the plasma concentration–time curve of the reference product [28] are shown in Table 4.
For all predicted profiles, low values were found for the prediction error parameters SSE, RMSE, and MAE (Table 4), indicating the viability of using GastroPlus to predict plasma concentrations of fluconazole from input data. High correlation (R2) was demonstrated between the predicted plasma concentration–time curves of all products and the experimentally-determined reference curve.
The percent of drug dissolved less than 85% at 30 min for products C1 and C2 did not affect the predicted in vivo performance, as observed in the predicted plasma concentration–time curves (Figure 2) and statistical parameters (Table 4).
GastroPlus also calculates the amount of drug dissolved in vivo (AmtDiss), absorbed to the portal vein (AmtPV), total amount absorbed (AmtAbs), and the amount in the systemic circulation (AmtSC). These data are shown in Figure 3.
It can be observed in Figure 3 that products A1, A2, B1, and B2 showed similar predicted in vivo dissolution behavior with a fast amount absorbed by enterocytes, then into the portal vein, and in the systemic circulation. The slow in vitro dissolution of products C1 and C2 (Figure 1) could be attributed to the presence of the low soluble polymorphic forms I and monohydrate. Despite a small displacement of the curves (Figure 3) corresponding to the predicted in vivo dissolution (AmDiss) of products C1 and C2 was observed, it did not affect the predicted fluconazole amount absorbed (AmtAbs) and the predicted amount in the systemic circulation (AmtSC). It is expected that for fluconazole, as for BCS class I drugs, dissolution is not the limiting step for absorption.
The Cmax and AUC predicted values for products A1, A2, B1, B2, C1, and C2 and the experimental ones for the reference product (Ref) are shown in Table 5.
As stated in the Methods section, in vivo data of the reference product (Ref) was extracted from a figure containing the plasma concentration–time curve of Zoltec® 150 mg capsules described by the reference #28, using WebPlotDigitizer [30]. These in vivo values were used as input data of Ref in GastroPlus and the pharmacokinetic parameters (F%, Tmax, Cmax, and AUC0–t) presented as Obs (Table 5) were calculated by the software. These PK parameters are in accordance with those reported by reference #28 (Tmax = 2.96 h (1.96 h−3.96 h), Cmax = 3.64 µg/mL (2.85 µg/mL–4.43 µg/mL), and AUC0–t = 135.72 µg h/mL (106.20 µg h/mL–165.24 µg h/mL)). Even with the small difference found in the value of Tmax, the calculations made using GastroPlus were reasonable.
ANVISA recommendations for the waiver of BE studies according to BCS for class I drugs state that IR solid oral products must have rapid drug dissolution (≥85% in 30 min) in 0.1 M HCl, pH 4.5 and pH 6.8 [6]. In this study, even though the dissolution tests were carried out only in hydrochloric acid as the dissolution medium [29], products C1 and C2 that did not meet the requirements of the dissolution rate still showed in vivo performance equivalent to the reference product. Al-Tabakha et al. [41] evaluated different products containing amoxicillin trihydrate and potassium clavulanate. These authors observed that products considered as bioequivalents presented in vitro dissolution differences, showing that in some cases in vitro dissolution can be more discriminating than in vivo bioequivalence testing.
Population simulation results for products A1 and A2, B1 and B2, and C1 and C2 are presented in Table 6.
The 90% CI ln-transformed of the ratio of Cmax and AUC0–t for the products and reference are within the 80–125% interval (Table 6), in accordance with the regulatory guidance of the FDA [32] and ANVISA [33] for bioequivalence evaluation of test and reference products. The average AUC0–t/AUC0–inf ratios for the reference and all products were between 0.86 and 0.90, showing that the end time (96 h) used in the simulations was appropriate (>80%) to provide a reliable estimate of the extent of absorption [32,42].

4. Conclusions

Plasma concentration profile predictions and population simulation using virtual subjects obtained for fluconazole capsules with dissolution profiles that meet (A1, A2, B1, and B2) and do not meet (C1 and C2) the regulatory criterion of rapid or very rapid dissolution showed their bioequivalence. Computer simulations can be used as a tool for screening formulations that could be bioequivalent, contributing to gaining time and reducing costs for pharmaceutical companies.

