Extensión de tiempo QT
Efectos adversos de las drogas
Variantes ✨Para la evaluación computacionalmente intensiva de las variantes, elija la suscripción estándar paga.
Áreas de aplicación
Explicaciones para pacientes
|Fenitoína||2.85 [2.85,2.86] 1||1.31||1.83|
Los cambios en la exposición mencionados se refieren a cambios en la curva de concentración plasmática-tiempo [AUC]. No detectamos ningún cambio en la exposición a amiodarona. Actualmente no podemos estimar la influencia de fluconazol y fenitoína. La exposición a fenitoína aumenta al 285%, cuando se combina con amiodarona (131%) y fluconazol (183%). El AUC está entre 285% y 286% dependiendo del
Los parámetros farmacocinéticos de la población media se utilizan como punto de partida para calcular los cambios individuales en la exposición debidos a las interacciones.
La amiodarona tiene una biodisponibilidad oral media [ F ] del 55%, por lo que los niveles plasmáticos máximos [Cmax] tienden a cambiar con una interacción. La vida media terminal [ t12 ] es bastante larga a las 1884 horas y los niveles plasmáticos constantes [ Css ] solo se alcanzan después de más de 7536 horas. La unión a proteínas [ Pb ] es 96% fuerte. El metabolismo tiene lugar a través de CYP2C8 y CYP3A4, entre otros. y el transporte activo tiene lugar en particular a través de PGP.
La fluconazol tiene una alta biodisponibilidad oral [ F ] del 90%, por lo que los niveles plasmáticos máximos [Cmax] tienden a cambiar poco durante una interacción. La vida media terminal [ t12 ] es bastante larga a las 30 horas y los niveles plasmáticos constantes [ Css ] solo se alcanzan después de más de 120 horas. La unión a proteínas [ Pb ] es muy débil al 11.5% y el volumen de distribución [ Vd ] es de 56 litros. Aproximadamente el 80.0% de la dosis administrada se excreta inalterada a través de los riñones y esta proporción rara vez se modifica por las interacciones. El metabolismo no tiene lugar a través de los citocromos comunes..
La fenitoína tiene una alta biodisponibilidad oral [ F ] del 85%, por lo que los niveles plasmáticos máximos [Cmax] tienden a cambiar poco durante una interacción. La vida media terminal [ t12 ] es de 13 horas y se alcanzan niveles plasmáticos constantes [ Css ] después de aproximadamente 52 horas. La unión a proteínas [ Pb ] es moderadamente fuerte al 90% y el volumen de distribución [ Vd ] es de 47 litros en el rango medio, Dado que la sustancia tiene una tasa de extracción hepática baja de 0,9, el desplazamiento de la unión a proteínas [Pb] en el contexto de una interacción puede aumentar la exposición. El metabolismo tiene lugar a través de CYP2C19, CYP2C9 y CYP2E1, entre otros. y el transporte activo tiene lugar en particular a través de PGP.
|Efectos serotoninérgicos a||0||Ø||Ø||Ø|
Clasificación: Según nuestro conocimiento, ni la amiodarona, fluconazol ni la fenitoína aumentan la actividad serotoninérgica.
Clasificación: Según nuestros hallazgos, ni la amiodarona, fluconazol ni la fenitoína aumentan la actividad anticolinérgica.
Extensión de tiempo QT
Clasificación: En combinación, la amiodarona y la fluconazol pueden desencadenar potencialmente arritmias ventriculares del tipo torsades de pointes. No conocemos ningún potencial de prolongación del intervalo QT para la fenitoína.
