Escitalopram/reboxetine combination in depressed patients with substance use disorder

Machine Learning Analysis of Cocaine Addiction Informed by DAT, SERT, and NET-Based Interactome Networks

Cocaine addiction is a psychosocial disorder induced by the chronic use of cocaine and causes a large number of deaths around the world. Despite decades of effort, no drugs have been approved by the Food and Drug Administration (FDA) for the treatment of cocaine dependence. Cocaine dependence is neurological and involves many interacting proteins in the interactome. Among them, the dopamine (DAT), serotonin (SERT), and norepinephrine (NET) transporters are three major targets. Each of these targets has a large protein-protein interaction (PPI) network, which must be considered in the anticocaine addiction drug discovery. This work presents DAT, SERT, and NET interactome network-informed machine learning/deep learning (ML/DL) studies of cocaine addiction. We collected and analyzed 61 protein targets out of 460 proteins in the DAT, SERT, and NET PPI networks that have sufficiently large existing inhibitor datasets. Utilizing autoencoder (AE) and other ML/DL algorithms, including gradient boosting decision tree (GBDT) and multitask deep neural network (MT-DNN), we built predictive models for these targets with 115 407 inhibitors to predict drug repurposing potential and possible side effects. We further screened their absorption, distribution, metabolism, and excretion, and toxicity (ADMET) properties to search for leads having potential for developing treatments for cocaine addiction. Our approach offers a new systematic protocol for artificial intelligence (AI)-based anticocaine addiction lead discovery.

Why do some promising brain-stimulation devices fail the next steps of clinical development?

Interest in techniques of noninvasive brain stimulation (NIBS) has been growing exponentially in the last decade. Recent studies have shown that some of these techniques induce significant neurophysiological and clinical effects. Although recent results are promising, there are several techniques that have been abandoned despite positive initial results. In this study, we performed a systematic review to identify NIBS methods with promising preliminary clinical results that were not fully developed and adopted into clinical practice, and discuss its clinical, research and device characteristics. We identified five devices (transmeatal cochlear laser stimulation, transcranial micropolarization, transcranial electrostimulation, cranial electric stimulation and stimulation with weak electromagnetic fields) and compared them with two established NIBS devices (transcranial magnetic stimulation and transcranial direct current stimulation) and with well-known drugs used in neuropsychiatry (pramipexole and escitalopram) in order to understand the reasons why they failed to reach clinical practice and further steps of research development. Finally, we also discuss novel NIBS devices that have recently showed promising results: brain ultrasound and transcranial high-frequency random noise stimulation. Our results show that some of the reasons for the failure of NIBS devices with promising clinical findings are the difficulty to disseminate results, lack of controlled studies, duration of research development, mixed results and lack of standardization.

Monotherapy with reboxetine in amphetamine withdrawal syndrome

Amphetamine withdrawal can induce a condition with the symptoms of major depression. We report the case of a 46-year-old woman with antecedents of abuse of amphetamines and amphetamine derivatives from age 16 to age 41, who in the 5 years since withdrawal presented recurrent depression resistant to treatment. She was treated with maximum doses of selective serotonin reuptake inhibitors and lithium, but there was no remission of symptoms. On being treated with reboxetine, a selective noradrenaline reuptake inhibitor, euthymia was achieved, without negative after effects. Several studies have shown that noradrenaline plays an important role in the modulation of the response to amphetamines. The findings in this case suggest that reboxetine may constitute an interesting alternative for the treatment of amphetamine withdrawal syndrome (AWS).

Multi-target strategies for the improved treatment of depressive states: Conceptual foundations and neuronal substrates, drug discovery and therapeutic application

Major depression is a debilitating and recurrent disorder with a substantial lifetime risk and a high social cost. Depressed patients generally display co-morbid symptoms, and depression frequently accompanies other serious disorders. Currently available drugs display limited efficacy and a pronounced delay to onset of action, and all provoke distressing side effects. Cloning of the human genome has fuelled expectations that symptomatic treatment may soon become more rapid and effective, and that depressive states may ultimately be "prevented" or "cured". In pursuing these objectives, in particular for genome-derived, non-monoaminergic targets, "specificity" of drug actions is often emphasized. That is, priority is afforded to agents that interact exclusively with a single site hypothesized as critically involved in the pathogenesis and/or control of depression. Certain highly selective drugs may prove effective, and they remain indispensable in the experimental (and clinical) evaluation of the significance of novel mechanisms. However, by analogy to other multifactorial disorders, "multi-target" agents may be better adapted to the improved treatment of depressive states. Support for this contention is garnered from a broad palette of observations, ranging from mechanisms of action of adjunctive drug combinations and electroconvulsive therapy to "network theory" analysis of the etiology and management of depressive states. The review also outlines opportunities to be exploited, and challenges to be addressed, in the discovery and characterization of drugs recognizing multiple targets. Finally, a diversity of multi-target strategies is proposed for the more efficacious and rapid control of core and co-morbid symptoms of depression, together with improved tolerance relative to currently available agents.