Author Contributions

Conceptualization, M.D.D., D.A.S. and M.G.I.; methodology, M.D.D., D.A.S. and M.G.I.; software, M.D.D. and D.A.S.; investigation, M.D.D., D.A.S. and M.G.I.; resources, M.G.I., R.L. and H.G.F.; writing—original draft preparation, M.D.D. and M.G.I.; writing—review and editing, M.D.D., M.G.I., R.L., V.P. and H.G.F.; supervision, R.L., V.P. and H.G.F.; funding acquisition, M.G.I., R.L. and H.G.F.

Funding

This research was funded by the National Council of Scientific and Technological Development—CNPq/Brazil, grant number 400455/2014-5 (Löbenberg) and by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)—Brazil—Finance Code 001 (Issa).

Acknowledgments

Portions of these results were generated by GastroPlus software provided by Simulations Plus, Inc., Lancaster, CA, USA.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

References

  1. Silva, M.F.; Schramm, S.G.; Kano, E.K.; Koono, E.D.M.; Porta, V.; Serra, C.H.R. Bioequivalence evaluation of single doses of two tramadol formulations: A randomized, open-label, two-period crossover study in healthy Brazilian volunteers. Clin. Ther. 2010, 32, 758–765. [Google Scholar] [CrossRef]
  2. Kano, E.K.; Koono, E.E.M.; Schramm, S.G.; Serra, C.H.R.; Junior, E.A.; Pereira, R.; Freitas, M.S.T.; Iecco, M.C.; Porta, V. Average bioequivalence of single 500 mg doses of two oral formulations of levofloxacin: A randomized, open-label, two-period crossover study in healthy adult Brazilian volunteers. Braz. J. Pharm. Sci. 2015, 51, 203–211. [Google Scholar] [CrossRef]
  3. FDA. Food and Drug Administration. Guidance for Industry: Bioavailability and Bioequivalence Studies Submitted in NDAs or INDs—General Considerations. Draft Guidance. U.S. Department of Health and Human Services, Center for Drug Evaluation and Research (CDER). 2014. Available online: https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM389370.pdf (accessed on 7 June 2018).
  4. FDA. Food and Drug Administration. Guidance for Industry: Waiver on In Vivo Bioavailability and Bioequivalence Studies for Immediate-Release Solid Oral Dosage Forms Based on a Biopharmaceutics Classification System. U.S. Department of Health and Human Services, Center for Drug Evaluation and Research (CDER). 2017. Available online: https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM070246.pdf (accessed on 7 June 2018).
  5. Modi, N.B. In vitro-in vivo correlation. In Pharmaceutical Product Development: In Vitro-In Vivo Correlation, 1st ed.; Chilukuri, D.M., Sunkara, G., Young, D., Eds.; Informa Healthcare: New York, NY, USA, 2007; Volume 1, pp. 107–112. [Google Scholar]
  6. BRASIL. Brazilian Health Surveillance Agency (ANVISA). Resolução da Diretoria Colegiada RDC nº 37 de 03 de agosto de 2011. Dispõe sobre o guia para isenção e substituição de estudos de biodisponibilidade relativa/bioequivalência e dá outras providências. CFAR/GTFAR/CGMED/ANVISA. 2011. Available online: http://portal.anvisa.gov.br/documents/33880/2568070/rdc0037_03_08_2011.pdf/13c41657-e93b-4d09-99eb-377f760f3aa0 (accessed on 7 June 2018).
  7. BRASIL. Brazilian Health Surveillance Agency (ANVISA). Instrução Normativa IN nº 04 de 03 de agosto de 2011. Dispõe sobre a lista de fármacos candidatos à biosenção baseada no sistema de classificação biofarmacêutica (SCB) e dá outras providências. CFAR/GTFAR/CGMED/ANVISA. 2011. Available online: http://bvsms.saude.gov.br/bvs/saudelegis/anvisa/2011/int0004_03_08_2011.html (accessed on 7 June 2018).
