Qualitative evaluation of the Autism Behavior Inventory: use of cognitive interviewing to establish validity of a caregiver report scale for autism spectrum disorder.

PURPOSE: The Autism Behavior Inventory (ABI) is an observer-reported outcome scale measuring core and associated features of autism spectrum disorder (ASD). Extensive scale development (reported elsewhere) took place, in alignment with the Food and Drug Administration's patient-reported outcome guidance, to address the need for instruments to measure change and severity of ASD symptoms. METHODS: Cognitive interviewing was used to confirm understanding and content validity of the scale prior to its use in clinical trials. Respondents were caregivers of individuals with ASD (N = 50). Interviews used a hybrid of the "think-aloud" and verbal probing approach to assess ABI's content validity and participant understanding of the instrument, including: item clarity and relevance; item interpretation; appropriateness of response scales; and clarity of instructions. Audio-recordings of the interviews were transcribed for qualitative data analysis. The scale was revised based on participant feedback and tested in a second round of interviews (round 1 N = 38, round 2 N = 12). RESULTS: In total, 67/70 items reached ≥ 90% understandability across participants. Caregivers were able to select an appropriate response from the options available and reported finding the examples helpful. Based on participant feedback, instructions were simplified, 8 items were removed, and 10 items were reworded. The final revised 62-item scale was presented in round 2, where caregivers reported readily understanding the instructions, response options, and 61/62 items reached ≥ 90% understandability. CONCLUSIONS: Cognitive interviews with caregivers of a diverse sample of individuals with ASD confirm the content validity and relevance of the ABI to assess core and associated symptoms of ASD.

Impaired mitochondrial function in psychiatric disorders.

Major psychiatric illnesses such as mood disorders and schizophrenia are chronic, recurrent mental illnesses that affect the lives of millions of individuals. Although these disorders have traditionally been viewed as 'neurochemical diseases', it is now clear that they are associated with impairments of synaptic plasticity and cellular resilience. Although most patients with these disorders do not have classic mitochondrial disorders, there is a growing body of evidence to suggest that impaired mitochondrial function may affect key cellular processes, thereby altering synaptic functioning and contributing to the atrophic changes that underlie the deteriorating long-term course of these illnesses. Enhancing mitochondrial function could represent an important avenue for the development of novel therapeutics and also presents an opportunity for a potentially more efficient drug-development process.

Down syndrome and Alzheimer's disease: Common pathways, common goals.

In the United States, estimates indicate there are between 250,000 and 400,000 individuals with Down syndrome (DS), and nearly all will develop Alzheimer's disease (AD) pathology starting in their 30s. With the current lifespan being 55 to 60 years, approximately 70% will develop dementia, and if their life expectancy continues to increase, the number of individuals developing AD will concomitantly increase. Pathogenic and mechanistic links between DS and Alzheimer's prompted the Alzheimer's Association to partner with the Linda Crnic Institute for Down Syndrome and the Global Down Syndrome Foundation at a workshop of AD and DS experts to discuss similarities and differences, challenges, and future directions for this field. The workshop articulated a set of research priorities: (1) target identification and drug development, (2) clinical and pathological staging, (3) cognitive assessment and clinical trials, and (4) partnerships and collaborations with the ultimate goal to deliver effective disease-modifying treatments.

Pharmacokinetics and safety of adjunctive topiramate in infants (1-24 months) with refractory partial-onset seizures: a randomized, multicenter, open-label phase 1 study.

