Tissue distribution of propafenone in the rat after intravenous administration

A Tissue Distribution Study of Propafenone in an Intentional Fatal Poisoning Case

Propafenone (PPF) belongs to the class 1C antiarrhythmics and can cause electrocardiogram-associated adverse/toxic effects. Cases of PPF intoxication are rarely investigated. We developed a novel and selective GC-MS/MS method for the determination of PPF and its tissue distribution in an intentional fatal poisoning case, which is applicable to PPF quantification in the range of therapeutic to lethal concentrations in complex post-mortem samples. A simple and effective sample pretreatment was applied to all analyzed samples. PPF was determined without the need for dilution, even in highly complex samples containing a wide range of analyte concentrations. Quantification was performed using the standard addition method, developed and validated according to the ICH M10 guidelines. The obtained results indicated that the PPF concentration in the serum from blood taken while alive, before therapy, was the highest ever reported in the literature. Despite the intensive therapy after the patients' admission, the PPF concentrations in the lungs, spleen, femoral blood and cardiac blood were fatal or abnormally high. On the other hand, the concentrations in the liver and skeletal muscle were lower or approximately the same as observed in cases with therapeutic doses. To the best of our knowledge, the distribution of PPF has not been investigated in fatal intoxication cases and can be helpful in clinical or forensic toxicology.

Effect of Rythmol (propafenone HCl) administration during pregnancy in Wistar rats

Propafenone is a well-known Class 1C antiarrhythmic agent that has sodium channel blocking properties as well as the ability to block 13 other channels and a modest calcium antagonistic effect. Propafenone has a profound electrophysiologic effect on auxiliary atrioventricular circuits and in patients with atrioventricular nodal reentry tachycardia can obstruct conduction in the fast conducting pathway. Furthermore, propafenone is less likely than other Class 1C drugs to cause proarrhythmia. However, although this medicine can pass through the placenta, the effects during pregnancy remain unknown. Here, we investigated the potential teratogenic and genotoxic effects of Rythmol during rat development. Pregnant Wistar rats received 46.25 mg/kg body weight of propafenone daily by gavage from Gestation Day (GD) 5 to GD 19. At GD 20, the dams were dissected, and their fetuses were assessed via morphologic, skeletal, and histologic investigation. In addition, a comet assay was used to measure DNA impairment of fetal skull osteocytes and hepatic cells. The study showed that propafenone treatment of pregnant rats led to a marked decrease in gravid uterine weight, number of implants/litter, number of viable fetuses, and bodyweight of fetuses but a clear increase in placental weight and placental index in the treated group. Frequent morphologic abnormalities and severe ossification deficiency in the cranium bones were observed in the treatment group. Various histopathological changes were observed in the liver, kidney, and brain tissues of maternally treated fetuses. Similarly, propafenone induced DNA damage to examined samples. Thus, our study indicates that propafenone may be embryotoxic in humans.

Influence of propafenone on the anticonvulsant activity of various novel antiepileptic drugs in the mouse maximal electroshock model

BACKGROUND

The main mechanism of action of propafenone (antiarrhythmic drug) involves the inhibition of the fast inward sodium current during phase 0 of the action potential. Sodium channel-blocking activity is also characteristic for some antiepileptic drugs. Therefore, it could be assumed that propafenone may also affect seizures. In the present study, we evaluated the effect of propafenone on the protective effect of oxcarbazepine, lamotrigine, topiramate and pregabalin against the maximal electroshock-induced seizures in mice.

METHODS

Anticonvulsant activity of propafenone was assessed with the maximal electroshock seizure threshold (MEST) test. Influence of propafenone on the anticonvulsant activity of antiepileptic drugs was estimated in the mouse maximal electroshock model (MES). Drug-related adverse effects were determined in the chimney test (motor coordination) and passive-avoidance task (long-term memory). Brain concentrations of antiepileptics were assessed by fluorescence polarization immunoassay.

RESULTS

Propafenone at doses 60-90mg/kg significantly increased the threshold of seizures, in turn at doses 5-50mg/kg did not affect this parameter. Administration of propafenone at the subthreshold dose of 50mg/kg increased antielectroshock activity of oxcarbazepine, topiramate and pregabalin, but not that of lamotrigine. As regards adverse effects, propafenone alone and in combination with antiepileptic drugs did not significantly impair motor coordination or long-term memory in mice. Propafenone (50mg/kg) significantly increased the brain level of pregabalin. Brain concentrations of topiramate and oxcarbazepine were not affected.

