Integration of in vitro biorelevant dissolution and in silico PBPK model of carvedilol to predict bioequivalence of oral drug products

Accepted Manuscript Integration of in vitro biorelevant dissolution and in silico PBPK model of carvedilol to predict bioequivalence of oral drug products

Manuel Ibarra, Cristian Valiante, Patricia Sopeña, Alejandra Schiavo, Marianela Lorier, Marta Vázquez, Pietro Fagiolino PII: DOI: Reference:

S0928-0987(18)30147-7 doi:10.1016/j.ejps.2018.03.032 PHASCI 4461

To appear in:

European Journal of Pharmaceutical Sciences

Received date: Revised date: Accepted date:

3 January 2018 27 February 2018 29 March 2018

Please cite this article as: Manuel Ibarra, Cristian Valiante, Patricia Sopeña, Alejandra Schiavo, Marianela Lorier, Marta Vázquez, Pietro Fagiolino , Integration of in vitro biorelevant dissolution and in silico PBPK model of carvedilol to predict bioequivalence of oral drug products. The address for the corresponding author was captured as affiliation for all authors. Please check if appropriate. Phasci(2017), doi:10.1016/j.ejps.2018.03.032

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ACCEPTED MANUSCRIPT Integration of in vitro biorelevant dissolution and in silico PBPK model of carvedilol to predict bioequivalence of oral drug products.

Manuel Ibarra*, Cristian Valiante, Patricia Sopeña, Alejandra Schiavo, Marianela Lorier, Marta Vázquez, Pietro Fagiolino.

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Pharmaceutical Sciences Department – Faculty of Chemistry

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Bioavailability and Bioequivalence Centre for Medicine Evaluation (CEBIOBE) –

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Universidad de la República, Uruguay.

(*) Corresponding author:

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Manuel Ibarra, PhD. [email protected] Faculty of Chemistry, POBox 1157, 11800 Montevideo, Uruguay.

ACCEPTED MANUSCRIPT 1. INTRODUCTION The Uruguayan pharmaceutical market is composed in a large percentage of similar drugs. Even a decade after bioequivalence started to be required for narrow therapeutic range drugs, several factors have played to make this situation practically unaltered. As a result, many of the formulations available for the treatment and prophylaxis of different illnesses have never been studied in vivo and clinicians are forced to establish therapies unknowing drug biopharmaceutical quality. This factor adds variability to the PK/PD outcome in the population, both at the onset of a therapy and when products are interchanged throughout chronic treatments.

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Average bioequivalence studies have been required for decades by the world most influential regulatory agencies such as the FDA and the EMA. The biopharmaceutical quality of the similar drug is compared with the brand-name drug which accomplished all development phases and has been used in the clinical settling for a significant period. This diminishes the formulation contribution to the overall variability in clinical response, and although average bioequivalence does not ensure product interchangeability, its requirement has proven to be a robust tool as a final drug quality assessment in new drug abbreviated applications. Although we endorse this regulation, the current context calls for alternative approaches to be explored focusing on drug biopharmaceutical quality assessment. In this regard, physiologically-based pharmacokinetic (PBPK) models are emerging as a suitable tool. These mechanistic mathematical models integrate prior knowledge of anatomical, biochemical and physiological parameters of animals or humans, physicochemical properties of drug substances and formulation properties of drug products to predict in vivo pharmacokinetic profiles (Zhang et al., 2011). Over the last decades, major advances have been made in PBPK modeling and their application was expanded from drug discovery to Quality by Design (QbD) in drug development, among other areas of pharmaceutical research. Regulatory agencies have included and embraced this methodology for decision-making during drug development (Zhao et al., 2011). Many different software are available with built-in PBPK models and population data allowing the translation of in vitro dissolution data to the prediction of in vivo performance of drug product in specific virtual populations (Otsuka et al., 2013). Simulations including formulation variability and pharmacokinetic interindividual variability can be performed in this way comparing the similar and the brand-name drug to predict a bioequivalence result in a virtual trial. Several works in Virtual Bioequivalence have been published with different drugs (Cristofoletti et al., 2017; Doki et al., 2017).

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In this work, we explored a workflow that could be applied to study similar products of massively used drugs: (1) Initial in vitro evaluation of similar and brand-name drugs in USP-2 Apparatus (paddles) at WHO’s biorelevant media (World Health Organization, 2015), selecting the most likely different similar for the next phase, (2) in vitro evaluation in USP-4 Apparatus (flow-through cell) with different biorelevant methods (Fotaki, 2011), (3) development of an in silico model for the specific drug with the input of dissolution profiles obtained in flow-through cell coupled with a PBPK model for simulation of virtual bioequivalence studies and (4) results evaluation for proposal of specific average bioequivalence studies to the regulatory agency. Phase 1 narrows down the spectra of similar drugs to evaluate, since we can find more than 10 different products being commercialized in the market for the same drug. Phase 2, with the flow-through cell analysis, provides a more biorelevant scenario for in vitro comparison in different situations, and with more suitable input data for the in silico model. Phase 3 expands the analysis to pharmacokinetic and pharmacodynamic simulations including collected in vitro

ACCEPTED MANUSCRIPT data and physicochemical/pharmacokinetic/pharmacodynamic parameters reported in the literature, allowing the prediction of a bioequivalence outcome between the most different available similars and the brand-name drug. The aim of this approach is to perform a rapid and cost-effective characterization of similar drug products available in the local market, identifying formulations with probable different in vivo performance for bioequivalence evaluation.

