Screening novel CNS drug candidates for P-glycoprotein interactions using the cell line iP-gp: In vitro efflux ratios from iP-gp and MDCK-MDR1 monolayers compared to brain distribution data from mice.

Drug efflux by P-glycoprotein (P-gp, ABCB1) is considered as a major obstacle for brain drug delivery for small molecules. P-gp-expressing cell monolayers are used for screening of new drug candidates during early states of drug development. It is, however, uncertain how well the in vitro studies can predict the in vivo P-gp mediated efflux at the blood-brain barrier (BBB). We previously developed a novel cell line of porcine origin, the iP-gp cell line, with high transepithelial resistance and functional expression of human P-gp. The aim of the present study was to evaluate the applicability of the cell line for screening of P-gp interactions of novel drug candidates. For this purpose, bidirectional fluxes of 14 drug candidates were measured in iP-gp cells and in MDCK-MDR1 cells, and compared with pharmacokinetic data obtained in male C57BL/6 mice. The iP-gp cells formed extremely tight monolayers (>15 000 Ω∙cm2) as compared to the MDCK- MDR1 cells (>250 Ω∙cm2) and displayed lower Papp,a-b values. The efflux ratios obtained with iP-gp and MDCK-MDR1 monolayers correlated with Kp,uu,brain values from the in vivo studies, where compounds with the lowest Kp,uu,brain generally displayed the highest efflux ratios. 12 of the tested compounds displayed a poor BBB penetration in mice as judged by Kp,uu less than 1. Of these compounds, nine compounds were categorized as P-gp substrates in the iP-gp screening, whereas analysis of data estimated in MDCK-MDR1 cells indicated four compounds as potential substrates. The results suggest that the iP-gp cell model may be a sensitive and useful screening tool for drug screening purposes to identify possible substrates of human P-glycoprotein.

[Electroconvulsive therapy in combination with psychotropic and non-psychotropic pharmacological treatments: Review of the literature and practical recommendations]. / Électroconvulsivothérapie en association avec des traitements pharmacologiques psychotropes et non psychotropes : revue de la littérature et recommandations pratiques.

CONTEXT: Electro-convulsive therapy (ECT) is the most effective treatment for treatment resistant mood disorders and catatonia. ECT also appears to be an effective treatment in combination with clozapine in the context of treatment resistant schizophrenia spectrum disorders. Although increasingly codified (guidelines on indications, contraindications, methods of implementation), the practice of ECT still lacks consensual protocols. The concomitant use of psychotropic and/or non-psychotropic medication is a common situation when ECT treatment is considered. To our knowledge, there is to date no summary of studies or case reports in France, nor any proposal for guidelines concerning the management of medication of the patient to whom ECT sessions are offered. Indeed, several particularities must be considered. This article proposes to specify for each pharmacological class the possible interaction between ECT and medication. A first section of this article will be devoted to non-psychotropic treatments, and a second section to psychotropic treatments. A practical summary table is also provided. METHOD: A review of the literature was conducted including all articles published prior to January 2019 referenced in Pub Med database, combining research with Medical Subject Headings "Electroconvulsive Therapy" and each following pharmacological class: "Cardiovascular Agents" "Bronchodilator Agents" "Bronchoconstrictor Agents" "Theophylline" "Anticoagulants" "Hypoglycemic Agents" "Insulin" "Potassium" "Benzodiazepines" "Valproic Acid" "Carbamazepine" "Lamotrigine" "Lithium" "Antidepressive Agents" "Antipsychotic Agents". RESULTS: After reading the titles, abstracts and whole articles, then searching for additional articles in the references, 50 articles were selected. A summary table summarizing the main risks and proposing a course of action has been produced. DISCUSSION: It is essential to take into account the specificity and the different physiological mechanisms involved in the ECT treatment in order to adjust the associated pharmacological treatments. The prescription for each molecule should be reviewed when ECT treatment is initiated.

Pharmacological treatment of attention-deficit/hyperactivity disorder in children and adolescents with epilepsy.