Efectos secundarios generales
|Efectos secundarios||∑ frecuencia||ami||flu||fen|
|Dolor de cabeza||7.4 %||n.a.||7.5||n.a.|
|Pérdida de apetito||6.5 %||6.5||n.a.||n.a.|
|Problema de coordinación||6.5 %||6.5||n.a.||n.a.|
Parestesia (6.5%): amiodarona
Neuropatía periférica: amiodarona
Deterioro de la memoria: fenitoína
Pseudotumor cerebri: amiodarona
Visión borrosa (6.5%): amiodarona
Neuritis óptica: amiodarona
Pérdida visual: amiodarona
Hipertiroidismo (2%): amiodarona
Síndrome de distrés respiratorio agudo (2%): amiodarona
Fibrosis pulmonar: amiodarona
Insuficiencia cardiaca: amiodarona
Arritmia ventricular: amiodarona
Fosfatasa alcalina elevada: fluconazol
ALT elevado: fluconazol
AST elevado: fluconazol
Hepatotoxicidad: amiodarona, fluconazol
Insuficiencia hepática: fluconazol
Síndrome de Stevens-Johnson: amiodarona, fluconazol, fenitoína
Necrolisis epidérmica toxica: amiodarona, fluconazol, fenitoína
Dermatosis bullosa: fenitoína
Sintiéndose nervioso: fenitoína
Trombocitopenia: amiodarona, fenitoína
Agranulocitosis: fluconazol, fenitoína
Reacción de hipersensibilidad: amiodarona
Síndrome de DRESS: fluconazol, fenitoína
Insuficiencia renal: amiodarona
Hipertrofia gingival: fenitoína
Con base en sus
Referencias de literatura
Abstract: Phenytoin is a relatively insoluble weak acid, usually administered as the sodium salt. Bioavailability is dependent upon particle size and problems of generic inequivalence have therefore arisen, particularly in Scandinavia. The drug has a moderately large volume of distribution and is approximately 90% bound to plasma proteins. Clinically important displacement can be caused by bilirubin and several drugs, particularly sodium valproate, which is often combined with phenytoin. Displacement will lower the total serum concentration but will little affect the free drug concentration. The metabolism of phenytoin to the major metabolite, 5-(p-hydroxyphenyl)-5-(phenylhydantoin, is saturable, giving rise to a non linear dose-serum concentration relationship. Therefore, the dose range compatible with a therapeutic serum concentration is narrow within subjects, and monitoring serum concentrations is of particular value in dosage tailoring. In renal failure, the binding of phenytoin to plasma proteins is reduced and therefore a lower range of serum drug concentrations is compatible with therapeutic control. In liver disease, binding may also be impaired but delayed metabolism may occur in addition. During pregnancy the serum concentration may fall progressively as pregnancy advances, probably due to an increased rate of metabolism. Phenytoin readily crosses the placenta, and is metabolised rapidly by the neonate exposed in utero.
Abstract: 1. The oral pharmacokinetics of fluconazole were studied in three groups of volunteers (n = 5) with various degrees of renal function (GFR greater than 70 ml min-1; 20-70 ml min-1; less than 20 ml min-1) and in a group of patients with chronic end-stage renal failure requiring regular haemodialysis. 2. The pharmacokinetics of fluconazole were markedly affected by impaired renal function with the elimination of half-life in Group III (GFR less than 20 ml min-1) being approximately three times that observed in normal volunteers (Group I). 3. Fluconazole renal clearance was positively correlated with GFR. 4. Non-renal clearance of fluconazole decreased with decreasing renal function. 5. Approximately 38% of the 50 mg dose of fluconazole was removed by haemodialysis extending over a 3 h period.
Abstract: 1. In a double-blind crossover study 10 healthy males received either placebo or omeprazole (40 mg day-1) for 9 days, a single dose of phenytoin (300 mg) being taken on the seventh day. 2. Omeprazole significantly increased the area under the curve (0 to 72 h) of phenytoin (mean +/- s.e. mean) from 121.6 +/- 14.0 to 151.4 +/- 13.6 micrograms ml-1 h) (P less than 0.01). 3. The peak concentration, and apparent elimination half-life of phenytoin also tended to be increased though not significantly. 4. The omeprazole-phenytoin interaction observed may be clinically important because of the low therapeutic index associated with phenytoin.
