Importance The prevalence of and mortality associated with methamphetamine use has doubled during the past 10 years. There is evidence suggesting that methamphetamine use disorder could be the next substance use crisis in the United States and possibly worldwide. Observation The neurobiology of methamphetamine use disorder extends beyond the acute effect of the drug as a monoaminergic modulator and includes intracellular pathways focused on oxidative stress, neurotoxic and excitotoxic effects, and neuroinflammation. Similarly, the clinical picture extends beyond the acute psychostimulatory symptoms to include complex cardiovascular and cerebrovascular signs and symptoms that need to be identified by the clinician. Although there are no pharmacologic treatments for methamphetamine use disorder, cognitive behavioral therapy, behavioral activation, and contingency management show modest effectiveness. Conclusions and Relevance There is a need to better understand the complex neurobiology of methamphetamine use disorder and to develop interventions aimed at novel biological targets. Parsing the disorder into different processes (eg, craving or mood-associated alterations) and targeting the neural systems and biological pathways underlying these processes may lead to greater success in identifying disease-modifying interventions. Finally, mental health professionals need to be trained in recognizing early cardiovascular and cerebrovascular warning signs to mitigate the mortality associated with methamphetamine use disorder.

Neurobiology, Clinical Presentation, and Treatment of Methamphetamine Use Disorder: A Review

Background The use of naltrexone plus bupropion to treat methamphetamine use disorder has not been well studied. Methods We conducted this multisite, double-blind, two-stage, placebo-contr...

https://www.nejm.org/doi/pdf/10.1056/NEJMoa2020214

Bupropion and Naltrexone in Methamphetamine Use Disorder

Aims Stimulant use disorder contributes to a substantial worldwide burden of disease, although evidence-based treatment options are limited This systematic review of reviews aims to: (i) synthesize the available evidence on both psychosocial and pharmacological interventions for the treatment of stimulant use disorder; (ii) identify the most effective therapies to guide clinical practice, and (iii) highlight gaps for future study Methods A systematic database search was conducted to identify systematic reviews and meta-analyses Eligible studies were those that followed standard systematic review methodology and assessed randomized controlled trials focused on the efficacy of interventions for stimulant use disorder Articles were critically appraised using an assessment tool adapted from Palmeteer et al and categorized for quality as ‘core’ or ‘supplementary’ reviews Evidence from the included reviews were further synthesized according to pharmacological or non-pharmacological management themes Results Of 476 identified records, 29 systematic reviews examining eleven intervention modalities were included The interventions identified include: contingency management, cognitive behavioural therapy, acupuncture, antidepressants, dopamine agonists, antipsychotics, anticonvulsants, disulfiram, opioid agonists, N-Acetylcysteine, and psychostimulants There was sufficient evidence to support the efficacy of contingency management programs for treatment of stimulant use disorder Psychostimulants, n-acetylcysteine, opioid agonist therapy, disulfiram and antidepressant pharmacological interventions were found to have insufficient evidence to support or discount their use Results of this review do not support the use of all other treatment options Conclusions The results of this review supports the use of contingency management interventions for the treatment of stimulant use disorder Although evidence to date is insufficient to support the clinical use of psychostimulants, our results demonstrate potential for future research in this area Given the urgent need for effective pharmacological treatments for stimulant use disorder, high-quality primary research focused on the role of psychostimulant medications for the treatment of stimulant use disorder is needed

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Treatment of stimulant use disorder: A systematic review of reviews.