Attention-deficit/hyperactivity disorder (ADHD) is the most frequent comorbidities in children with epilepsy with an increased risk of other psychiatric comorbidities and academic underachievement. In children with epilepsy, the attentive form is the most common clinical presentation in pediatric epilepsies. A systemic review and a consensus from the ILAE have been recently published on diagnosis, screening and management of ADHD in children with epilepsy. We give an overview of the pharmacological treatment of ADHD in children with epilepsy based on the lecture given at the International League Against Epilepsy (ILAE) French Chapter meeting, (October 2018, Lyon). Although only class II and class III studies are available, methylphenidate is the most appropriate pharmacological option for the treatment of ADHD in children with epilepsy with a limited risk of seizure worsening. The medical treatment should be used in combination of the global management including optimal antiepileptic drug treatment avoiding polytherapy, management of psychiatric comorbidities and support at school.

Physicochemical property profile for brain permeability: comparative study by different approaches.

A comparative study of classification models of brain penetration by different approaches was carried out on a training set of 1000 chemicals and drugs, and an external test set of 100 drugs. Ten approaches were applied in this work: seven medicinal chemistry approaches (including "rule of 5" and multiparameter optimization) and also three SAR techniques: logistic regression (LR), random forest (RF) and support vector machine (SVM). Forty-one different medicinal chemistry descriptors representing diverse physicochemical properties were used in this work. Medicinal chemistry approaches based on the intuitive estimation of preference zones of CNS or non-CNS chemicals, with different rules and scoring functions, yield unbalanced models with poor classification accuracy. RF and SVM methods yielded 82% and 84% classification accuracy respectively for the external test set. LR was also successful in CNS/non-CNS (denoted in this study as CNS+/CNS-) classification and yielded an overall accuracy equivalent to that of SVM and RF. At the same time, LR is especially valuable for medicinal chemists because of its simplicity and the possibility of clear mechanistic interpretation.

Psychopharmacology in autism: an update.

Autism spectrum disorders are characterized by impairment in social reciprocity, disturbances in language and communication, restricted interests and repetitive behaviors of various types, as defined by the DSM-IV. The neurobiological bases of these disorders are poorly understood, although several abnormalities have been found. Pharmacotherapy in autism spectrum disorders lacks a solid, reliable neurobiological basis and at present it is mainly directed at the so-called associated behavioral symptoms, with limited relevance to core symptoms. Atypical neuroleptics, especially risperidone, have been shown to be useful in the treatment of behavioral symptoms in autism. Recent trials with SSRIs did not show remarkable results, in spite of their promising potential role. Attention deficit and hyperactivity disorder medications may be useful for counteracting the additional features of hyperactivity and short attention span. Antiepileptics have shown promising results but there are no specific indications for them as of yet. Research is now directed at evaluating novel treatments and combined behavioral and pharmacologic treatments, since behavioral interventions are the mainstay of the early treatment of autism. An update of currently available pharmacological treatments is provided.

[Subject and basic definitions of the addictive medicine: the notion of addictive disorders].

The definition and classification of psychoactive substances are presented. The basic clinical notions related to non-medical use of drugs are defined and characterized. The criteria of drug dependences are listed. The description of phasic states of addictive diseases is presented. The relationship between addictive disorders and abnormal activity of cerebral reward system is emphasized. The problem of treatment resistance of addictive disorders and low treatment efficacy in addictive medicine is designated.

Outpatient utilization of drugs acting on nervous system: a study from the Republic of Srpska, Bosnia & Herzegovina.