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The extensively prescribed drug Carvedilol was selected for analysis. Carvedilol is an arylethanolamine with antagonist effect over β- and α1- adrenergic receptors (nonselective β-blocker), used in the treatment of hypertension and chronic heart failure due to its β-blocking and vasodilator activity (Keating and Jarvis, 2003). The drug is rapidly absorbed following oral administration, with and absolute bioavailability of approximately 25% to 35% due to significant degree of first-pass metabolism in the liver (Roche Products PTY Limited, 2012). It reaches a peak concentration 1 to 2 hours post-dose and has an elimination half-life of about 4 to 7 hours (Morgan, 1994). Carvedilol disposition shows extensive metabolism, mainly mediated by CYP2D6 to form 4′- and 5′- hydroxyphenyl carvedilol with minor contributions of CYP1A2 (8′- hydroxyphenyl carvedilol) and CYP2C9 (O-desmethyl carvedilol) (Oldham and Clarke, 1997). Dose-exposure linearity is reported for single doses of a sustained-release formulation between 8 and 128 mg and maximum plasma concentrations [mean (geometric CV)] of 6.93 (63%) and 77.0 (67%) respectively (Yo Han Kim et al., 2015). Carvedilol disposition seems to be unaffected by efflux transporters.

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Carvedilol [MW = 406.48 g/mol (Sunghwan Kim et al., 2016)] is a weak basic compound with a pKa of 7.8 and a logP (octanol/water) of 3.8 (Loftsson et al., 2008), classified as a BCS class II drug (low Solubility – high Permeability). Its aqueous solubility is pHdependent: 832 mg/L in acidic media (pH 1.2) and 5.8 mg/L at pH 7.8 (Hamed et al., 2016). The dissolution test described in the USP monograph is performed in 900 mL of medium with hydrochloric acid adjusted to pH 1.45 with USP-2 apparatus rotating at 50 rpm at 37 ± 0.5 °C and specifying that not less than 80% of the nominal dose should dissolve in 30 minutes (U.S. Pharmacopeial Convention, 2014).

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In Uruguay, eight multi-source products are available as conventional release tablets including the brand-name drug, Dilatrend® (Roche, Switzerland), and seven similar formulations. The following products were included in the present work: T1-Bidecar (Brandt Laboratory of Uruguay S.A.), T2-Cardiolil (Laboratory Novophar S.A.), T3Carvedil (Noas Farma Uruguay S.A.), T4-Carvedilol ION (Laboratory Ion S.A.), T5Carvedilol Lazar (Lazar S.A.), T6-Tensibona (Szabó S.A.) and T7-Carvemox (Gador S.A. Laboratory). Considering that the recommended daily dose is between 25 and 50 mg, presentations containing 25 mg of carvedilol were evaluated.

2. MATERIALS AND METHODS 2.1 Dissolution testing All similar products available in the Uruguayan market, along with Dilatrend®, were acquired for in vitro assessment. As a first approach, dissolution testing was performed in USP-2 Apparatus according to WHO guidelines for biowaivers using the acidic medium to simulate gastric fluid without enzymes: HCl/KCl pH 1.2 solution. Dissolution system consisted in a Distek 2100C configured with paddles rotating at 75 rpm, 900 mL of medium

ACCEPTED MANUSCRIPT per vessel maintained at 37 ± 0.5 °C. Carvedilol concentrations were determined by UV spectrophotometry at 240 nm using an Agilent 8453 UV-Vis spectrophotometer coupled to a multicell-based system with automated sampling from the dissolution medium. Drug dissolution was measured every 5 minutes throughout 60 minutes of assay and cumulative percentages of dose dissolved were calculated. Six units of each product were evaluated to compare dissolution performance at fasting gastric conditions.

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∗ 100}

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1 𝑓2 = 50 ∗ 𝑙𝑜𝑔 {[1 + ∑(𝑅𝑗 − 𝑇𝑗 )2 ] 𝑛

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Several parameters were employed for comparison of carvedilol dissolution profiles obtained in Apparatus 2 between similar products. The similarity factor 𝑓2 recommended by FDA and WHO for biowaivers was estimated for multi-source products versus Dilatrend® according to the following equation:

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Where 𝑅𝑗 and 𝑇𝑗 are percentages of drug dissolved at time j for the Reference (Dilatrend®) and the compared similar respectively and n is the number of samples. This factor was estimated individually for comparison of dosage forms dissolved in the same vessel including one time-point after the reference reached 85%. In addition, dissolution efficiency (DE) (Khan, 1975) and mean dissolution times (MDT) for each product were quantified: 𝐷𝐸𝑇 =

𝐴𝑈𝐶0𝑇 × 100 100 ∗ 𝑇

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𝑀𝐷𝑇 = 𝐴𝐵𝐶⁄𝑊∞

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Being 𝐷𝐸𝑇 the dissolution efficiency at time T and 𝐴𝑈𝐶0𝑇 the area under the cumulative dissolution curve from zero to T, 𝑊∞ the asymptote of the dissolved amount of drug and ABC is the area between the cumulative dissolution curve and 𝑊∞. Integration was performed by trapezoidal-rule. Each test formulation was compared to the reference establishing 90% confidence intervals for DE and MDT mean ratios.