PURPOSE: To characterize the pharmacokinetics of adjunctive topiramate in infants (1-24 months) with refractory partial-onset seizures (POS); also to evaluate safety and tolerability of topiramate in the dose range of 3-25 mg/kg/day. METHODS: In this open-label phase 1 study, infants (N = 55) with refractory POS receiving at least one concurrent antiepileptic drug (AED) were enrolled. Infants were stratified by age and randomly assigned to one of four topiramate target dose groups (3-, 5-, 15-, or 25 mg/kg/day). Treatment was initiated at 3 mg/kg/day with titration to the target dose by weekly dose escalation. Topiramate was administered daily in two divided doses as oral liquid (5 mg/ml for infants <9 kg or those who could not tolerate solid foods) or sprinkle capsule (25 mg) formulations. Following seven consecutive days of topiramate administration at the target dose, four blood samples were collected from each infant for pharmacokinetic assessments (predose, 1-3, 4-6, and 8-10 h postdose). KEY FINDINGS: Fifty-five infants (mean [SD] age in months: 11.4 [5.79]) with POS were enrolled, of whom 33% had seizures with or without secondary generalization. Complete pharmacokinetic profiles were obtained in 35 infants in whom mean plasma topiramate concentration-time profiles demonstrated linear pharmacokinetics (predose topiramate concentrations [C(trough) ] and area under the plasma concentration-time curve from time 0 through 12 h [AUC(12 h)]) of topiramate over the dose range studied). Apparent steady state oral clearance (CL(ss) /F) remained similar across all topiramate target dose groups and was independent of creatinine clearance, age, and weight. Mean values for CL(ss) /F were approximately twofold greater in infants receiving concomitant enzyme-inducing AEDs versus enzyme-inhibiting AEDs. Topiramate was well tolerated and safety findings were consistent with previous reports in children and adults. Most common treatment emergent adverse events (≥10%) were upper respiratory tract infection, fever, vomiting, somnolence, and anorexia. SIGNIFICANCE: In infants (1-24 months), topiramate exhibited linear steady state pharmacokinetics over the dose range 3-25 mg/kg/day, and CL(ss) /F of topiramate was independent of dose. Moreover, the concomitant enzyme-inducing AEDs doubled the clearance of topiramate. Topiramate was generally well tolerated as adjunctive therapy at doses up to 25 mg/kg/day.

A platform trial approach to proof-of-concept (POC) studies in autism spectrum disorder: Autism spectrum POC initiative (ASPI).

Background: Over the past decade, autism spectrum disorder (ASD) research has blossomed, and multiple clinical trials have tested potential interventions, with varying results and no clear demonstration of efficacy. Lack of clarity concerning appropriate biological mechanisms to target and lack of sensitive, objective tools to identify subgroups and measure symptom changes have hampered the efforts to develop treatments. A platform trial for proof-of-concept studies in ASD could help address these issues. A major goal of a platform trial is to find the best treatment in the most expeditious manner, by simultaneously investigating multiple treatments, using specialized statistical tools for allocation and analysis. We describe the setup of a platform trial and perform simulations to evaluate the operating characteristics under several scenarios. We use the Autism Behavior Inventory (ABI), a psychometrically validated web-based rating scale to measure the change in ASD core and associated symptoms. Methods: Detailed description of the setup, conduct, and decision-making rules of a platform trial are explained. Simulations of a virtual platform trial for several scenarios are performed to compare operating characteristics. The success and futility criteria for treatments are based on a Bayesian posterior probability model. Results: Overall, simulation results show the potential gain in terms of statistical properties especially for improved decision-making ability, while careful planning is needed due to the complexities of a platform trial. Conclusions: Autism research, shaped particularly by its heterogeneity, may benefit from the platform trial approach for POC clinical studies.

Personalized relapse prediction in patients with major depressive disorder using digital biomarkers.

Major depressive disorder (MDD) is a chronic illness wherein relapses contribute to significant patient morbidity and mortality. Near-term prediction of relapses in MDD patients has the potential to improve outcomes by helping implement a 'predict and preempt' paradigm in clinical care. In this study, we developed a novel personalized (N-of-1) encoder-decoder anomaly detection-based framework of combining anomalies in multivariate actigraphy features (passive) as triggers to utilize an active concurrent self-reported symptomatology questionnaire (core symptoms of depression and anxiety) to predict near-term relapse in MDD. The framework was evaluated on two independent longitudinal observational trials, characterized by regular bimonthly (every other month) in-person clinical assessments, weekly self-reported symptom assessments, and continuous activity monitoring data with two different wearable sensors for ≥ 1 year or until the first relapse episode. This combined passive-active relapse prediction framework achieved a balanced accuracy of ≥ 71%, false alarm rate of ≤ 2.3 alarm/patient/year with a median relapse detection time of 2-3 weeks in advance of clinical onset in both studies. The study results suggest that the proposed personalized N-of-1 prediction framework is generalizable and can help predict a majority of MDD relapses in an actionable time frame with relatively low patient and provider burden.

