Trials In Autism Spectrum Disorder Research Articles

A Convolutional Deep Neural Network Approach to Predict Autism Spectrum Disorder Based on Eye-Tracking Scan Paths

Autism spectrum disorder (ASD) is a developmental disorder that encompasses difficulties in communication (both verbal and non-verbal), social skills, and repetitive behaviors. The diagnosis of autism spectrum disorder typically involves specialized procedures and techniques, which can be time-consuming and expensive. The accuracy and efficiency of the diagnosis depend on the expertise of the specialists and the diagnostic methods employed. To address the growing need for early, rapid, cost-effective, and accurate diagnosis of autism spectrum disorder, there has been a search for advanced smart methods that can automatically classify the disorder. Machine learning offers sophisticated techniques for building automated classifiers that can be utilized by users and clinicians to enhance accuracy and efficiency in diagnosis. Eye-tracking scan paths have emerged as a tool increasingly used in autism spectrum disorder clinics. This methodology examines attentional processes by quantitatively measuring eye movements. Its precision, ease of use, and cost-effectiveness make it a promising platform for developing biomarkers for use in clinical trials for autism spectrum disorder. The detection of autism spectrum disorder can be achieved by observing the atypical visual attention patterns of children with the disorder compared to typically developing children. This study proposes a deep learning model, known as T-CNN-Autism Spectrum Disorder (T-CNN-ASD), that utilizes eye-tracking scans to classify participants into ASD and typical development (TD) groups. The proposed model consists of two hidden layers with 300 and 150 neurons, respectively, and underwent 10 rounds of cross-validation with a dropout rate of 20%. In the testing phase, the model achieved an accuracy of 95.59%, surpassing the accuracy of other machine learning algorithms such as random forest (RF), decision tree (DT), K-Nearest Neighbors (KNN), and multi-layer perceptron (MLP). Furthermore, the proposed model demonstrated superior performance when compared to the findings reported in previous studies. The results demonstrate that the proposed model can accurately classify children with ASD from those with TD without human intervention.

Evaluation of clinical assessments of social abilities for use in autism clinical trials by the autism biomarkers consortium for clinical trials.

Clinical trials in autism spectrum disorder (ASD) often rely on clinician rating scales and parent surveys to measure autism-related features and social behaviors. To aid in the selection of these assessments for future clinical trials, the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) directly compared eight common instruments with respect to acquisition rates, sensitivity to group differences, equivalence across demographic sub-groups, convergent validity, and stability over a 6-week period. The sample included 280 children diagnosed with ASD (65 girls) and 119 neurotypical children (36 girls) aged from 6 to 11 years. Full scale IQ for ASD ranged from 60 to 150 and for neurotypical ranged from 86 to 150. Instruments measured clinician global assessment and autism-related behaviors, social communication abilities, adaptive function, and social withdrawal behavior. For each instrument, we examined only the scales that measured social or communication functioning. Data acquisition rates were at least 97.5% at T1 and 95.7% at T2. All scales distinguished diagnostic groups. Some scales significantly differed by participant and/or family demographic characteristics. Within the ASD group, most clinical instruments exhibited weak (≥ |0.1|) to moderate (≥ |0.4|) intercorrelations. Short-term stability was moderate (ICC: 0.5-0.75) to excellent (ICC: >0.9) within the ASD group. Variations in the degree of stability may inform viability for different contexts of use, such as identifying clinical subgroups for trials versus serving as a modifiable clinical outcome. All instruments were evaluated in terms of their advantages and potential concerns for use in clinical trials.

The Autism Biomarkers Consortium for Clinical Trials: evaluation of a battery of candidate eye-tracking biomarkers for use in autism clinical trials