Abstract: Clearance of phenytoin after i.v. injection of 100 mg was studied in six patients before and after 2 weeks daily treatment with 450 mg rifampicin, and in 14 patients with tuberculosis receiving standard treatment with 450 mg rifampicin, 300 mg isoniazid, and 1200 mg ethambutol daily. Acetylator status was measured by urinary acetylated sulphadimidine. Clearance of phenytoin in patients receiving only rifampicin increased from 46.7 ml min-1 +/- 20.6 ml min-1 to 97.8 ml min-1 +/- 33.4 ml min-1 (P less than 0.01), while clearance in patients on three drugs increased from 47.1 +/- 23.4 ml min-1 to 81.3 ml min-1 +/- 41.6 ml min-1 (P less than 0.01). No significant differences were observed between the six fast acetylators and the eight slow acetylators. Phenytoin kinetics were unchanged after further 3 months of combined treatment. Rifampicin is a strong inducer of the elimination of phenytoin. Combined treatment with isoniazid has no counter-acting effect in either fast or slow acetylators.
Abstract: No Abstract available
Abstract: Amiodarone is considered to be safe in patients with prior QT prolongation and torsades de pointes taking class I antiarrhythmic agents who require continued antiarrhythmic drug therapy. However, the safety of amiodarone in advanced heart failure patients with a history of drug-induced torsades de pointes, who may be more susceptible to proarrhythmia, is unknown. Therefore, the objective of this study was to assess amiodarone safety and efficacy in heart failure patients with prior antiarrhythmic drug-induced torsades de pointes. We determined the history of torsades de pointes in 205 patients with heart failure treated with amiodarone, and compared the risk of sudden death in patients with and without such a history. To evaluate the possibility that all patients with a history of torsades de pointes would be at high risk for sudden death regardless of amiodarone treatment, we compared this risk in patients with a history of torsades de pointes who were and were not subsequently treated with amiodarone. Of 205 patients with advanced heart failure, 8 (4%) treated with amiodarone had prior drug-induced torsades de pointes. Despite similar severity of heart failure, the 1-year actuarial sudden death risk was markedly increased in amiodarone patients with than without prior torsades de pointes (55% vs 15%, p = 0.0001). Similarly, the incidence of 1-year sudden death was markedly increased in patients with prior torsades de pointes taking amiodarone compared with such patients who were not subsequently treated with amiodarone (55% vs 0%, p = 0.09).(ABSTRACT TRUNCATED AT 250 WORDS)
Abstract: A 25-year-old woman who was hospitalized for worsening endocarditis had a prolonged QT interval at baseline and developed monomorphic ventricular arrhythmias, which were managed successfully with pacing and antiarrhythmic therapy. Several days later, the patient started receiving high-dose fluconazole for fungemia and subsequently experienced episodes of torsades de pointes, a polymorphic ventricular arrhythmia associated with a prolonged QT interval or prominent U wave on the electrocardiogram. The arrhythmia developed in the presence of known risk factors. Clinicians should be aware of these risk factors and other relevant structural similarities with drugs that cause torsades de pointes so that they can recognize patients who may be at risk for fluconazole-associated arrhythmia.