  8. BRASIL. Brazilian Health Surveillance Agency (ANVISA). Instrução Normativa IN nº 07 de 21 de agosto de 2014. Determina a publicação da lista de fármacos candidatos à biosenção baseada no sistema de classificação biofarmacêutica (SCB) e dá outras providências. CFAR/GTFAR/CGMED/ANVISA. 2014. Available online: http://portal.anvisa.gov.br/documents/33836/349509/IN%2B07%2B2014.pdf/0996340b-24e5-4855-8bfd-0756765e422e?version=1.0 (accessed on 7 June 2018).
  9. BRASIL. Brazilian Health Surveillance Agency (ANVISA). Resolução da Diretoria Colegiada RDC nº 31 de 11 de agosto de 2010. Dispõe sobre a realização dos estudos de equivalência farmacêutica e de perfil de dissolução comparativo. CFAR/GTFAR/CGMED/ANVISA. 2010. Available online: http://portal.anvisa.gov.br/documents/33880/2568070/res0031_11_08_2010.pdf/5e157d15-d3d5-4bb9-98db-5667e4d9e0c8 (accessed on 7 June 2018).
  10. Sweetman, S.C. Martindale: The Complete Drug Reference, 36th ed.; Pharmaceutical Press: London, UK, 2009; pp. 532–534. [Google Scholar]
  11. Charoo, N.; Cristofoletti, R.; Graham, A.; Lartey, P.; Abrahamsson, B.; Groot, D.W.; Kopp, S.; Langguth, P.; Polli, J.; Shah, V.P.; et al. Biowaiver monograph for immediate-release solid oral dosage forms: Fluconazole. J. Pharm. Sci. 2014, 103, 3843–3858. [Google Scholar] [CrossRef] [PubMed]
  12. Charoo, N.A.; Cristofoletti, R.; Dressman, J.B. Risk assessment for extending the Biopharmaceutics Classification System-based biowaiver of immediate release dosage forms of fluconazole in adults to the paediatric population. J. Pharm. Pharmacol. 2015, 67, 1156–1169. [Google Scholar] [CrossRef] [PubMed]
  13. Okumo, A.; Dimaso, M.; Löbenberg, R. Dynamic dissolution testing to establish in vitro/in vivo correlations for montelukast sodium, a poorly soluble drug. Pharmaceut. Res. 2008, 12, 2778–2785. [Google Scholar] [CrossRef] [PubMed]
  14. Okumo, A.; Dimaso, M.; Löbenberg, R. Computer simulations using GastroPlus to justify a biowaiver for etoricoxib solid oral drug products. Eur. J. Pharm. Biopharm. 2009, 72, 91–98. [Google Scholar] [CrossRef] [PubMed]
  15. Wei, H.; Dalton, C.; Dimaso, M.; Kanfer, I.; Löbenberg, R. Physicochemical characterization of file glyburide powders: A BCS based approach to predict oral absorption. Eur. J. Pharm. Biopharm. 2008, 69, 1046–1056. [Google Scholar] [CrossRef] [PubMed]
  16. Honório, T.S.; Pinto, E.C.; Rocha, H.V.A.; Esteves, V.S.D.; Santos, T.C.; Castro, H.C.R.; Rodrigues, C.R.; Sousa, V.P.; Cabral, L. In vitro-in vivo correlation of efavirenz tablets using GastroPlus®. AAPS PharmSciTech 2013, 14, 1244–1254. [Google Scholar] [CrossRef]
  17. Kostewicz, E.S.; Aarons, L.; Bergstrand, M.; Bolger, M.B.; Galetin, A.; Hatley, O.; Jamei, M.; Lloyd, R.; Pepin, X.; Rostami-Hodjegan, A.; et al. PBPK models for the prediction of in vivo performance of oral dosage forms. Eur. J. Pharm. Sci. 2014, 57, 300–321. [Google Scholar] [CrossRef] [PubMed]
  18. Almukainzi, M.; Jamali, F.; Aghazadeh-Habashi, A.; Löbenberg, R. Disease specific modeling: Simulation of the pharmacokinetics of meloxicam and ibuprofen in disease state vs. healthy conditions. Eur. J. Pharm. Biopharm. 2016, 100, 77–84. [Google Scholar] [CrossRef]