BackgroundEye tracking (ET) is a powerful methodology for studying attentional processes through quantification of eye movements. The precision, usability, and cost-effectiveness of ET render it a promising platform for developing biomarkers for use in clinical trials for autism spectrum disorder (ASD).MethodsThe Autism Biomarkers Consortium for Clinical Trials conducted a multisite, observational study of 6–11-year-old children with ASD (n = 280) and typical development (TD, n = 119). The ET battery included: Activity Monitoring, Social Interactive, Static Social Scenes, Biological Motion Preference, and Pupillary Light Reflex tasks. A priori, gaze to faces in Activity Monitoring, Social Interactive, and Static Social Scenes tasks were aggregated into an Oculomotor Index of Gaze to Human Faces (OMI) as the primary outcome measure. This work reports on fundamental biomarker properties (data acquisition rates, construct validity, six-week stability, group discrimination, and clinical relationships) derived from these assays that serve as a base for subsequent development of clinical trial biomarker applications.ResultsAll tasks exhibited excellent acquisition rates, met expectations for construct validity, had moderate or high six-week stabilities, and highlighted subsets of the ASD group with distinct biomarker performance. Within ASD, higher OMI was associated with increased memory for faces, decreased autism symptom severity, and higher verbal IQ and pragmatic communication skills.LimitationsNo specific interventions were administered in this study, limiting information about how ET biomarkers track or predict outcomes in response to treatment. This study did not consider co-occurrence of psychiatric conditions nor specificity in comparison with non-ASD special populations, therefore limiting our understanding of the applicability of outcomes to specific clinical contexts-of-use. Research-grade protocols and equipment were used; further studies are needed to explore deployment in less standardized contexts.ConclusionsAll ET tasks met expectations regarding biomarker properties, with strongest performance for tasks associated with attention to human faces and weakest performance associated with biological motion preference. Based on these data, the OMI has been accepted to the FDA’s Biomarker Qualification program, providing a path for advancing efforts to develop biomarkers for use in clinical trials.

5.2 NURTURING NEUROMODULATION IN CHILD AND ADOLESCENT PSYCHIATRY: LESSONS LEARNED FROM RECENT STUDIES IN AUTISM SPECTRUM DISORDER AND DEPRESSION

The objective of this presentation is to review recent neuromodulation research focused on child and adolescent psychiatry to facilitate a discussion of research design challenges, safety concerns, ethics, regulatory compliance, and future directions. A clinical child and adolescent psychiatry researcher focused on adapting transcranial magnetic stimulation (TMS) for youth will review recent studies as a framework for discussing ethical, regulatory, safety, and research design challenges. The research design and results from recent randomized controlled trials in autism spectrum disorder (ASD) and depression will be highlighted. One recent randomized controlled trial of TMS for MDD (n = 103) demonstrated a change in depressive symptom severity and encouraging tolerability and safety findings. However, the change in depressive symptoms across 6 weeks was not significantly different than sham stimulation. Another recent, double-blind, sham controlled, pilot study of TMS treatment for executive function deficits in ASD (n = 40) also demonstrated the feasibility, tolerability, and safety of TMS. However, TMS treatment did not differ from sham stimulation with respect to improvement in executive function performance. Recent commentaries have highlighted the safety and ethical considerations of adapting brain stimulation treatments for youth. Conversely, recent efforts with trigeminal nerve stimulation demonstrated efficacy for ADHD. Recent findings examining brain stimulation interventions in youth highlight the well-known challenges related to pharmacology studies in children and adolescents. However, brain stimulation interventions add another layer of complexity for research designs and ethical considerations. Future studies must carefully consider dosing parameters, brain state, targeting, and efforts to mitigate the placebo effect. Long-term outcome measures with respect to efficacy and safety are lacking in the current evidence base. Future efforts will require innovative approaches and unique collaborations.

The promise of precision medicine in autism

Autism spectrum disorder (ASD) is a clinically and etiologically diverse developmental condition characterized by diminished social interactions, impaired communication, and repetitive and/or restrictive behaviors. Recent advances in ASD genetics pave the way for implementation of precision medicine in clinical management of autism.

Moral obligations in conducting stem cell-based therapy trials for autism spectrum disorder

Unregulated patient treatments and approved clinical trials have been conducted with haematopoietic stem cells and mesenchymal stem cells for children with autism spectrum disorder (ASD). While the former direct-to-consumer practice...

New Strategies for Clinical Trials in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition that poses several challenges in terms of clinical diagnosis and investigation of molecular etiology. The lack of knowledge on the pathogenic mechanisms underlying ASD has hampered the clinical trials that so far have tried to target ASD behavioral symptoms. In order to improve our understanding of the molecular abnormalities associated with ASD, a deeper and more extensive genetic profiling of targeted individuals with ASD was needed. The recent availability of new and more powerful sequencing technologies (third-generation sequencing) has allowed to develop novel strategies for the characterization of comprehensive genetic profiles of individuals with ASD. In particular, this review will describe integrated approaches based on the combination of various omics technologies that will lead to a better stratification of targeted cohorts for the design of clinical trials in ASD. In order to analyze the big data collected by assays such as the whole genome, epigenome, transcriptome, and proteome, it is critical to develop an efficient computational infrastructure. Machine learning models are instrumental to identify non-linear relationships between the omics technologies and, therefore, establish a functional informative network among the different data sources. The potential advantage provided by these new integrated omics-based strategies is better characterization of the genetic background of ASD cohorts, to identify novel molecular targets for drug development, and ultimately offer a more personalized approach in the design of clinical trials for ASD.