Abstract: OBJECTIVE: Posaconazole is an extended-spectrum triazole antifungal agent for the treatment and prophylaxis of invasive fungal infections. This randomized, open-label, parallel-group, multiple-dose study was conducted in healthy adult volunteers to assess the potential for a drug interaction between phenytoin and the posaconazole tablet formulation. METHODS: Subjects were randomly assigned for 10 days to one of the following treatments: posaconazole (200 mg once daily), phenytoin (200 mg once daily), or posaconazole (200 mg once daily) and phenytoin (200 mg once daily). Blood samples were collected on days 1 and 10 for pharmacokinetic evaluation of posaconazole and phenytoin concentrations. RESULTS: A total of 36 healthy men enrolled in the study. On day 1, the maximum plasma concentration (C(max)) and area under the concentration-time curve calculated from time 0-24 h post-dose (AUC(0-24)) were unchanged upon co-administration. At steady state (day 10), co-administration of posaconazole with phenytoin resulted in 44% (p = 0.012) and 52% (p = 0.007) decreases in posaconazole C(max) and AUC(0-24), respectively. These decreases in exposure corresponded with a 90% increase in steady-state clearance of orally administered posaconazole. Phenytoin C(max) and AUC(0-24) were not significantly altered upon co-administration of the two agents, 24% increase in C(max) (p = 0.196) and 25% increase in AUC(0-24) (p = 0.212) values, although inter-subject variability was observed within this group. CONCLUSION: Because co-administration of phenytoin and posaconazole significantly reduces posaconazole exposure and increases phenytoin levels in some subjects, concomitant use of these agents should be avoided unless the benefit outweighs the risk.
Abstract: Fluconazole is an antifungal medication that has been reported to cause prolongation of the QT interval and Torsades de Pointes (TdP) ventricular tachycardia in adults. We describe the case of an 11-year-old child treated with fluconazole who developed ventricular arrhythmia culminating in TdP. We discuss the possible roles played by genetic and environmental factors in this child's rhythm disturbances. After briefly summarizing similar cases from the adult literature, we outline the putative mechanism by which fluconazole may cause arrhythmia. This case should alert pediatricians to the possible risks of fluconazole use, especially in the presence of electrolyte abnormalities, diuretic use, therapy with other pro-arrhythmic agents, or suspicion of congenital Long-QT Syndrome.
Abstract: PURPOSE: A case of torsades de pointes associated with fluconazole use is described. SUMMARY: A 68-year-old woman with a history of hypertension treated with 2.5 mg of indapamide for 16 months sought medical treatment after having two falls 1 month apart. A computed tomography scan and subsequent magnetic resonance imaging of the brain revealed a lesion in the left pons and middle cerebellar peduncle. Biopsy of the pontine lesion revealed large yeast forms and subsequently revealed Cryptococcus neoformans var. gattii. The patient was initially treated with conventional amphotericin B and flucytosine for six weeks. The first week of therapy was complicated by hypokalemia, hypomagnesemia, and an episode of atrial fibrillation that was managed with electrolyte replacement, commencement of metoprolol, and switching from conventional amphotericin B to amphotericin B lipid complex. After six weeks, liposomal amphotericin was discontinued and high-dose oral fluconazole was initiated. Six days after beginning fluconazole therapy, the patient had a generalized tonic-clonic seizure and suffered cardiopulmonary arrest. Postresuscitation, an electrocardiogram demonstrated a corrected Q-T interval of 556 msec. Recurrent episodes of torsades de pointes were also recorded postarrest. Fluconazole was discontinued at this time, and liposomal amphotericin B was resumed. Neurologic and electroencephalographic assessment conducted 48 hours postarrest revealed that significant neurologic damage had been sustained. Supportive care was withdrawn, and the patient died two days later. A postmortem examination revealed no coronary artery disease or hemorrhagic transformation of the pontine cryptococcoma. CONCLUSION: Treatment with high-dose fluconazole was the probable cause of torsades de pointes in a patient with risk factors for this condition. The benefits and risks of using fluconazole should be carefully weighed for patients with risk factors for Q-T interval prolongation.