  19. Kesisoglou, F.; Ghung, J.; Van Asperen, J.; Heimbach, T. Physiologically based absorption modeling to impact biopharmaceutics and formulation strategies in drug development- industry case studies. J. Pharm. Sci. 2016, 105, 2723–2734. [Google Scholar] [CrossRef]
  20. Almukainzi, M.; Gabr, R.; Abdelhamid, G.; Löbenberg, R. Mechanistic understanding of the effect of renal impairment on metformin oral absorption using computer simulations. J. Pharm. Investig. 2017, 47, 151–161. [Google Scholar] [CrossRef]
  21. Silva, D.A.; Duque, M.D.; Davies, N.M.; Löbenberg, R.; Ferraz, H.G. Application of in silico tools in clinical practice using ketoconazole as model drug. J. Pharm. Pharm. Sci. 2018, 21, 242s–253s. [Google Scholar] [CrossRef]
  22. Tubic-Grozdanis, M.; Bolger, M.G.; Langguth, P. Application of gastrointestinal simulation for extensions for biowaivers of highly permeable compounds. AAPS J. 2008, 10, 213–226. [Google Scholar] [CrossRef] [PubMed]
  23. Kovačević, I.; Parojčić, J.; Homšek, I.; Tubić-Grozdanis, M.; Langguth, P. Justification of biowaiver for carbamazepine, a low soluble high permeable compound, in solid dosage forms based on IVIVC and gastrointestinal simulation. Mol. Pharm. 2009, 6, 40–47. [Google Scholar] [CrossRef]
  24. Tsume, Y.; Amidon, G.L. The biowaiver extension for BCS class III drugs: The effect of dissolution rate on the bioequivalence of BCS class III immediate-release drugs predicted by computer simulation. Mol. Pharm. 2010, 7, 1235–1243. [Google Scholar] [CrossRef] [PubMed]
  25. Kortejärvi, H.; Shawahna, R.; Koski, A.; Malkki, J.; Ojala, K.; Yliperttula, M. Very rapid dissolution is not needed to guarantee bioequivalence for biopharmaceutics classification system (BCS) I drugs. J. Pharm. Sci. 2010, 99, 621–625. [Google Scholar] [CrossRef] [PubMed]
  26. Chen, Z.-F.; Ying, G.-G.; Jiang, Y.-X.; Yang, B.; Lai, H.-J.; Liu, Y.-S.; Pan, C.-G.; Peng, F.-Q. Photodegradation of the azole fungicide fluconazole in aqueous solution under UV-254: Kinetics, mechanistic investigations and toxicity evaluation. Water Res. 2014, 52, 83–91. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  27. Corrêa, J.C.R.; Vianna-Soares, C.D.; Salgado, H.R.N. Development and validation of dissolution test for fluconazole capsules by HPLC and derivative UV spectrophotometry. Chromatogr. Res. Int. 2012, 610427, 1–8. [Google Scholar] [CrossRef]
  28. Porta, V.; Chang, K.H.; Storpirtis, S. Evaluation of the bioequivalence of capsules containing 150 mg of fluconazole. Int. J. Pharm. 2005, 288, 81–86. [Google Scholar] [CrossRef] [PubMed]
  29. Porta, V.; Yamamichi, E.; Storpirtis, S. Avaliação biofarmacêutica in vitro de cápsulas de fluconazol. Braz. J. Pharm. Sci. 2002, 38, 333–343. [Google Scholar] [CrossRef]
  30. Rohatgi, A. WebPlotDigitizer: Web Based Tool to Extract Data from Plot, Images, and Maps. Version 4.1. January 2018. Available online: https://automeris.io/WebPlotDigitizer/citation.html (accessed on 17 March 2019).
  31. Simulations Plus. GastroPlus Version 9.0 Manual; Simulations Plus: Lancaster, CA, USA, 2015. [Google Scholar]
  32. FDA. Food and Drug Administration. Guidance for Industry: Statistical Approaches to Establishing Bioequivalence. U.S. Department of Health and Human Services, Center for Drug Evaluation and Research (CDER). 2001. Available online: https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM070244.pdf (accessed on 7 June 2018).