The NIMH 'Fast-Fail Trials' (FAST) Initiative: Rationale, Promise, and Progress.

In 2012, the US National Institute of Mental Health launched three clinical trial contracts under a new FAST initiative. The overall goal for these contracts (Fast-Fail Trials) was to focus early-stage trials, testing novel pharmacologic agents that target the central nervous system, on pharmacologic-based designs to objectively identify doses that produce central nervous system effects. The three contracts targeted different psychiatric populations: psychotic (FAST-PS), mood and anxiety (FAST-MAS), and autism spectrum disorders (FAST-AS). The FAST initiative was a first attempt for the National Institute of Mental Health to adapt an experimental medicine approach to its clinical trial portfolio. As the Fast-Fail trials implemented this new approach for the field, we present the rationale for each trial, design considerations, results, and how each one contributed new knowledge to the field of psychopharmacology; important lessons for pharma and biotech. Under the FAST initiative, the National Institute of Mental Health assembled research teams with a broad range of expertise, who developed and validated the outcome measures and study protocol, and conducted multi-site clinical trials, testing candidate compounds. In the FAST-PS contract, the team validated an imaging-based pharmacodynamic biomarker of the effect of ketamine in the brain that could be utilized in subsequent clinical trials. The initial FAST-AS study was an important first step in the design of early-stage target-engagement trials in autism spectrum disorder, suggesting that a resting electroencephalogram can be used as a pharmacodynamic measure in future studies. The FAST-MAS study showed that blocking the kappa-opioid receptor significantly affects functional magnetic resonance imaging ventral striatal activation in the monetary incentive delay task in anticipation of gain. Together, the outcomes of the FAST-FAIL trials demonstrated the importance of rigorously designed and informative central nervous system trials, including the value of pharmacodynamic measures in early-stage trials. Use of these measures furthered our knowledge about the relationship between specific molecular mechanisms, brain effects, and therapeutic effects in patients with mental illnesses.

What are we targeting when we treat autism spectrum disorder? A systematic review of 406 clinical trials.

The number of trials aimed at evaluating treatments for autism spectrum disorder has been increasing progressively. However, it is not clear which outcome measures should be used to assess their efficacy, especially for treatments which target core symptoms. The present review aimed to provide a comprehensive overview regarding the outcome measures used in clinical trials for people with autism spectrum disorder. We systematically searched the Web of KnowledgeSM database between 1980 and 2016 to identify published controlled trials investigating the efficacy of interventions in autism spectrum disorder. We included 406 trials in the final database, from which a total of 327 outcome measures were identified. Only seven scales were used in more than 5% of the studies, among which only three measured core symptoms (Autism Diagnostic Observation Schedule, Childhood Autism Rating Scale, and Social Responsiveness Scale). Of note, 69% of the tools were used in the literature only once. Our systematic review has shown that the evaluation of efficacy in intervention trials for autism spectrum disorder relies on heterogeneous and often non-specific tools for this condition. The fragmentation of tools may significantly hamper the comparisons between studies and thus the discovery of effective treatments for autism spectrum disorder. Greater consensus regarding the choice of these measures should be reached.

Systematic Review: Distribution of Age and Intervention Modalities in Therapeutic Clinical Trials for Autism Spectrum Disorder.

The prevalence of ASD remains relatively stable across the lifespan, necessitating a quantitative understanding of how intervention clinical research is applied across age groups. Here we report a systematic review of treatment studies between 2013 and 2017, enrolling 11,213 subjects with ASD in 218 studies. Individuals under 18years old constituted the majority of studies (84%) and subjects (92%). Subjects under 18years old were more likely to be enrolled in behavioral studies (OR (CI) = 1.34 (1.17-1.54)), and less likely to be enrolled in pharmacological (OR = 0.60 (0.52-0.69)) studies than subjects ≥ 18years old. Identified disparities in both intervention modalities and outcome measures should serve to guide future research priorities.

Clinical trials in autism spectrum disorder: evidence, challenges and future directions.

The purpose of this manuscript is to review the evidence generated by clinical trials of pharmaceuticals in autism spectrum disorder (ASD), describe challenges in the conduct of such trials, and discuss future directions RECENT FINDINGS: Clinical trials in ASD have produced several compounds to adequately support the pharmacological treatment of associated symptom domains: attention deficit hyperactivity disorder (methylphenidate, atomoxetine, and alpha agonists), irritability/aggression (risperidone and aripiprazole), sleep (melatonin), and weight gain associated with atypical antipsychotic use (metformin). However, there is no evidence yet to support the routine use of pharmaceuticals for the treatment of core symptom domains. Challenges in the field include biological heterogeneity within ASD, lack of biomarkers that clarify biological heterogeneity or predict response to treatment, lack of data across the lifespan, and suboptimal outcome measures. Several compounds have evidence for the treatment of co-occurring symptoms in children and youth with ASD, although pharmacological interventions for core symptoms are still lacking. Identifying the various biologies underling ASD and developing biomarkers that stratify biologically homogeneous populations are both necessary to realize the promise of precision medicine in ASD.