CONCLUSION

Our findings show that propafenone has own anticonvulsant action and enhances efficacy of oxcarbazepine, topiramate and pregabalin, but not that of lamotrigine, at least in experimental condition.

Propafenone enhances the anticonvulsant action of classical antiepileptic drugs in the mouse maximal electroshock model

BACKGROUND

Antiarrhythmic and antiepileptic drugs share some mechanisms of actions. Therefore, possibility of interactions between these in epileptic patients with cardiac arrhythmias is quite considerable. Herein, we attempted to assess interactions between propafenone and four conventional antiepileptic drugs: carbamazepine, valproate, phenytoin and phenobarbital.

METHODS

Effects of propafenone on seizures were determined in the electroconvulsive threshold test in mice. Interactions between propafenone and antiepileptic drugs were estimated in the model of maximal electroshock. Motor coordination was evaluated in the chimney test, while long-term memory in the passive-avoidance task. Brain concentrations of antiepileptics were determined by fluorescence polarization immunoassay.

RESULTS

Propafenone up to 50mg/kg did not affect the electroconvulsive threshold, significantly enhancing this parameter at doses of 60-90mg/kg. Applied at its subthreshold doses, propafenone potentiated the antielectroshock action of all four tested classical antiepileptics: carbamazepine, valproate, phenytoin, and phenobarbital. Propafenone alone and in combinations with antiepileptics impaired neither motor performance nor long-term memory in mice. Propafenone did not change brain concentration of phenytoin and phenobarbital; however, it significantly decreased brain levels of carbamazepine and increased those of valproate.

CONCLUSIONS

Propafenone exhibits its own anticonvulsant effect and enhances the action of classical antiepileptic drugs against electrically induced convulsions in mice. Further investigations are required to determine the effect of propafenone on antiepileptic therapy in humans.

Prediction of pharmacokinetics prior to in vivo studies. 1. Mechanism-based prediction of volume of distribution

In drug discovery and nonclinical development the volume of distribution at steady state (V(ss)) of each novel drug candidate is commonly determined under in vivo conditions. Therefore, it is of interest to predict V(ss) without conducting in vivo studies. The traditional description of V(ss) corresponds to the sum of the products of each tissue:plasma partition coefficient (P(t:p)) and the respective tissue volume in addition to the plasma volume. Because data on volumes of tissues and plasma are available in the literature for mammals, the other input parameters needed to estimate V(ss) are the P(t:p)'s, which can potentially be predicted with established tissue composition-based equations. In vitro data on drug lipophilicity and plasma protein binding are the input parameters used in these equations. Such a mechanism-based approach would be particularly useful to provide first-cut estimates of V(ss) prior to any in vivo studies and to explore potential unexpected deviations between sets of predicted and in vivo V(ss) data, when the in vivo data become available during the drug development process. The objective of the present study was to use tissue composition-based equations to predict rat and human V(ss) prior to in vivo studies for 123 structurally unrelated compounds (acids, bases, and neutrals). The predicted data were compared with in vivo data obtained from the literature or at Roche. Overall, the average ratio of predicted-to-experimental rat and human V(ss) values was 1.06 (SD = 0.817, r = 0.78, n = 147). In fact, 80% of all predicted values were within a factor of two of the corresponding experimental values. The drugs can therefore be separated into two groups. The first group contains 98 drugs for which the predicted V(ss) were within a factor of two of those experimentally determined (average ratio of 1.01, SD = 0.39, r = 0.93, n = 118), and the second group includes 25 other drugs for which the predicted and experimental V(ss) differ by a factor larger than two (average ratio of 1.32, SD = 1.74, r = 0.42, n = 29). Thus, additional relevant distribution processes were neglected in predicting V(ss) of drugs of the second group. This was true especially in the case of some cationic-amphiphilic bases. The present study is the first attempt to develop and validate a mechanistic distribution model for predicting rat and human V(ss) of drugs prior to in vivo studies.