A randomized, double-blind, placebo-controlled study of the efficacy, safety, and tolerability of adjunctive carisbamate treatment in patients with partial-onset seizures.

PURPOSE: To assess the efficacy, safety, and tolerability of adjunctive carisbamate treatment at 800 mg/day and 1,200 mg/day in patients with partial-onset seizures (POS). METHODS: Patients ≥ 16 years of age with an established diagnosis of POS for ≥ 1 year and uncontrolled on one to three antiepileptic drugs were enrolled. Eligible patients remained on stable doses of prescribed antiepileptic drugs for an 8-week pretreatment baseline phase and were then randomized (1:1:1) to receive carisbamate (800 mg/day or 1,200 mg/day), or placebo, for a 14-week double-blind phase. Primary efficacy endpoints were percentage reduction in POS frequency and responder rate (patients with ≥ 50% reduction in POS frequency) during the double-blind versus baseline phase. KEY FINDINGS: Five hundred forty-seven patients were randomized; 540 composed the intent-to-treat (ITT) analysis. Four hundred thirty-four patients (79%) completed the study. The median percent reduction from baseline to treatment phase in POS frequency was: 21% (placebo); 30% (carisbamate 800 mg); 36% (carisbamate 1,200 mg), and 32% (combined carisbamate doses). The combined carisbamate dose group was not significantly different from placebo for the median percent reduction of POS frequency (p = 0.20) or responder rate (p = 0.18). Therefore, the difference from placebo for the individual carisbamate dose groups was also considered nonsignificant, based on a prespecified step-down analysis. Dizziness was the most common treatment-emergent adverse event, with a higher incidence (≥ 5% difference) in the combined carisbamate group (31%) than placebo (9%); the incidence was higher with carisbamate 1,200 mg (32%, n = 58) than with carisbamate 800 mg (30%, n = 53). SIGNIFICANCE: Adjunctive carisbamate therapy in patients with POS did not demonstrate efficacy across the dose range assessed versus placebo. No new safety findings were observed.

Visual Preference for Biological Motion in Children and Adults with Autism Spectrum Disorder: An Eye-Tracking Study.

Participants with autism spectrum disorder (ASD) (n = 121, mean [SD] age: 14.6 [8.0] years) and typically developing (TD) controls (n = 40, 16.4 [13.3] years) were presented with a series of videos representing biological motion on one side of a computer monitor screen and non-biological motion on the other, while their eye movements were recorded. As predicted, participants with ASD spent less overall time looking at presented stimuli than TD participants (P < 10-3) and showed less preference for biological motion (P < 10-5). Participants with ASD also had greater average latencies than TD participants of the first fixation on both biological (P < 0.01) and non-biological motion (P < 0.02). Findings suggest that individuals with ASD differ from TD individuals on multiple properties of eye movements and biological motion preference.

Current Approaches to the Pharmacologic Treatment of Core Symptoms Across the Lifespan of Autism Spectrum Disorder.

There are no approved medications for autism spectrum disorder (ASD) core symptoms. However, given the significant clinical need, children and adults with ASD are prescribed medication off label for core or associated conditions, sometimes based on limited evidence for effectiveness. Recent developments in the understanding of biologic basis of ASD have led to novel targets with potential to impact core symptoms, and several clinical trials are underway. Heterogeneity in course of development, co-occurring conditions, and age-related treatment response variability hampers study outcomes. Novel measures and approaches to ASD clinical trial design will help in development of effective pharmacologic treatments.

Current Approaches to the Pharmacologic Treatment of Core Symptoms Across the Lifespan of Autism Spectrum Disorder.

There are no approved medications for autism spectrum disorder (ASD) core symptoms. However, given the significant clinical need, children and adults with ASD are prescribed medication off label for core or associated conditions, sometimes based on limited evidence for effectiveness. Recent developments in the understanding of biologic basis of ASD have led to novel targets with potential to impact core symptoms, and several clinical trials are underway. Heterogeneity in course of development, co-occurring conditions, and age-related treatment response variability hampers study outcomes. Novel measures and approaches to ASD clinical trial design will help in development of effective pharmacologic treatments.

Learning Scan Paths of Eye Movement in Autism Spectrum Disorder.