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Next, two similar products were selected for further in vitro comparison with the reference carrying out a dissolution test in USP-4 Apparatus operating in the open mode at 37 ± 0.5 °C. Tests products showing larger and lower differences in USP-2 Apparatus were chosen. Sotax CE7 Smart system with fraction collector was used, quantifying carvedilol in dissolution media by UV-absorption at 240 nm as described above. Cells of 22.6 mm of diameter were used, with a 5mm-size glass bead in the tip. The cell cone was filled with 1mm-size glass beads, formulations were placed above these beads on a tablet holder, and a Whatmann® glass fiber filter (GF/F: 0.7 µm of pore size) was placed at the top of the cell. Conditions implemented in previous works (unpublished data) were employed here: 8 mL/min of HCl/KCl pH 1.2 solution for 30 minutes; 4 mL/min of 50 mM phosphate buffer at pH 4.5 for 30 minutes; and 4 mL/min of 50 mM phosphate buffer solution at pH 6.8 for 120 minutes. Drug precipitation was evaluated in the fractions collected after each media transition by diluting an aliquot 1/2 in methanol and measuring carvedilol concentration. Media pH was measured in all fractions collected. Six units of each product were evaluated and dissolution profiles (mean and standard deviation) were used as an input to estimate carvedilol pharmacokinetic profiles using a PBPK model.

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In vitro conditions employed are biorelevant for the fasted state. Although carvedilol is frequently administered with food to reduce the risk of drug-induced orthostatic hypotension, recommendation in this regard is not consistently given for all patients and drug products. Postprandial administration is recommended in Dilatrend® prescribing information only for chronic heart failure patients, which have a higher incidence of orthostatic effects. Multi-source products evaluated in this study include dissimilar recommendation: two products suggest postprandial administration for reducing adverse effects (Carvemox® – Gador Laboratory, and Carvedilol Lazar®) while the other products state that food does not alter carvedilol absorption rate and suggest taking the drug with or without food. As explained below, carvedilol in silico predictions performed integrating in vitro biorelevant data in a PBPK model were contrasted with Dilatrend® bioequivalence published data for model evaluation. Since the present work aims to assess the bioequivalence of Uruguayan carvedilol multisource drug products, currently performed in fasted state, and considering that food would significantly affect carvedilol CMAX, both in vitro and in silico conditions were designed for predicting pharmacokinetics of a fasting administration. 2.2 Carvedilol PBPK model

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Physicochemical and pharmacokinetic relevant parameters of carvedilol were included in the PK-Sim® software (Systems Biology Software Suite 7.0, Bayer Technology Services GmbH, Leverkusen, Germany) to develop the PBPK model. In PK-Sim®, the GI tract is divided in 12 compartments, each representing a definite segment from the stomach to the rectum, and the GI mucosa is represented in separated compartments allowing specific description of drug uptake and intestinal first-pass metabolism (Thelen et al., 2011). Right after drug intake, kinetics of drug dissolution from the dosage form and longitudinal transit time throughout GI tract of both the dosage form and the drug in solution are key in defining drug absorption. The dosage form and the drug in solution are treated as independent elements regarding transit throughout GI tract, as described by Thelen et al. (Thelen et al., 2012). Kinetics of longitudinal transit through the GI tract are defined in the PBPK model for the drug in solution (DIS) and for the non-disintegrated solid dosage form (SDF), which is transported independently along the tract. In default fasting conditions of PK-Sim, mean residence times in stomach, small intestine and large intestine of the DIS are 15 minutes, 2.1 hours and 44.2 respectively, whereas for the SDF mean residence time in stomach and small intestine are 1 and 7 hours respectively. Drug transference from SDF to DIS is defined by the data obtained in vitro in the USP-4 Apparatus under biorelevant conditions, appended in the software as a table (mean percentage of drug dissolved versus time). The absorption model is combined with a physiologically-based whole body model (Willmann et al., 2012). The virtual population utilized for carvedilol pharmacokinetic simulations consisted in 1000 Caucasian subjects (500 male, 500 female), of ages constrained between 18 and 50 years. Body weights (mean ± standard deviation) were 71 ± 11 and 61 ± 8.8 for male and female subjects respectively. Default PK-Sim® values were implemented for between subject variability for anatomical and physiological parameters. Simulated carvedilol concentrations after a 25-mg dose were computed every 3 minutes for an initial 2-hour period and then every 15 minutes until 24 hours post-dose. Mean pharmacokinetic parameters including maximum concentration (Cmax), time-topeak (Tmax), area under the concentration-time curve (AUC) and carvedilol half-life (𝑡1/2 ) simulated for Dilatrend® were compared with published results of 5 single dose bioequivalence studies, all performed under fasting conditions (ANNEAL PHARMA

ACCEPTED MANUSCRIPT SPAIN, 2000; Soo-Hwan Kim et al., 2010; Medical Products Agency. Sweden, 2008; Medicines and Healthcare products Regulatory Agency. United Kingdom, 2011; Portoles et al., 2005). Carvedilol parameters were adjusted accordingly through a learningconfirming process. 2.3 Virtual bioequivalence

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The same virtual population (N=1000) was employed for simulating carvedilol pharmacokinetics after single dose of each formulation (two Test products and the Reference). For each subject and formulation, Cmax and Tmax values were computed, while the AUC from zero to infinity was estimated by trapezoidal rule. Median and nonparametric 95% CI are reported for each formulation. The population bioequivalence ratio was estimated for each of the similar drug products through a non-parametric approach from the individual Test/Reference (T/R) ratios, reporting the median and the 90%CI taken directly with the 5th and 95th percentiles of the resulting distribution.

