Which cytochrome P450 metabolizes phenazepam? Step by step in silico, in vitro, and in vivo studies

[Personalized character of toxic effects through mass nonlethal poisoning by phenazepam and other psychoactive substances]

Over several months, 14 people were admitted in 6 hospitals with severe symptoms of intoxication with psychoactive substances as a result of mass poisoning. All symptoms occurred after taking a drink that contained crushed phenazepam tablets. Samples of blood (n=10) and urine (n=6) taken from 14 sufferers for forensic, chemical and toxicological examination were analyzed using the HPLC-MS/MS method. Phenazepam was detected in the biomaterial of all 14 patients. Other psychoactive substances (baclofen, pregabalin, chlorprothixene, chlorpromazine, phenibut, tramadol, diazepam), narcotic substances and ethanol were also found in the sufferers. The phenazepam concentration in the blood was in the range of 109.75-786.50 ng/ml, in the urine - 8.97-101.28 ng/ml. The pharmacokinetic and toxicokinetic characteristics of toxicants as well as additional factors characterizing the phenotype of the sufferer in addition to drug's content in the biological material must be taken into account to determine the toxicity level of phenazepam against the background of combined action with other psychoactive substances.

[Therapy of mental disorders in patients with hematological malignancies]

OBJECTIVE

To assess the possibilities of therapy with minimal effective doses (MED) of psychotropic drugs for mental disorders (MD) that manifest during the treatment of hematological malignancies (HM).

MATERIAL AND METHODS

A prospective study was conducted at the National Medical Research Center for Hematology of the Russian Ministry of Health (Moscow), which included 204 (39.4%) men and 314 (60.6%) women (518 patients in total), aged 17 to 83 years (median 45 years), with various HM, in which the manifestation of MD occurred during the treatment of the underlying disease. To minimize the side-effects of psychotropic drugs and given the relatively mild level of MD, psychopharmacotherapy of patients was carried out mainly at MED. The severity of MD, manifested in patients, was assessed by the illness severity scale of the Clinical Global Impression (CGI) scale, and the effectiveness of the treatment was assessed by the improvement scale (CGI-I).

RESULTS

Mainly mild (188, 36%) and moderately pronounced (270, 52%) MD were noted in patients with HM during the treatment of the underlying disease. Severe psychopathological disorders (60, 12%) were observed much less often. Because of psychopharmacotherapy with MED, patients experienced a very significant (97, 19%) and significant improvement (354, 68%) of their mental state, less often the improvement was regarded as minimal (67, 13%). Therefore, almost all patients showed a stable relief of MD; in 87% (95% CI 84-90) of patients, this improvement was significant.

CONCLUSION

The tactics of treatment MD that manifest in patients with HM with MED of psychotropic drugs turned out to be therapeutically effective according to the results of the assessment on CGI scales.

Effects of CYP2C19*2 polymorphisms on the efficacy and safety of phenazepam in patients with anxiety disorder and comorbid alcohol use disorder

Introduction: Phenazepam therapy can often be ineffective and some patients develop dose-related adverse drug reactions. Aim. The purpose of this research was to study the effect of the CYP2C19*2 (681G>A, rs4244285) in patients with anxiety disorders and alcohol dependence taking phenazepam therapy. Materials & methods: Patients (175 males, average age: 37.16 ± 7.84 years) received phenazepam in tablet form for 5 days. Genotyping was performed by real-time polymerase chain reaction. Results: The statistically significant differences in the UKU Side-Effect Rating Scale scores on the fifth day of therapy: (CYP2C19*1/*1) 2.00 [1.00; 2.00), (CYP2C19*1/*2) 7.00 (7.00; 7.00), (CYP2C19*2/*2) 9.00 (8.00; 9.00), p < 0.001. Conclusion: This study demonstrated the different efficacy and safety of phenazepam in patients with different genotypes of CYP2C19*2.

CYP3A subfamily activity affects the equilibrium concentration of Phenazepam® in patients with anxiety disorders and comorbid alcohol use disorder

Phenazepam^® is prescribed to relieve anxiety and sleep disorders during alcohol withdrawal, although it is associated with undesirable side effects. Aim: To demonstrate changes in the safety and efficacy profiles of Phenazepam in patients with anxiety disorders and comorbid alcohol use disorder. Materials & methods: A total of 94 Russian patients with alcohol use disorder received 4.0 mg of Phenazepam per day in tablets. We used a urinary 6-beta-hydroxycortisol/cortisol ratio to evaluate CYP3A activity. Results: A statistically significant inverse correlation between Phenazepam plasma concentration and CYP3A activity was found (r = -0.340 and p = 0.017). Correlation between the concentration/dose ratio and phenotyping results was also statistically significant (r = 0.301 and p = 0.026). Conclusion: The safety and efficacy of Phenazepam depend on CYP3A genetic polymorphisms.

Drug-drug interaction prediction using PASS

Simultaneous use of the drugs may lead to undesirable Drug-Drug Interactions (DDIs) in the human body. Many DDIs are associated with changes in drug metabolism that performed by Drug-Metabolizing Enzymes (DMEs). In this case, DDI manifests itself as a result of the effect of one drug on the biotransformation of other drug(s), its slowing down (in the case of inhibiting DME) or acceleration (in case of induction of DME), which leads to a change in the pharmacological effect of the drugs combination. We used OpeRational ClassificAtion (ORCA) system for categorizing DDIs. ORCA divides DDIs into five classes: contraindicated (class 1), provisionally contraindicated (class 2), conditional (class 3), minimal risk (class 4), no interaction (class 5). We collected a training set consisting of several thousands of drug pairs. Algorithm of PASS program was used for the first, second and third classes DDI prediction. Chemical descriptors called PoSMNA (Pairs of Substances Multilevel Neighbourhoods of Atoms) were developed and implemented in PASS software to describe in a machine-readable format drug substances pairs instead of the single molecules. The average accuracy of DDI class prediction is about 0.84. A freely available web resource for DDI prediction was developed (http://way2drug.com/ddi/).

Prediction of Drug-Drug Interactions Related to Inhibition or Induction of Drug-Metabolizing Enzymes

Drug-drug interaction (DDI) is the phenomenon of alteration of the pharmacological activity of a drug(s) when another drug(s) is co-administered in cases of so-called polypharmacy. There are three types of DDIs: pharmacokinetic (PK), pharmacodynamic, and pharmaceutical. PK is the most frequent type of DDI, which often appears as a result of the inhibition or induction of drug-metabolising enzymes (DME). In this review, we summarise in silico methods that may be applied for the prediction of the inhibition or induction of DMEs and describe appropriate computational methods for DDI prediction, showing the current situation and perspectives of these approaches in medicinal and pharmaceutical chemistry. We review sources of information on DDI, which can be used in pharmaceutical investigations and medicinal practice and/or for the creation of computational models. The problem of the inaccuracy and redundancy of these data are discussed. We provide information on the state-of-the-art physiologically- based pharmacokinetic modelling (PBPK) approaches and DME-based in silico methods. In the section on ligand-based methods, we describe pharmacophore models, molecular field analysis, quantitative structure-activity relationships (QSAR), and similarity analysis applied to the prediction of DDI related to the inhibition or induction of DME. In conclusion, we discuss the problems of DDI severity assessment, mention factors that influence severity, and highlight the issues, perspectives and practical using of in silico methods.