  33. BRASIL. AGÊNCIA NACIONAL DE VIGILÂNCIA SANITÁRIA (ANVISA). Resolução RE nº 1.170 de 19 de abril de 2006. Guia para provas de biodisponibilidade relativa/bioequivalência de medicamentos. CFAR/GTFAR/CGMED/ANVISA. 2006. Available online: http://portal.anvisa.gov.br/documents/10181/2718376/%281%29RE_1170_2006_COMP.pdf/52326927-c379-45b4-9a7e-9c5ecabaa16b (accessed on 7 June 2018).
  34. Debruyne, D. Clinical pharmacokinetics of fluconazole in superficial and systemic mycoses. Clin. Pharmacokinet. 1997, 33, 52–77. [Google Scholar] [CrossRef]
  35. Charoo, N.A.; Cristofoletti, R.; Kim, S.K. Integrating biopharmaceutics risk assessment and in vivo absorption model in formulation development of BCS class I drug using the QbD approach. Drug Dev. Ind. Pharm. 2017, 43, 668–677. [Google Scholar] [CrossRef]
  36. Alkhamis, K.A.; Obaidat, A.A.; Nuseirat, A.F. Solid-state characterization of fluconazole. Pharm. Dev. Technol. 2002, 7, 491–503. [Google Scholar] [CrossRef]
  37. Park, H.J.; Kim, M.S.; Kim, J.S.; Cho, W.; Park, J.; Cha, K.H.; Kang, Y.S.; Hwang, S.J. Solid-state carbon NMR characterization and investigation of intrinsic dissolution behavior of fluconazole polymorphs, anhydrate forms I and II. Chem. Pharm. Bull. 2010, 58, 1243–1247. [Google Scholar] [CrossRef] [PubMed]
  38. Modha, N.B.; Chotai, N.P.; Patel, V.A.; Patel, B.G. Preparation, characterization and evaluation of fluconazole polymorphs. Int. J. Res. Pharm. Biomed. Sci. 2010, 1, 124–127. [Google Scholar]
  39. Desai, S.R.; Dharwadkar, S.R. Study of process induced polymorphic transformations in fluconazole drug. Acta Pol. Pharm. Drug Res. 2009, 66, 115–122. [Google Scholar]
  40. Obaidat, R.M.; Alkhamis, K.A.; Salem, M.S. Determination of factors affecting kinetics of solid-state transformation of fluconazole polymorph II to polymorph I using diffuse reflectance Fourier transform spectroscopy. Drug Dev. Ind. Pharm. 2010, 36, 570–580. [Google Scholar] [CrossRef] [PubMed]
  41. Al-Tabakha, M.M.; Fahelelbom, K.M.S.; Obaid, D.E.E.; Sayed, S. Quality attributes and in vitro bioequivalence of different brands of amoxicillin trihydrate tablets. Pharmaceutics 2017, 9, 18. [Google Scholar] [CrossRef]
  42. EMEA. European Medicines Agency. Committee for Medical Products for Human Use (CHMP). Guideline on the Investigation of Bioequivalence. 2010. Available online: https://www.ema.europa.eu/en/documents/scientific-guideline/guideline-investigation-bioequivalence-rev1_en.pdf (accessed on 22 March 2019).
Figure 1. Dissolution profiles of products A1, A2, B1, B2, C1, and C2, obtained in USP Apparatus 1 (basket) with 900 mL of 0.1 M HCl at 37 ± 0.5 °C and 100 rpm for 30 min (adapted from [29], with permission from Brazilian Journal of Pharmaceutical Sciences, 2019).
Figure 1. Dissolution profiles of products A1, A2, B1, B2, C1, and C2, obtained in USP Apparatus 1 (basket) with 900 mL of 0.1 M HCl at 37 ± 0.5 °C and 100 rpm for 30 min (adapted from [29], with permission from Brazilian Journal of Pharmaceutical Sciences, 2019).
Pharmaceutics 11 00215 g001