Importance Substance use disorders (SUDs) represent a pressing public health concern Combined behavioral and pharmacological interventions are considered best practices for addiction Cognitive behavioral therapy (CBT) is a first-line intervention, yet the superiority of CBT compared with other behavioral treatments when combined with pharmacotherapy remains unclear An understanding of the effects of combined CBT and pharmacotherapy will inform best-practice guidelines for treatment of SUD Objective To conduct a meta-analysis of the published literature on combined CBT and pharmacotherapy for adult alcohol use disorder (AUD) or other SUDs Data Sources PubMed, Cochrane Register, MEDLINE, PsychINFO, and Embase databases from January 1, 1990, through July 31, 2019, were searched Keywords were specified in 3 categories: treatment type, outcome type, and study design Collected data were analyzed through September 30, 2019 Study Selection Two independent raters reviewed abstracts and full-text articles English language articles describing randomized clinical trials examining CBT in combination with pharmacotherapy for AUD and SUD were included Data Extraction and Synthesis Inverse-variance weighted, random-effects estimates of effect size were pooled into 3 clinically informative subgroups: (1) CBT plus pharmacotherapy compared with usual care plus pharmacotherapy, (2) CBT plus pharmacotherapy compared with another specific therapy plus pharmacotherapy, and (3) CBT added to usual care and pharmacotherapy compared with usual care and pharmacotherapy alone Sensitivity analyses included assessment of study quality, pooled effect size heterogeneity, publication bias, and primary substance moderator effects Main Outcomes and Measures Substance use frequency and quantity outcomes after treatment and during follow-up were examined Results The sample included 62 effect sizes from 30 unique randomized clinical trials that examined CBT in combination with some form of pharmacotherapy for AUD and SUD The primary substances targeted in the clinical trial sample were alcohol (15 [50%]), followed by cocaine (7 [23%]) and opioids (6 [20%]) The mean (SD) age of the patient sample was 39 (6) years, with a mean (SD) of 28% (12%) female participants per study The following pharmacotherapies were used: naltrexone hydrochloride and/or acamprosate calcium (26 of 62 effect sizes [42%]), methadone hydrochloride or combined buprenorphine hydrochloride and naltrexone (11 of 62 [18%]), disulfiram (5 of 62 [8%]), and another pharmacotherapy or mixture of pharmacotherapies (20 of 62 [32%]) Random-effects pooled estimates showed a benefit associated with combined CBT and pharmacotherapy over usual care (grange, 018-028;k = 9) However, CBT did not perform better than another specific therapy, and evidence for the addition of CBT as an add-on to combined usual care and pharmacotherapy was mixed Moderator analysis showed variability in effect direction and magnitude by primary drug target Conclusions and Relevance The present study supports the efficacy of combined CBT and pharmacotherapy compared with usual care and pharmacotherapy Cognitive behavioral therapy did not perform better than another evidence-based modality (eg, motivational enhancement therapy, contingency management) in this context or as an add-on to combined usual care and pharmacotherapy These findings suggest that best practices in addiction treatment should include pharmacotherapy plus CBT or another evidence-based therapy, rather than usual clinical management or nonspecific counseling services

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Combined Pharmacotherapy and Cognitive Behavioral Therapy for Adults With Alcohol or Substance Use Disorders: A Systematic Review and Meta-analysis.

Non-pharmacological interventions for methamphetamine use disorder: a systematic review.

Aims Addiction to methamphetamine/amphetamine (MA/A) is a major public health problem. Currently there are no pharmacotherapies for MA/A use disorder that have been approved for use by the US Food and Drug Administration or the European Medicines Agency. We reviewed the effectiveness of pharmacotherapy for MA/A use disorder to assess the quality, publication bias and overall strength of the evidence. Methods Systematic review and meta-analysis. We searched multiple data sources (MEDLINE, PsycINFO and Cochrane Library) to April 2019 for systematic reviews (SRs) and randomized controlled trials (RCTs). Included studies recruited adults who had MA/A use disorder; sample sizes ranged from 19 to 229 participants. Outcomes of interest were abstinence, defined as 3 or more consecutive weeks with negative urine drug screens (UDS); overall use, analyzed as the proportion of MA/A negative UDS specimens; and treatment retention. One SR of pharmacotherapies for MA/A use disorder and 17 additional RCTs met our inclusion criteria encompassing 17 different drugs (antidepressants, antipsychotics, psychostimulants, anticonvulsants and opioid antagonists). We combined the findings of trials with comparable interventions and outcome measures in random-effects meta-analyses. We assessed quality, publication bias and the strength of evidence for each outcome using standardized criteria. Results There was low-strength evidence from two RCTs that methylphenidate may reduce MA/A use: 6.5 versus 2.8% MA/A-negative UDS in one study (n = 34, P = 0.008) and 23 versus 16% in another study (n = 54, P = 0.047). Antidepressants as a class had no statistically significant effect on abstinence or retention on the basis of moderate strength evidence. Studies of anticonvulsants, antipsychotics (aripiprazole), opioid antagonists (naltrexone), varenicline and atomoxetine provided either low-strength or insufficient evidence of no effect on the outcomes of interest. Many of the studies had high or unclear risk of bias. Conclusions On the basis of low- to moderate-strength evidence, most medications evaluated for methamphetamine/amphetamine use disorder have not shown a statistically significant benefit. However, there is low-strength evidence that methylphenidate may reduce use.