Abstract: AIMS: To assess the role of MDR1 and gamma-aminobutyric acid receptor-gamma 2 sub unit (GABRG2) gene polymorphism in seizure susceptibility in generalized seizure (GS) and febrile seizure (FS) patients and to evaluate MDR1 C3435T gene polymorphism's role in absorption of the anti-epileptic drug, phenytoin (PHT) in a cohort of patients. METHODS: One hundred twenty-seven cases of seizure (86 GS and 41 FS) patients were analyzed for MDR1 C3435T and GABRG2 C588T gene polymorphisms using restriction fragment length polymorphism-polymerase chain reaction. Serum PHT levels were analyzed. RESULTS: The T allele of MDR1 C3435T and GABRG2 C588T gene polymorphism was higher in GS in the Indian population compared with controls. From the data in GS, CT and TT genotype carriers of the MDR1 gene and TT genotype carriers of the GABRG2 gene had more recurrent seizures compared with others. MDR1 T allele carriers in the seizure reoccurrence (SR) group of GS and FS were high compared with the well-controlled seizure group (with no seizures after treatment). TT genotype carriers in SR group were high in FS (with regard to MDR1 gene polymorphism) and GS (with regard to GABRG2 gene polymorphism) compared with a well-controlled seizure group. MDR1 C3435T gene polymorphism affects serum PHT levels (p<0.015). Association of dose PHT ratio and genotype groups of MDR1 C3435T gene polymorphism showed a significant association (p<0.05). MDR1*CC genotype was more common in cases with low serum PHT levels.In addition, it is evident that CT and TT genotype carriers have a high percentage of SR with elevated serum PHT levels. CONCLUSIONS: Our results show that the MDR1 3435T and GABRG2 588T alleles play a role in seizure occurrence. Moreover, the MDR1 3435T allele also affects PHT absorption. We suggest MDR1 C3435T and GABRG2 C588T genotyping would be of value in order to lower the risk of concentration-dependent drug toxicity and for better patient management.
Abstract: P-glycoprotein (P-gp), an ATP-dependant efflux pump transports a wide range of substrates across cellular membranes. Earlier studies have identified drug efflux due to the over-expression of P-gp as one of the causes for the resistance of phenytoin, an anti-epileptic drug (AED). While no clear evidence exists on the specific characteristics of phenytoin association with the human P-gp, this study employed structure-based computational approaches to identify its binding site and the underlying interactions. The identified site was validated with that of rhodamine, a widely accepted reference and an experimental probe. Further, an in silico proof-of-concept for phenytoin interactions and its decreased binding affinity with the closed-state of human P-gp model was provided in comparison with other AEDs. This is the first report to provide insights into the phenytoin binding site and possibly better explain its efflux by P-gp.
Abstract: AIM: Conducting PK studies in pregnant women is challenging. Therefore, we asked if a physiologically-based pharmacokinetic (PBPK) model could be used to predict the disposition in pregnant women of drugs cleared by multiple CYP enzymes. METHODS: We expanded and verified our previously published pregnancy PBPK model by incorporating hepatic CYP2B6 induction (based on in vitro data), CYP2C9 induction (based on phenytoin PK) and CYP2C19 suppression (based on proguanil PK), into the model. This model accounted for gestational age-dependent changes in maternal physiology and hepatic CYP3A, CYP1A2 and CYP2D6 activity. For verification, the pregnancy-related changes in the disposition of methadone (cleared by CYP2B6, 3A and 2C19) and glyburide (cleared by CYP3A, 2C9 and 2C19) were predicted. RESULTS: Predicted mean post-partum to second trimester (PP : T2 ) ratios of methadone AUC, Cmax and Cmin were 1.9, 1.7 and 2.0, vs. observed values 2.0, 2.0 and 2.6, respectively. Predicted mean post-partum to third trimester (PP : T3 ) ratios of methadone AUC, Cmax and Cmin were 2.1, 2.0 and 2.4, vs. observed values 1.7, 1.7 and 1.8, respectively. Predicted PP : T3 ratios of glyburide AUC, Cmax and Cmin were 2.6, 2.2 and 7.0 vs. observed values 2.1, 2.2 and 3.2, respectively. CONCLUSIONS: Our PBPK model integrating prior physiological knowledge, in vitro and in vivo data, allowed successful prediction of methadone and glyburide disposition during pregnancy. We propose this expanded PBPK model can be used to evaluate different dosing scenarios, during pregnancy, of drugs cleared by single or multiple CYP enzymes.
