Confronting the challenge of failed translation in medications development for substance use disorders.
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ABSTRACT:
SUBMITTER: Negus SS
PROVIDER: S-EPMC8418188 | biostudies-literature | 2021 Nov
REPOSITORIES: biostudies-literature
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Confronting the challenge of failed translation in medications development for substance use disorders.
Pharmacology, biochemistry, and behavior 20210828
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Project description:ObjectivesIn Ethiopia, little is known about the association between substance use disorders and adherence to antituberculosis (anti-TB) medications. Therefore, the objective of this study was to assess the effect of substance use disorders on adherence to anti-TB medications in Southwest Ethiopia.DesignProspective cohort study.SettingsPatients were recruited from 22 health centres and four hospitals in Southwest Ethiopia.ParticipantsThis study was conducted among 268 patients with TB, aged 18-80 in Southwest Ethiopia between October 2017 and October 2018. At baseline, patients who were exposed substance use disorders (134 patients) and unexposed to substance use disorders (134 patients) were recruited. Patients were followed for 6 months, and data were collected on three occasions.Main outcome measureAdherence to anti-TB medications.ResultsPatients with substance use disorders had consistently higher prevalence of non-adherence than those without, 16.4% versus 3.0% at baseline, 41.7% versus 14.4% at 2-month follow-up and 45.7% versus 10.8% at 6-month follow-up assessments. Patients with khat use disorder were 3.8 times more likely to be non-adherent to anti-TB medications than patients without khat use disorder (Adjusted odds ratio (aOR)=3.8, 95% CI 1.8 to 8.0). Patients who had alcohol use disorder (AUD) were also 3.2 times likely to have poor adherence compared with their counterparts (aOR=3.2, 95% CI 1.6 to 6.6). In addition, being educated (aOR=4.4, 95% CI 1.7 to 11.3), and being merchant (aOR=6.1, 95% CI 1.2 to 30.8) were associated with non-adherence to anti-TB medications.ConclusionKhat and AUDs predict greater likelihood of non-adherence to anti-TB medication. This implies the need to integrate the management for substance use disorders into the existing TB treatment services.
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Project description:Environmental contexts that are reliably associated with the use of pharmacologically active substances are hypothesized to contribute to substance use disorders. In this review, we provide an updated summary of parallel preclinical and human studies that support this hypothesis. Research conducted in rats shows that environmental contexts that are reliably paired with drug use can renew extinguished drug-seeking behavior and amplify responding elicited by discrete, drug-predictive cues. Akin to drug-associated contexts, interoceptive drug stimuli produced by the psychopharmacological effects of drugs can also influence learning and memory processes that play a role in substance use disorders. Findings from human laboratory studies show that drug-associated contexts, including social stimuli, can have profound effects on cue reactivity, drug use, and drug-related cognitive expectancies. This translationally relevant research supports the idea that treatments for substance use disorders could be improved by considering drug-associated contexts as a factor in treatment interventions. We conclude this review with ideas for how to integrate drug-associated contexts into treatment-oriented research based on 4 approaches: pharmacology, brain stimulation, mindfulness-based relapse prevention, and cognitive behavioral group therapy. Throughout, we focus on alcohol- and tobacco-related research, which are two of the most prevalent and commonly misused drugs worldwide for which there are known treatments.
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Project description:ObjectiveDespite growing interest in the use of evidence-based treatment practices for treating substance use disorders, adoption of medications by treatment programs remains modest. Drawing on resource dependence and institutional theory, this study examined the relationships between adoption of medications by treatment programs and their perceptions about the state policy environment.MethodsData were collected through mailed surveys and telephone interviews with 250 administrators of publicly funded substance abuse treatment programs in the United States between 2009 and 2010. Multiple imputation and multivariate logistic regression were used to estimate the associations between perceptions of the state policy environment and the odds of adopting at least one medication for the treatment of substance use disorders.ResultsA total of 91 (37%) programs reported having prescribed any medication for treatment of a substance use disorder. Programs were significantly more likely to have adopted at least one medication if they perceived greater support for medications by the Single State Agency. The odds of adoption were significantly greater if the program was aware that at least one medication was included on their state's Medicaid formulary and that state-contract funding permitted the purchase of medications.ConclusionsStates may play significant roles in promoting the adoption of medications, but adequate dissemination of information about state policies and priorities may be vital to further adoption. Future research should continue to study the relationships between the adoption of medications for treating substance use disorders and the evolving policy environment.