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3. RESULTS

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Dissolution profiles of formulations obtained in USP-2 Apparatus at pH 1.2 are shown in Figure 1. Table II includes the dissolution parameters estimated for each formulation and the comparison with the reference. Dissolution testing in USP-2 Apparatus at acidic medium revealed a significantly different performance of similar products in relation to Dilatrend®, which showed the slowest carvedilol release profile. Estimated parameters for dissolution profile comparison DE, MDT and 𝑓2 consistently showed that T1 formulation (Bidecar®, Brandt) presented the largest difference from the reference product, while T6 (Tensibona®, Szabo) achieved the closest dissolution profile. Similar products T1 and T6 were therefore selected for further assessment.

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Figure 2 shows the dissolution profiles of T1, T6 and Dilatrend® in USP-4 Apparatus. Results obtained with this method were consistent with previous observations, confirming significant differences in carvedilol release between formulations. Table III summarizes product comparison in this assay with dissolution parameters.

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The final set of carvedilol parameters introduced in the development of the PBPK model to PK-Sim® are shown in Table I. Table IV summarizes the comparison between simulated and bibliographic parameters for the final Dilatrend® in silico model. Specifically, carvedilol logP (octanol/water), plasma protein binding and hepatic clearance had a high incidence in pharmacokinetic outcome. Experimental logP values of 4.19 (Sunghwan Kim et al., 2016) and 3.22 (Cheng et al., 1996) are reported in addition to the final included value of 3.8 (Loftsson et al., 2008). In the same way was defined the plasma protein binding, which had a high impact on drug distribution. The fraction unbound was finally set to 0.0054, the same included in a previously published carvedilol PBPK model (Rasool et al., 2015). In accordance with these authors and following the same comparative approach, the Paulin and Theil prediction method for drug distribution was chosen instead of the PK-Sim standard. The hepatic clearance was set to 0.52 L/h/kg according to reports from Cubeddu et al. and Neugebauer et al. (Cubeddu et al., 1987; Neugebauer et al., 1987). Other values were evaluated and regarded inferior in predictive performance, including defining the specific affinity to each CYP450 isozyme related to carvedilol metabolism. Finally, the only adjusted physiologic variable was the mean gastric residence time for fasting conditions, which was set to 20 minutes after comparing the simulated mean TMAX and CMAX values with reported data. As it can be observed, PBPK

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model predictions were well adjusted to previously published pharmacokinetic data obtained under similar conditions. Interindividual variability in systemic clearance for the virtual population obtained through the PK-Sim simulation of physiologic differences (organ size and composition) was not increased after comparing the in silico simulations for Dilatrend® with pharmacokinetic reported interindividual variability, mainly for AUC which reflects clearance and bioavailability random effects. Bibliographic data show coefficients of variation for Dilatrend® Cmax and AUC interindividual variability in the range of 13.1 - 60% and 13.1 - 81.8 % respectively. While predicted interindividual variability in AUC is in line with reported findings, for Cmax the prediction resulted less variable. However, as reported Cmax values are affected by additional sources of variation like the sampling protocol, the analytical error and the interocassion variability (periods), and considering the aim of this work of predicting the relative performance of multisource drug products, the difference was regarded as not significant.

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Finally, the population bioequivalence ratio and its 90% confidence interval were estimated from the simulated data of T1 and T2 versus Dilatrend®. These results are shown in Table V. Simulated pharmacokinetic profiles for these bioequivalence trials in the virtual sample of 1000 subjects (median and 90% percentile intervals) are illustrated in Figure 3. Since T1 reached a dissolved carvedilol percentage higher than 100% and separated by more than 5% than the dissolved percentage in the reference product, dissolution profiles were normalized for inclusion in the PBPK model and the mean experimentally estimated dose content was used for simulation of the single dose pharmacokinetic profiles. Bioequivalence parameters were then corrected by this difference. 4. DISCUSSION

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The Uruguayan pharmaceutical industry has grown over the past century to be now consolidated as one of the most relevant sectors in national economy. Its expansion has been historically based on the production of similar drugs, products of quality strictly evaluated according to pharmacopoeia specifications. Many efforts and resources are invested to ensure the quality of the production process. Paradoxically, biopharmaceutical quality is rarely assessed, as bioequivalence was not required by the local sanitary agency until 2007, a requirement limited to some narrow therapeutic index drugs such as antiepileptic, immunosuppressant and antiretroviral drugs. Even for these drugs the implementation of the bioequivalence decree is facing serious difficulties. A similar situation can be observed in other Latin American countries, except for Brazil, Chile and Argentina which have implemented stricter bioequivalence regulations to their similarbased markets. This context calls for the search of alternative approaches for the assessment of in vivo performance of marketed drugs. Pharmaceutical products of massive use are totally lacking these evaluations to the point that their pharmacokinetic profile remains unknown, a situation that may be causing toxicity and inefficacy issues in current treatments, with the subsequent economic burden to public health. The perspective commented before can be reflected in the results obtained in vitro in USP2 Apparatus. Dissolution conditions are close to those required in USP carvedilol monograph for dissolution testing (pH is more acidic, and paddles rotate more rapidly). Under this paradigm, the best outcome is the fastest possible dissolution (high DE, low MDT) and hence all similar products appear to be formulated with the goal of accomplishing USP specification of 80% carvedilol dissolved in 60 minutes of assay. This specification is not designed to assess biopharmaceutical quality. Dilatrend®, the only