Abstract: Transporters in proximal renal tubules contribute to the disposition of numerous drugs. Furthermore, the molecular mechanisms of tubular secretion have been progressively elucidated during the past decades. Organic anions tend to be secreted by the transport proteins OAT1, OAT3 and OATP4C1 on the basolateral side of tubular cells, and multidrug resistance protein (MRP) 2, MRP4, OATP1A2 and breast cancer resistance protein (BCRP) on the apical side. Organic cations are secreted by organic cation transporter (OCT) 2 on the basolateral side, and multidrug and toxic compound extrusion (MATE) proteins MATE1, MATE2/2-K, P-glycoprotein, organic cation and carnitine transporter (OCTN) 1 and OCTN2 on the apical side. Significant drug-drug interactions (DDIs) may affect any of these transporters, altering the clearance and, consequently, the efficacy and/or toxicity of substrate drugs. Interactions at the level of basolateral transporters typically decrease the clearance of the victim drug, causing higher systemic exposure. Interactions at the apical level can also lower drug clearance, but may be associated with higher renal toxicity, due to intracellular accumulation. Whereas the importance of glomerular filtration in drug disposition is largely appreciated among clinicians, DDIs involving renal transporters are less well recognized. This review summarizes current knowledge on the roles, quantitative importance and clinical relevance of these transporters in drug therapy. It proposes an approach based on substrate-inhibitor associations for predicting potential tubular-based DDIs and preventing their adverse consequences. We provide a comprehensive list of known drug interactions with renally-expressed transporters. While many of these interactions have limited clinical consequences, some involving high-risk drugs (e.g. methotrexate) definitely deserve the attention of prescribers.
Abstract: All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs) of new chemical entities (NCEs) and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit), located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level). A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK) model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.
Abstract: BACKGROUND: The most common acquired cause of Long QT syndrome (LQTS) is drug induced QT interval prolongation. It is an electrophysiological entity, which is characterized by an extended duration of the ventricular repolarization. Reflected as a prolonged QT interval in a surface ECG, this syndrome increases the risk for polymorphic ventricular tachycardia (Torsade de Pointes) and sudden death. METHOD: Bibliographic databases as MEDLINE and EMBASE, reports and drug alerts from several regulatory agencies (FDA, EMEA, ANMAT) and drug safety guides (ICH S7B, ICH E14) were consulted to prepare this article. The keywords used were: polymorphic ventricular tachycardia, adverse drug events, prolonged QT, arrhythmias, intensive care unit and Torsade de Pointes. Such research involved materials produced up to December 2017. RESULTS: Because of their mechanism of action, antiarrhythmic drugs such as amiodarone, sotalol, quinidine, procainamide, verapamil and diltiazem are associated to the prolongation of the QTc interval. For this reason, they require constant monitoring when administered. Other noncardiovascular drugs that are widely used in the Intensive Care Unit (ICU), such as ondansetron, macrolide and fluoroquinolone antibiotics, typical and atypical antipsychotics agents such as haloperidol, thioridazine, and sertindole are also frequently associated with the prolongation of the QTc interval. As a consequence, critical patients should be closely followed and evaluated. CONCLUSION: ICU patients are particularly prone to experience a QTc interval prolongation mainly for two reasons. In the first place, they are exposed to certain drugs that can prolong the repolarization phase, either by their mechanism of action or through the interaction with other drugs. In the second place, the risk factors for TdP are prevalent clinical conditions among critically ill patients. As a consequence, the attending physician is expected to perform preventive monitoring and ECG checks to control the QTc interval.
Abstract: Amiodarone is one of the most commonly used antiarrhythmic drugs. Despite its well-known side effects, amiodarone is considered to be a relatively safe drug, especially in short-term usage to prevent life-threatening ventricular arrhythmias. Our case demonstrates an instance where short-term usage can yield drug side effect.
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 Zoltec150 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 ofand AUCvalues 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.