Pharmacotherapy for methamphetamine/amphetamine use disorder-a systematic review and meta-analysis

Currently, there are no accepted FDA-approved pharmacotherapies for cocaine use disorder, though numerous medications have been tested in clinical trials. We conducted a systematic review and meta-analysis to better understand the effectiveness of pharmacotherapy for cocaine use disorder. We searched multiple data sources (MEDLINE, PsycINFO, and Cochrane Library) through November 2017 for systematic reviews and randomized controlled trials (RCTs) of pharmacological interventions in adults with cocaine use disorder. When possible, we combined the findings of trials with comparable interventions and outcome measures in random-effects meta-analyses. We assessed the risk of bias of individual trials and the strength of evidence for each outcome using standardized criteria. Outcomes included continuous abstinence (3+ consecutive weeks); cocaine use; harms; and study retention. For relapse prevention studies (participants abstinent at baseline), we examined lapse (first cocaine positive or missing UDS) and relapse (two consecutive cocaine positive or missed UDS′). Sixty-six different drugs or drug combinations were studied in seven systematic reviews and 48 RCTs that met inclusion criteria. Antidepressants were the most widely studied drug class (38 RCTs) but appear to have no effect on cocaine use or treatment retention. Increased abstinence was found with bupropion (2 RCTs: RR 1.63, 95% CI 1.02 to 2.59), topiramate (2 RCTs: RR 2.56, 95% CI 1.39 to 4.73), and psychostimulants (14 RCTs: RR 1.36, 95% CI 1.05 to 1.77), though the strength of evidence for these findings was low. We found moderate strength of evidence that antipsychotics improved treatment retention (8 RCTs: RR 1.33, 95% CI 1.03 to 1.75). Most of the pharmacotherapies studied were not effective for treating cocaine use disorder. Bupropion, psychostimulants, and topiramate may improve abstinence, and antipsychotics may improve retention. Contingency management and behavioral interventions along with pharmacotherapy should continue to be explored. Prospero CRD42018085667

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Pharmacotherapy for Cocaine Use Disorder—a Systematic Review and Meta-analysis

This report documents the programme and the outcomes of Dagstuhl Seminar 22382"Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling". Today's scientific challenges are characterised by complexity. Interconnected natural, technological, and human systems are influenced by forces acting across time- and spatial-scales, resulting in complex interactions and emergent behaviours. Understanding these phenomena -- and leveraging scientific advances to deliver innovative solutions to improve society's health, wealth, and well-being -- requires new ways of analysing complex systems. The transformative potential of AI stems from its widespread applicability across disciplines, and will only be achieved through integration across research domains. AI for science is a rendezvous point. It brings together expertise from $\mathrm{AI}$ and application domains; combines modelling knowledge with engineering know-how; and relies on collaboration across disciplines and between humans and machines. Alongside technical advances, the next wave of progress in the field will come from building a community of machine learning researchers, domain experts, citizen scientists, and engineers working together to design and deploy effective AI tools. This report summarises the discussions from the seminar and provides a roadmap to suggest how different communities can collaborate to deliver a new wave of progress in AI and its application for scientific discovery.

AI for Science: An Emerging Agenda

This report documents the programme and the outcomes of Dagstuhl Seminar 22382 “Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling”. Today’s scientific challenges are characterised by complexity. Interconnected natural, technological, and human systems are influenced by forces acting across time- and spatial-scales, resulting in complex interactions and emergent behaviours. Understanding these phenomena – and leveraging scientific advances to deliver innovative solutions to improve society’s health, wealth, and well-being – requires new ways of analysing complex systems. The transformative potential of AI stems from its widespread applicability across disciplines, and will only be achieved through integration across research domains. AI for science is a rendezvous point. It brings together expertise from AI and application domains; combines modelling knowledge with engineering know-how; and relies on collaboration across disciplines and between humans and machines. Alongside technical advances, the next wave of progress in the field will come from building a community of machine learning researchers, domain experts, citizen scientists, and engineers working together to design and deploy effective AI tools. This report summarises the discussions from the seminar and provides a roadmap to suggest how different communities can collaborate to deliver a new wave of progress in AI and its application for scientific discovery.

Jessica Montgomery

Papers

Pharmacotherapy for methamphetamine/amphetamine use disorder-a systematic review and meta-analysis

Pharmacotherapy for Cocaine Use Disorder—a Systematic Review and Meta-analysis

AI for Science: An Emerging Agenda

Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling (Dagstuhl Seminar 22382)