ACCEPTED MANUSCRIPT drug product of this group formulated within a complete drug development process, evaluated in several clinical trials and further assessed by independent researchers, shows a more sustained dissolution profile, significantly different from that obtained by national similar products.

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Results obtained at biorelevant dissolution conditions implemented with the flow-through cell apparatus supported the above observations, as the differences between test products and Dilatrend® remained significant. Dissolution conditions employed in this assay were previously developed for other drugs establishing in vitro-in vivo correlations (Lorier et al., 2016), being a simple representation of the fasting GI tract. A higher flow rate was set for the acidic media to represent the higher motility and fluid volume at the stomach. Phosphate buffer was used for the 4.5-pH medium because acetates are not present in intestinal fluids. According to Hamed et al. (Hamed et al., 2016), acetates increase carvedilol aqueous solubility by forming soluble salts. Although this phosphate buffer has low buffer capacity, in vivo fasting intestinal fluids are similar (0.003-0.006 M/dpH), and ionic-strength is within reported values for fasting intestinal fluids (0.07-0.166 mol/L). This medium was included for 30 minutes as a transition to the neutral phosphate buffer, which was then sustained for 120 minutes at a low flow rate.

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The inclusion of in vitro data from USP-4 Apparatus to the carvedilol PBPK model representing fasting conditions was evaluated through pharmacokinetic comparison of simulated parameters and bibliographic data. This comparison showed that simulations of carvedilol bioavailability and disposition in Caucasian population after an oral dose of Dilatrend® 25 mg without food were acceptably accurate (Table IV). Dissolution profiles obtained for each product were appended to the PBPK model and single dose pharmacokinetics of carvedilol 25 mg were simulated in the same 1000 subjects and conditions. As a limitation, PK-Sim® does not allow the inclusion of variability observed in the in vitro test, and only mean dissolved percentages were included.

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Bioequivalence between each test product and Dilatrend® was assessed through the estimation of the population median T/R ratio and its non-parametric 90% confidence interval. Given that the aim of this study was not the simulation of a bioequivalence trial, interocassion variability was not included.

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As it can be observed in Figure 3 and Table V, a non-bioequivalent outcome is predicted for T1 and T6. Although a similar absorbed amount is predicted for the three formulations, Test products would present a higher Cmax and lower Tmax than the Reference. This finding is in accordance with the dissolution profiles observed in both USP-2 and USP-4 dissolution testing, in which Test products showed a significantly faster carvedilol release. Accordingly with results obtained in a previous work in which in vitro data was correlated with bioequivalence outcomes for efavirenz (Ibarra et al., 2016), in vitro dissolution efficiency T/R ratio proved to be a suitable subrogate of Cmax bioequivalence T/R ratio. In addition, a similarity factor 𝑓2 below 30 for the acidic dissolution media in the USP-2 Apparatus (absolute difference higher than 20% in mean dissolution profiles) would indicate probable bioinequivalence issues for carvedilol multisource drug products. Simulated Cmax for T1 and T6 are above the reported minimum toxic concentration of 150 µg/L (Moffat et al., 2011). These concentrations are likely to produce adverse effects. In a study comparing carvedilol immediate (IR) and controlled release (CR) formulations at the same doses in patients with hypertension, Henderson et al. (Henderson et al., 2006) found less incidence of dizziness and headache in patients under CR treatment. Together

ACCEPTED MANUSCRIPT with the predicted pharmacokinetic profiles, a higher incidence of adverse effects in treatments with Test products relative to Dilatrend® could be expected under fasting conditions of administration. Given that carvedilol absorption is slower when taken with food, these differences could be diminished in the clinical settling recommending postprandial administration. The fed condition could be implemented in further experiments aimed to evaluate drug product switchability and the impact of food on carvedilol bioequivalence, reaching probably very interesting conclusions.

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T6 was, among the evaluated similar products, the one that showed a closer carvedilol dissolution profile to the reference. Failure of this formulation to accomplish bioequivalence in the virtual population indicates that all similar products available are likely to obtain analogous results. The bioequivalence prediction obtained for T1 supports this affirmation. This work could be complemented by carrying out a bioequivalence study between T1 or T6 versus Dilatrend®. In vivo data would serve for evaluating the implemented in vitro-in silico process. The flow-through dissolution testing and the PBPK model could be optimized contrasting simulations with in vivo data, improving the predictions for the rest of the similar products. Above all, the observed and predicted performance of similar products available in the Uruguayan pharmaceutical market expose the importance of bioequivalence implementation as a regulatory tool to reduce product performance variability and improve biopharmaceutical quality. 5. CONCLUSIONS