PURPOSE: The aim of this study was to analyse the utilization patterns of drugs acting on the nervous system in the Republic of Srpska, Bosnia & Herzegovina between 2002 and 2008. METHODS: This was a retrospective study aimed at analysing outpatient utilization of drugs reimbursed by the Health Insurance Fund, with a focus on the utilization of drugs acting on the nervous system. Anatomical therapeutic chemical/defined daily dose methodology was used to monitor drug utilization, and the drug utilization 90% (DU90%) method was used to assess drug prescribing. RESULTS: The most highly used drug subgroups were psycholeptics and antiepileptics followed by the psychoanaleptics. Anxyolitics comprised the most prescribed pharmacological subgroup over the whole study period, but a decrease was observed in 2007 and 2008. Following updating of the list with selective serotonin re-uptake inhibitor drugs, particularly sertraline, antidepressant use increased fivefold in 2008 compared to 2006. Tramadol was the predominant opioid analgesics in terms of utilization, while the use of oral morphine was low. Diazepam was the most highly prescribed drug, followed by phenobarbital and carbamazepine. The list update with the new generation drugs was immediately reflected in the DU90% profile. CONCLUSIONS: The observed tendency toward increased total drug utilization observed in our study is comparable to worldwide trends. Implementation of new clinical guidelines for nervous diseases and updating of the list of reimbursable drugs with the addition of new ones contributed to the observed improvement in prescribing patterns in primary healthcare during the study period. The DU90% is shown to be a simple rough method for assessing prescribing quality. More stratified analyses should be performed on a routine basis to ensure a rational use of medicines and a cost-efficient use of limited healthcare resources.

A neural network based virtual high throughput screening test for the prediction of CNS activity.

A virtual high throughput screening test to identify potentially CNS-active drugs has been developed. Discrimination was based on the knowledge available in databases containing CNS-active (Cipsline from Prous Science) and inactive compounds (Chemical Directory from Sigma-Aldrich). Molecular structures were represented using 2D Unit y fingerprints and a feedforward neural network was trained to classify molecules regarding their CNS activity. The parameterized network was validated by reclassification of the training set elements, by the classification of a test set preselected from the Prous database, and also by the prediction of activity for known CNS drugs not used in the training set but available in the Medchem database (Daylight). These tests revealed that our neural net recognized at least 89% of CNS-active compounds and would be suitable for use in our virtual screening protocol.

Designing libraries with CNS activity.

Library design is an important and difficult task. In this paper we describe one possible solution to designing a CNS-active library. CNS-actives and -inactives were selected from the CMC and the MDDR databases based on whether they were described as having some kind of CNS activity in the databases. This classification scheme results in over 15 000 actives and over 50 000 inactives. Each molecule is described by 7 1D descriptors (molecular weight, number of donors, number of acceptors, etc.) and 166 2D descriptors (presence/absence of functional groups such as NH(2)). A neural network trained using Bayesian methods can correctly predict about 75% of the actives and 65% of the inactives using the 7 1D descriptors. The performance improves to a prediction accuracy on the active set of 83% and 79% on the inactives on adding the 2D descriptors. On a database with 275 compounds where the CNS activity is known (from the literature) for each compound, we achieve 92% and 71% accuracy on the actives and inactives, respectively. The models we construct can therefore be used as a "filter" to examine any set of proposed molecules in a chemical library. As an example of the utility of our method, we describe the generation of a small library of potentially CNS-active molecules that would be amenable to combinatorial chemistry. This was done by building and analyzing a large database of a million compounds constructed from frameworks and side chains frequently found in drug molecules.

Use of central nervous system medications among elderly home health clients.

Older persons consume a disproportionate share of all medications dispensed in the United States. In particular, medications acting upon the central nervous system (CNS) have been overprescribed for elderly persons, both in and out of the institutional setting. Although researchers have studied drug use by elders who live in the community, little is known about the use of CNS medications by ill older persons who live at home. This descriptive study examined the use of CNS medications in a group of elderly persons (N = 141) admitted to a visiting nurse association for skilled care. Subjects resided in the community of a large midwestern city. Approximately half of the subjects used some type of CNS drug. Sedative/hypnotic and narcotic and opioid analgesics, two categories of medications with the potential for serious side effects, were most frequently prescribed. Nurses in community and institutional settings are in an ideal position to screen and monitor the use of CNS medications by homebound ill elders.