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Project description:Patients who suffer from alcohol use disorders (AUDs) usually go through various socio-behavioral and pathophysiological changes that take place in the brain and other organs. Recently, consumption of unhealthy food and excess alcohol along with a sedentary lifestyle has become a norm in both developed and developing countries. Despite the beneficial effects of moderate alcohol consumption, chronic and/or excessive alcohol intake is reported to negatively affect the brain, liver and other organs, resulting in cell death, organ damage/failure and death. The most effective therapy for alcoholism and alcohol related comorbidities is alcohol abstinence, however, chronic alcoholic patients cannot stop drinking alcohol. Therefore, targeted therapies are urgently needed to treat such populations. Patients who suffer from alcoholism and/or alcohol abuse experience harmful effects and changes that occur in the brain and other organs. Upon stopping alcohol consumption, alcoholic patients experience acute withdrawal symptoms followed by a protracted abstinence syndrome resulting in the risk of relapse to heavy drinking. For the past few decades, several drugs have been available for the treatment of AUDs. These drugs include medications to reduce or stop severe alcohol withdrawal symptoms during alcohol detoxification as well as recovery medications to reduce alcohol craving and support abstinence. However, there is no drug that completely antagonizes the adverse effects of excessive amounts of alcohol. This review summarizes the drugs which are available and approved by the FDA and their mechanisms of action as well as the medications that are under various phases of preclinical and clinical trials. In addition, the repurposing of the FDA approved drugs, such as anticonvulsants, antipsychotics, antidepressants and other medications, to prevent alcoholism and treat AUDs and their potential target mechanisms are summarized.
| S-EPMC5898984 | biostudies-literature
Project description:Addiction is a devastating disorder that produces persistent maladaptive changes to the central nervous system, including glial cells. Although there is an extensive body of literature examining the neuronal mechanisms of substance use disorders, effective therapies remain elusive. Glia, particularly microglia and astrocytes, have an emerging and meaningful role in a variety of processes beyond inflammation and immune surveillance, and may represent a promising therapeutic target. Indeed, glia actively modulate neurotransmission, synaptic connectivity and neural circuit function, and are critically poised to contribute to addictive-like brain states and behaviors. In this review, we argue that glia influence the cellular, molecular, and synaptic changes that occur in neurons following drug exposure, and that this cellular relationship is critically modified following drug exposure. We discuss direct actions of abused drugs on glial function through immune receptors, such as Toll-like receptor 4, as well as other mechanisms. We highlight how drugs of abuse affect glia-neural communication, and the profound effects that glial-derived factors have on neuronal excitability, structure, and function. Recent research demonstrates that glia have brain region-specific functions, and glia in different brain regions have distinct contributions to drug-associated behaviors. We will also evaluate the evidence demonstrating that glial activation is essential for drug reward and drug-induced dopamine release, and highlight clinical evidence showing that glial mechanisms contribute to drug abuse liability. In this review, we synthesize the extensive evidence that glia have a unique, pivotal, and underappreciated role in the development and maintenance of addiction.
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Project description:Genomics of Substance Use Disorders in Latin American Populations
| PRJNA1078494 | ENA
Project description:Genomics of Substance Use Disorders in Latin American Populations
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Project description:Abstract In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle?based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next?generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process?level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle?based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods. Key Points Microphysics is an important component of weather and climate models, but its representation in current models is highly uncertain Two critical challenges are identified: representing cloud and precipitation particle populations and knowledge gaps in cloud physics A possible blueprint for addressing these challenges is proposed to accelerate progress in improving microphysics schemes
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Project description:In contrast to traditional pharmacodynamic approaches to treat substance-use disorders (SUDs), the use of biologics (vaccines, monoclonal antibodies, and genetically modified enzymes) is based on a pharmacokinetic principle: reduce the amount of (and, ideally, eliminate) abused drug entering the central nervous system (CNS). Preclinical studies indicate that biologics are effective in both facilitating abstinence and preventing relapse to abused substances ranging from nicotine to heroin. While data are still emerging, the results from multiple clinical trials can best be described as mixed. Nonetheless, these clinical studies have already provided important insights using 'first-generation' tools that may inform the development of effective and commercially viable biologics to treat tobacco-, cocaine-, and methamphetamine-use disorders.
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Project description:BackgroundAlthough co-occurring conditions are common with substance use disorders (SUDs), estimation methods for joint health state utilities have not yet been tested in this context.ObjectivesTo compare joint health state utility estimators in SUD to inform economic evaluation.MethodsWe conducted two Internet-based surveys of US adults to collect community perspective standard gamble utilities for SUD and common co-occurring conditions. We evaluated six conditions as they occur individually and four combinations of these as they occur in tandem. We applied joint utility estimators using the six individual conditions' utilities to compare their performance relative to the observed combination states' utilities. We assessed performance with bias (estimated utility minus observed utility) and root mean square error (RMSE).ResultsUsing 3892 utilities from 1502 respondents, the minimum estimator was statistically unbiased (i.e., the 95% confidence interval included 0) for all combination states that we measured. The maximum estimator was unbiased for two states and the linear index and adjusted decrement estimators were unbiased for one state. The maximum estimator had the smallest RMSE for two combination states (back pain and prescription opioid misuse [0.0004] and injection crack and injection opioid use [0.0007]); the linear index and minimum estimators had the smallest RMSE for one combination state each. The additive and multiplicative estimators had the largest RMSE for all states.ConclusionsOur results demonstrate the usefulness of the minimum estimator in this context, and confirm the inadequacy of the additive and multiplicative estimators. Further research is needed to extend these results to other SUD states.
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