Figure 2. Plasma concentration-time curve of reference product (Ref) based on experimental values and of products A1, A2, B1, B2, C1, and C2 created using simulated values given by GastroPlus; error bars represent the standard deviation for the reference plot. A zoom in of the time period 0–48 h is highlighted for better visualization.
Figure 2. Plasma concentration-time curve of reference product (Ref) based on experimental values and of products A1, A2, B1, B2, C1, and C2 created using simulated values given by GastroPlus; error bars represent the standard deviation for the reference plot. A zoom in of the time period 0–48 h is highlighted for better visualization.
Pharmaceutics 11 00215 g002
Figure 3. Amount of fluconazole dissolved in vivo (AmtDiss), amount absorbed to the portal vein (AmtPV), total amount absorbed (AmtAbs), and the amount in the systemic circulation (AmtSC) for products (A1C2) calculated by GastroPlus. Simulation time displayed is 8 h instead of the total simulation time (96 h) to provide better visualization.
Figure 3. Amount of fluconazole dissolved in vivo (AmtDiss), amount absorbed to the portal vein (AmtPV), total amount absorbed (AmtAbs), and the amount in the systemic circulation (AmtSC) for products (A1C2) calculated by GastroPlus. Simulation time displayed is 8 h instead of the total simulation time (96 h) to provide better visualization.
Pharmaceutics 11 00215 g003aPharmaceutics 11 00215 g003b
Table 1. Input data used in GastroPlus to simulate plasma concentrations.
Table 1. Input data used in GastroPlus to simulate plasma concentrations.
ParameterValueReference/Data Source
Solubility (mg/mL)8.03 at pH 0.8;[11,12]
6.91 at pH 4.5;
7.82 at pH 6.8;
6.90 at pH 7.4
pKa2.56; 2.94; 11.01[26,27]
Log P0.82ADMET Predictor
Dose (mg)150[28,29]
Effective permeability, Peff (cm/s × 10−4)4.06 ADMET Predictor
Blood/plasma ratio1.1ADMET Predictor
Unbound plasma (%)27.41ADMET Predictor
PhysiologyHuman, fasting conditions[28]
Body weight (kg)61[28]
Table 2. Elimination half-life (T1/2), coefficient of determination (R2), and Akaike Information Criterion (AIC) for compartmental models calculated by PKPlus module.
Table 2. Elimination half-life (T1/2), coefficient of determination (R2), and Akaike Information Criterion (AIC) for compartmental models calculated by PKPlus module.
Compartmental ModelsT1/2 (h)R2AIC
One-compartmental29.550.9936−80.27
Two-compartmental30.250.9977−87.53
Three-compartmental1523.500.9976−83.84
Table 3. Pharmacokinetic (PK) parameters from the two-compartmental model calculated by the PKPlus module.
Table 3. Pharmacokinetic (PK) parameters from the two-compartmental model calculated by the PKPlus module.
ParameterValue
Clearance, CL (L/h)0.99565
Central compartment volume, Vc (L)30.66
Elimination half-life, T1/2 (h)30.25
Distribution rate constant from C1 to C2, K12 (h−1)0.16515
Distribution rate constant from C2 to C1, K21 (h−1)0.41884
Distribution volume of second compartment, V2 (L/kg)0.19817
Table 4. Statistical parameters generated by GastroPlus for each predicted plasma concentration-time curve.
Table 4. Statistical parameters generated by GastroPlus for each predicted plasma concentration-time curve.
ProductR2SSERMSEMAE
A10.9871.482 × 10−11.161 × 10−17.561 × 10−2
A20.9369.806 × 10−12.986 × 10−11.833 × 10−1
B10.9291.0973.158 × 10−11.898 × 10−1
B20.9291.0943.154 × 10−11.897 × 10−1
C10.8322.3824.653 × 10−12.402 × 10−1
C20.9694.301 × 10−11.977 × 10−11.366 × 10−1