Commentary: Randomized controlled trials in autism spectrum disorder: state of the field and challenges for the future.

This issue of the Journal includes two articles summarizing the evidence from clinical trials aimed at improving symptoms of autism. French and Kennedy (Journal of Child Psychology and Psychiatry, 2018, xx, xxxx) systematically review randomized controlled trials (RCTs) aimed at an "early intervention" and focus on trials including children with or at risk of autism under age 6years. Although no type of intervention were excluded from their review, none of the included 48 RCTs employed pharmacological modalities and the overwhelming majority tested psychological/behavioural interventions aimed at modifying aspects of observed behaviours that are abnormal in children with autism. Using the standard Cochrane tool for evaluating risk of bias, French and Kennedy conclude that many RCTs are of low quality, which throws into question the reliance that should be placed on the findings.

Assessing Risk of Bias in Randomized Controlled Trials for Autism Spectrum Disorder.

To determine construct validity and reliability indicators of the Cochrane risk of bias (RoB) tool in the context of randomized clinical trials (RCTs) for autism spectrum disorder (ASD). Confirmatory factor analysis was used to evaluate a unidimensional model consisting of 9 RoB categorical indicators evaluated across 94 RCTs addressing interventions for ASD. Only five of the nine original RoB items returned good fit indices and so were retained in the analysis. Only one of this five had very high factor loadings. The remaining four indicators had more measurement error than common variance with the RoB latent factor. Together, the five indicators showed poor reliability (ω = 0.687; 95% CI: 0.613-0.761). Although the Cochrane model of RoB for ASD exhibited good fit indices, the majorities of the items have more residual variance than common variance and, therefore, did not adequately capture the RoB in ASD intervention trials.

Autism spectrum disorders: linking neuropathological findings to treatment with transcranial magnetic stimulation.

Postmortem studies in autism spectrum disorder (ASD) individuals indicate the presence of abnormalities within the peripheral neuropil space (PNS) of cortical minicolumns. The geometrical orientation of inhibitory elements within the PNS suggests using repetitive transcranial magnetic stimulation (rTMS) to up-regulate their activity. Several rTMS trials in ASD have shown marked improvements in motor symptomatology, attention and perceptual binding. rTMS is the first therapeutic attempt at ASD aimed at correcting some of its core pathology.

A review of traditional and novel treatments for seizures in autism spectrum disorder: findings from a systematic review and expert panel.

Despite the fact that seizures are commonly associated with autism spectrum disorder (ASD), the effectiveness of treatments for seizures has not been well studied in individuals with ASD. This manuscript reviews both traditional and novel treatments for seizures associated with ASD. Studies were selected by systematically searching major electronic databases and by a panel of experts that treat ASD individuals. Only a few anti-epileptic drugs (AEDs) have undergone carefully controlled trials in ASD, but these trials examined outcomes other than seizures. Several lines of evidence point to valproate, lamotrigine, and levetiracetam as the most effective and tolerable AEDs for individuals with ASD. Limited evidence supports the use of traditional non-AED treatments, such as the ketogenic and modified Atkins diet, multiple subpial transections, immunomodulation, and neurofeedback treatments. Although specific treatments may be more appropriate for specific genetic and metabolic syndromes associated with ASD and seizures, there are few studies which have documented the effectiveness of treatments for seizures for specific syndromes. Limited evidence supports l-carnitine, multivitamins, and N-acetyl-l-cysteine in mitochondrial disease and dysfunction, folinic acid in cerebral folate abnormalities and early treatment with vigabatrin in tuberous sclerosis complex. Finally, there is limited evidence for a number of novel treatments, particularly magnesium with pyridoxine, omega-3 fatty acids, the gluten-free casein-free diet, and low-frequency repetitive transcranial magnetic simulation. Zinc and l-carnosine are potential novel treatments supported by basic research but not clinical studies. This review demonstrates the wide variety of treatments used to treat seizures in individuals with ASD as well as the striking lack of clinical trials performed to support the use of these treatments. Additional studies concerning these treatments for controlling seizures in individuals with ASD are warranted.