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Significant differences were found in dissolution profiles of carvedilol between similar products of immediate release produced locally and Dilatrend®. A PBPK model for carvedilol developed and optimized with Dilatrend® published pharmacokinetic data allowed the inclusion of in vitro similar product performance under biorelevant conditions for the prediction of in vivo pharmacokinetics after a single oral dose of 25 mg in a virtual population. Bioequivalence ratios were estimated for two of the evaluated similar products, both failing in achieving the required similarity for Cmax. Predictions support the need to perform in vivo bioequivalence for these products of massive use. Application of the in vitro-in silico-in vivo approach stands as an interesting alternative to tackle and reduce the variability in biopharmaceutical quality present in developing countries in which bioequivalence is not required. 6. ACKNOWLEDGMENTS

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This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. 7. CONFLICT OF INTERESTS Authors have no conflict of interests to declare.

8. REFERENCES. ANNEAL PHARMA SPAIN. 2000. Carvedilol PHARMAGENUS comprimidos EFG. Resumen del estudio de bioequivalencia. Cheng, H. Y., Randall, C. S., Holl, W. W., Constantinides, P. P., Yue, T. L., Feuerstein, G. Z. 1996. Carvedilol-liposome interaction: Evidence for strong association with the

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hydrophobic region of the lipid bilayers. Biochim. Biophys. Acta - Biomembr., 1284(1), 20–28. Cristofoletti, R., Patel, N., Dressman, J. B. 2017. Assessment of Bioequivalence of Weak Base Formulations Under Various Dosing Conditions Using Physiologically Based Pharmacokinetic Simulations in Virtual Populations. Case Examples: Ketoconazole and Posaconazole. J. Pharm. Sci., 106(2), 560–569. Cubeddu, L., Fuenmayor, N., Varin, F., Villagra, V., Colindres, R., Powell, J. 1987. Mechanism of the vasodilatory effect of carvedilol in normal volunteers: a comparison with labetalol. J. Cardiovasc. Pharmacol., 10(11), S81–S84. Doki, K., Darwich, A. S., Patel, N., Rostami-Hodjegan, A. 2017. Virtual bioequivalence for achlorhydric subjects: The use of PBPK modelling to assess the formulationdependent effect of achlorhydria. Eur. J. Pharm. Sci., 109, 111–120. Fotaki, N. 2011. Flow-through cell apparatus (USP Apparatus 4): Operation and features. Dissolution Technol., 18(4), 46–49. Hamed, R., Awadallah, A., Sunoqrot, S., Tarawneh, O., Nazzal, S., AlBaraghthi, T., Al Sayyad, J., Abbas, A. 2016. pH-Dependent Solubility and Dissolution Behavior of Carvedilol—Case Example of a Weakly Basic BCS Class II Drug. AAPS PharmSciTech, 17(2), 418–426. Henderson, L. S., Tenero, D. M., Baidoo, C. A., Campanile, A. M., Harter, A. H., Boyle, D., Danoff, T. M. 2006. Pharmacokinetic and Pharmacodynamic Comparison of Controlled-Release Carvedilol and Immediate-Release Carvedilol at Steady State in Patients with Hypertension. Am. J. Cardiol., 98(7A), 17–26. Ibarra, M., Magallanes, L., Lorier, M., Vázquez, M., Fagiolino, P. 2016. Sex-byformulation interaction assessed through a bioequivalence study of efavirenz tablets. Eur. J. Pharm. Sci., 85, 106–111. Keating, G., Jarvis, B. 2003. Carvedilol: A review of its use in chronic heart failure. Drugs, 63(16), 1697–1741. Khan, K. A. 1975. The concept of dissolution efficiency. J. Pharm. Pharmacol., 27, 48– 49. Kim, S.-H., Lee, S. H., Lee, H. J. 2010. Rapid and Sensitive Carvedilol Assay in Human Plasma Using a High-Performance Liquid Chromatography with Mass/Mass Spectrometer Detection Employed for a Bioequivalence Study. Am. J. Anal. Chem., 1(3), 135–143. Kim, S., Thiessen, P. A., Bolton, E. E., Chen, J., Fu, G., Gindulyte, A., Han, L., He, J., He, S., Shoemaker, B. A., Wang, J., Yu, B., Zhang, J., Bryant, S. H. 2016. PubChem substance and compound databases. Nucleic Acids Res., 44(D1), D1202–D1213. Kim, Y. H., Choi, H. Y., Noh, Y. H., Lee, S. H., Lim, H. S., Kim, C., Bae, K. S. 2015. Dose proportionality and pharmacokinetics of carvedilol sustained-release formulation: A single dose-ascending 10-sequence incomplete block study. Drug Des. Devel. Ther., 9, 2911–2918. Loftsson, T., Vogensen, S. B., Desbos, C., Jansook, P. 2008. Carvedilol: Solubilization and Cyclodextrin Complexation: A Technical Note. AAPS PharmSciTech, 9(2), 425– 430. Lorier, M., Fotaki, N., Vázquez, M., Fagiolino, P. 2016. Biorelevant in vitro dissolution coupled with n-octanol partition assay to predict in vivo absorption of ketoprofen after oral administration. In AAPS Annu. Meet. Denver, USA. Medical Products Agency. Sweden. 2008. Public Assessment Report. Scientific Discussion. Carvsanna. Carvedilol (Vol. SE/H/854/0). Uppsala, Sweden. Medicines and Healthcare products Regulatory Agency. United Kingdom. 2011. CARVEDILOL 3.125 MG, 6.25 MG, 12.5 MG AND 25 MG TABLETS. PL