R2, coefficient of determination; SSE, sum of square error; RMSE, root mean square error; MAE, mean absolute error.
Table 5. Pharmacokinetic parameters of the reference product (Ref) based on the experimental curve and of products A1, A2, B1, B2, C1, and C2 obtained using simulated curves given by GastroPlus.
Table 5. Pharmacokinetic parameters of the reference product (Ref) based on the experimental curve and of products A1, A2, B1, B2, C1, and C2 obtained using simulated curves given by GastroPlus.
ProductsF%Tmax (h)Cmax (µg/mL)AUC0–t (µg h/mL)
ObsPredObsPred
Ref90.04.003.49--135.77--
A199.62.30--3.26--133.24
A299.61.66--3.82--132.48
B199.61.60--3.82--132.51
B299.61.60--3.82--132.51
C199.43.20--3.16--132.66
C299.61.80--3.81--132.37
%F, oral bioavailability: % of the drug that reached the systemic circulation; Tmax, time of Cmax; Cmax, maximum plasma concentration; AUC, area under the plasma concentration-time curve; Obs, observed value.
Table 6. Population simulation results: average pharmacokinetic (PK) parameters F%, Cmax, Tmax, AUC0–inf, AUC0–t, 90% CI ln-transformed for their ratio for A1, A2, B1, B2, C1, C2, and the reference product (Ref), and average AUC0–t/AUC0–inf ratio.
Table 6. Population simulation results: average pharmacokinetic (PK) parameters F%, Cmax, Tmax, AUC0–inf, AUC0–t, 90% CI ln-transformed for their ratio for A1, A2, B1, B2, C1, C2, and the reference product (Ref), and average AUC0–t/AUC0–inf ratio.
PK ParameterRefA1A2B1B2C1C2
F%9099.62
(99.58–99.66)
99.53
(99.44–99.63)
99.55
(99.48–99.63)
99.58
(99.54–99.62)
99.25
(99.11–99.38)
99.64
(99.60–99.68)
Cmax (µg/mL)3.493.22
(3.06–3.40)
3.79
(3.61–3.98)
3.88
(3.71–4.07)
3.80
(3.65–3.96)
3.16
(3.02–3.31)
3.73
(3.58–3.89)
Tmax (h)42.24
(2.14–2.35)
1.66
(1.59–1.74)
1.60
(1.53–1.68)
1.60
(1.55–1.65)
3.36
(3.20–3.53)
1.77
(1.73–1.82)
AUC0–inf (µg h/mL)153.56135.06
(126.60–144.10)
146.81
(135.90–158.60)
156.58
(146.50–167.30)
157.02
(148.30–166.30)
141.3
(129.3–154.4)
150.58
(142.10–159.60)
AUC0–t
(µg h/mL)
135.77121.59
(115.70–127.80)
128.43
(121.50–135.70)
135.81
(129.30–142.60)
135.81
(129.30–142.70)
125.48
(117.20–134.40)
130.6
(124.90–136.60)
Average AUC0–t/AUC0–inf0.880.900.870.870.860.880.87

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Duque, M.D.; Silva, D.A.; Issa, M.G.; Porta, V.; Löbenberg, R.; Ferraz, H.G. In Silico Prediction of Plasma Concentrations of Fluconazole Capsules with Different Dissolution Profiles and Bioequivalence Study Using Population Simulation. Pharmaceutics 2019, 11, 215. https://doi.org/10.3390/pharmaceutics11050215

AMA Style

Duque MD, Silva DA, Issa MG, Porta V, Löbenberg R, Ferraz HG. In Silico Prediction of Plasma Concentrations of Fluconazole Capsules with Different Dissolution Profiles and Bioequivalence Study Using Population Simulation. Pharmaceutics. 2019; 11(5):215. https://doi.org/10.3390/pharmaceutics11050215

Chicago/Turabian Style

Duque, Marcelo Dutra, Daniela Amaral Silva, Michele Georges Issa, Valentina Porta, Raimar Löbenberg, and Humberto Gomes Ferraz. 2019. "In Silico Prediction of Plasma Concentrations of Fluconazole Capsules with Different Dissolution Profiles and Bioequivalence Study Using Population Simulation" Pharmaceutics 11, no. 5: 215. https://doi.org/10.3390/pharmaceutics11050215

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