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33410/0004-7. London, UK. Moffat, A., Osselton, M., Widdop, B. 2011. Clarke’s analysis of drugs and poisons. Morgan, T. 1994. Clinical Pharmacokinetics and Pharmacodynamics of Carvedilol. Clin. Pharmacokinet., 26(5), 335–346. Neugebauer, G., Apkan, W., Möllendorff, E., Neubert, P., Reiff, K. 1987. Pharmacokinetic and Disposition of Carvedilol in Humans. J. Cardiovasc. Pharmacol., 10(11), S85–S88. Oldham, H. G., Clarke, S. E. 1997. In vitro identification of the human cytochrome P450 enzymes involved in the metabolism of R(+)- and S(-)-carvedilol. Drug Metab Dispos, 25(8), 970–977. Otsuka, K., Shono, Y., Dressman, J. 2013. Coupling biorelevant dissolution methods with physiologically based pharmacokinetic modelling to forecast in-vivo performance of solid oral dosage forms. J. Pharm. Pharmacol., 65, 937–952. Portoles, A., Filipe, A., Almeida, S., Terleira, A., Vallee, F., Vargas, E. 2005. Bioequivalence study of two different tablet formulations of carvedilol in healthy volunteers. Arzneimittelforschung, 55(4), 212–217. Poulin, P., Theil, F.-P. 2002. Prediction of Pharmacokinetics Prior to In Vivo Studies. II. Generic Physiologically Based Pharmacokinetic Models of Drug Disposition. J. Pharm. Sci., 91(5), 1358–1370. Rasool, M., Khalil, F., Läer, S. 2015. A Physiologically Based Pharmacokinetic Drug – Disease Model to Predict Carvedilol Exposure in Adult and Paediatric Heart Failure Patients by Incorporating Pathophysiological Changes in Hepatic and Renal Blood Flows. Clin. Pharmacokinet., 54(9), 943–962. Roche Products PTY Limited. 2012. Dilatrend Prescribing Information (Vol. 120831). Thelen, K., Coboeken, K., Willmann, S., Burghaus, R., Dressman, J., Lippert, J. 2011. Evolution of a Detailed Physiological Model to Simulate the Gastrointestinal Transit and Absorption Process in Humans, Part 1: Oral Solutions. J. Pharm. Sci., 100(12), 5324–5345. Thelen, K., Coboeken, K., Willmann, S., Dressman, J., Lippert, J. 2012. Evolution of a Detailed Physiological Model to Simulate the Gastrointestinal Transit and Absorption Process in Humans, Part II: Extension to Describe Performance of Solid Dosage Forms. J. Pharm. Sci., 101(3), 1267–1280. U.S. Pharmacopeial Convention. 2014. USP 37 - NF 32. Rockville, MD: U.S. Pharmacopeial Convention. Willmann, S., Thelen, K., Lippert, J. 2012. Integration of dissolution into physiologicallybased pharmacokinetic models III: PK-Sim®. J. Pharm. Pharmacol., 64(7), 997– 1007. World Health Organization. WHO Expert Committee on Specifications for Pharmaceutical Preparations. Forty-ninth report. , WHO Technical Report Series (2015). Zhang, X., Lionberger, R. A., Davit, B. M., Yu, L. X. 2011. Utility of Physiologically Based Absorption Modeling in Implementing Quality by Design in Drug Development. AAPS J., 13(1), 59–71. Zhao, P., Zhang, L., Grillo, J. A., Liu, Q., Bullock, J. M., Moon, Y. J., Song, P., Brar, S. S., Madabushi, R., Wu, T. C., Booth, B. P., Rahman, N. A., Reynolds, K. S., Gil Berglund, E., Lesko, L. J., Huang, S. M. 2011. Applications of physiologically based pharmacokinetic (PBPK) modeling and simulation during regulatory review. Clin. Pharmacol. Ther., 89(2), 259–267.

ACCEPTED MANUSCRIPT FIGURE LEGENDS Figure 1 In vitro dissolution profiles (mean ± standard deviation) of evaluated 25 mg carvedilol tablets obtained in USP-2 Apparatus at 75 rpm with 900 mL of simulated gastric medium (pH 1.2) at 37 ± 0.5 °C. Figure 2

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In vitro dissolution profiles (mean ± standard deviation) of T1, T6 and Dilatrend® (Reference) obtained in USP-4 Apparatus in the following conditions: 8 mL/min of HCl/KCl pH 1.2 solution for 30 minutes; 4 mL/min of 50 mM phosphate buffer at pH 4.5 for 30 minutes; and 4 mL/min of 50 mM phosphate buffer solution at pH 6.8 for 120 minutes.

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Figure 3

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Carvedilol plasma concentration profiles simulated from the PBPK model in 1000 Caucasian subjects (mean, continuous lines ± 95% CI, shadows) after a single oral dose of 25 mg of Dilatrend®, T1 and T6.

ACCEPTED MANUSCRIPT TABLES Table I – Carvedilol parameters included in the PBPK model. Value

Reference

Molecular weight

406.48 g/mol

PubChem (Sunghwan Kim et al., 2016)

Solubility (pH=1.2, 37°C)

832 μg/mL

(Hamed et al., 2016)

pKa log P Intestinal permeability

7.8 3.80 1.94E-4 cm/min

(Loftsson et al., 2008) (Loftsson et al., 2008) (Rasool et al., 2015)

Unbound plasma fraction (fuP) Distribution calculation CLIV

0.0054

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(Rasool et al., 2015)

(Poulin and Theil, 2002) (Cubeddu et al., 1987; Neugebauer et al., 1987)

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Poulin and Theil 0.52 L/h/kg

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Parameter

ACCEPTED MANUSCRIPT Table II – Dissolution parameters obtained in USP-2 Apparatus at pH 1.2. Formulation

MDT (min)a

T/R (MDT)b

DE (%)a

T/R (DE)b

𝒇𝟐

Dilatrend

19.2 (0.47)

---

62.7 (0.8)

---

---

T1

3.10 (0.24)

0.161

94.8 (0.4)

1.51

21.7

(0.137 – 0.185) T2

3.73 (0.04)

0.194

(1.48 – 1.55) 93.5 (0.2)

T3

4.70 (0.11)

0.244

92.2 (0.2)

0.368

87.0 (0.9)

(0.328 – 0.408) 4.61 (0.29)

0.239

92.3 (0.5)

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T5

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7.08 (0.38)

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(0.229 – 0.259) T4

(0.209 – 0.269) 8.68 (0.71)

0.451

MA

T6

85.5 (1.2)

(0.381 – 0.521) T7

4.85 (0.25)

0.252

D

(0.226 – 0.278)

1.47

24.8

(1.44 – 1.50) 1.39

26.9

(1.35 – 1.43) 1.47

25.0

(1.44 – 1.51) 1.36

27.4

(1.32 – 1.41) 91.8 (0.4)

1.46

22.5

(1.43 – 1.50)

reported as: mean (standard error). bResults reported as: Mean (90%CI). MDT: mean dissolution time. DE: dissolution efficiency. 𝑓2 : similarity factor. T/R: Test/Reference ratio of means.

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aResults

24.7

(1.46 – 1.52)

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(0.185 – 0.203)

1.49

ACCEPTED MANUSCRIPT Table III – Dissolution parameters obtained in USP-4 Apparatus. Formulation

MDT (min)a

T/R (MDT)b

DE (%)a

T/R (DE)b

𝒇𝟐

Dilatrend

42.9 (1.4)

---

72.9 (2.8)

---

---

T1

15.2 (1.2)

0.35

91.6 (0.7)

1.25

20.2

(0.30 – 0.41) T6

23.5 (2.8)

0.55

(1.16 – 1.35) 85.8 (1.4)

31.2

(1.09 – 1.27)

PT

(0.42 – 0.67)

1.18

reported as: mean (standard error). bResults reported as: Mean (90%CI). MDT: mean dissolution time. DE: dissolution efficiency. 𝑓2 : similarity factor. T/R: Test/Reference ratio of means.

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aResults

ACCEPTED MANUSCRIPT Table IV – Comparison of Dilatrend® mean population pharmacokinetic parameters obtained in silico with published results of bioequivalence studies performed with Dilatrend® under similar conditions.

Bibliographic Valuesa

AUC (µg*h/L)

286.71 (227 – 362)

165-359

Cmax (µg/L)

101 (64.2 - 156)

80-108

Tmax (h)

0.912 (0.826 - 1.01)

t1/2 (h)

6.50 (5.29 – 8.08)

PT

PBPK model simulation

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Pharmacokinetic parameter

0.75-1.0 6-10

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Bibliographic values are included as a range of published means. In silico population values included as median (non-parametric 90%CI). AUC: area under the plasma concentration-time curve from 0 to infinity. Cmax: maximum plasma concentration after single oral dose. Tmax: time of Cmax. t1/2: elimination half-life. a(ANNEAL PHARMA SPAIN, 2000; Soo-Hwan Kim et al., 2010; Medical Products Agency. Sweden, 2008; Portoles et al., 2005)

ACCEPTED MANUSCRIPT Table V – Estimation of population bioequivalence ratios for T1 and T6 from carvedilol pharmacokinetic profiles simulated in 1000 Caucasian subjects after a single dose of 25 mg in fasting conditions. T1/R

T6

T6/R

AUC

302

1.05

296

1.03

(µg*h/L)

(239 - 381)

(1.04 - 1.06)

(235 - 374)

(1.03 – 1.04)

Cmax

145

1.44

142

1.39

(µg/L)

(86.0 -233)

(1.25 – 1.58)

(84.7 -228)

(1.25 – 1.54)

0.570

0.625

0.643

0.706

(0.511 0.636)

(0.579 0.667)

(0.584 0.710)

(0.667 0.750)

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(h)

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Tmax

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T1

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Results reported as: median (non-parametric 90%CI = 5th percentile – 95th percentile). AUC: area under the plasma concentration-time curve from 0 to infinity. Cmax: maximum plasma concentration after single oral dose. Tmax: time of Cmax.

Graphics Abstract

Figure 1

Figure 2

Figure 3