Eye tracking studies have demonstrated deficits in attention in individuals with Autism Spectrum Disorder (ASD) for a range of different social attention-based tasks. Here we examined social attention skills in a large sample of ASD participants (n = 120), using eye tracking data from a social information processing task, and compared them with a typically developing (TD) group (n = 35). Assuming eye movement parameters are random variables generated by an underlying stochastic process, we modeled the fixation sequences of participants in ASD and TD groups with a Hidden Markov Model. The Regions of Interests (ROIs), modeled as hidden states, corresponded to the true ROIs with a prediction accuracy of >90% for each group. The transition between ROIs revealed bias towards a specific area in the scene in ASD group, which deviated from the TD group. Objective time-dynamic measures of gaze patterns can potentially serve as useful endpoints in ASD diagnosis. Clinical Trial Registration: NCT02299700.

Social attention to activities in children and adults with autism spectrum disorder: effects of context and age.

BACKGROUND: Diminished visual monitoring of faces and activities of others is an early feature of autism spectrum disorder (ASD). It is uncertain whether deficits in activity monitoring, identified using a homogeneous set of stimuli, persist throughout the lifespan in ASD, and thus, whether they could serve as a biological indicator ("biomarker") of ASD. We investigated differences in visual attention during activity monitoring in children and adult participants with autism compared to a control group of participants without autism. METHODS: Eye movements of participants with autism (n = 122; mean age [SD] = 14.5 [8.0] years) and typically developing (TD) controls (n = 40, age = 16.4 [13.3] years) were recorded while they viewed a series of videos depicting two female actors conversing while interacting with their hands over a shared task. Actors either continuously focused their gaze on each other's face (mutual gaze) or on the shared activity area (shared focus). Mean percentage looking time was computed for the activity area, actors' heads, and their bodies. RESULTS: Compared to TD participants, participants with ASD looked longer at the activity area (mean % looking time: 58.5% vs. 53.8%, p < 0.005) but less at the heads (15.2% vs. 23.7%, p < 0.0001). Additionally, within-group differences in looking time were observed between the mutual gaze and shared focus conditions in both participants without ASD (activity: Δ = - 6.4%, p < 0.004; heads: Δ = + 3.5%, p < 0.02) and participants with ASD (bodies: Δ = + 1.6%, p < 0.002). LIMITATIONS: The TD participants were not as well characterized as the participants with ASD. Inclusion criteria regarding the cognitive ability [intelligence quotient (IQ) > 60] limited the ability to include individuals with substantial intellectual disability. CONCLUSIONS: Differences in attention to faces could constitute a feature discriminative between individuals with and without ASD across the lifespan, whereas between-group differences in looking at activities may shift with development. These findings may have applications in the search for underlying biological indicators specific to ASD. Trial registration ClinicalTrials.gov identifier NCT02668991.

Automated recognition of spontaneous facial expression in individuals with autism spectrum disorder: parsing response variability.

BACKGROUND: Reduction or differences in facial expression are a core diagnostic feature of autism spectrum disorder (ASD), yet evidence regarding the extent of this discrepancy is limited and inconsistent. Use of automated facial expression detection technology enables accurate and efficient tracking of facial expressions that has potential to identify individual response differences. METHODS: Children and adults with ASD (N = 124) and typically developing (TD, N = 41) were shown short clips of "funny videos." Using automated facial analysis software, we investigated differences between ASD and TD groups and within the ASD group in evidence of facial action unit (AU) activation related to the expression of positive facial expression, in particular, a smile. RESULTS: Individuals with ASD on average showed less evidence of facial AUs (AU12, AU6) relating to positive facial expression, compared to the TD group (p < .05, r = - 0.17). Using Gaussian mixture model for clustering, we identified two distinct distributions within the ASD group, which were then compared to the TD group. One subgroup (n = 35), termed "over-responsive," expressed more intense positive facial expressions in response to the videos than the TD group (p < .001, r = 0.31). The second subgroup (n = 89), ("under-responsive"), displayed fewer, less intense positive facial expressions in response to videos than the TD group (p < .001; r = - 0.36). The over-responsive subgroup differed from the under-responsive subgroup in age and caregiver-reported impulsivity (p < .05, r = 0.21). Reduced expression in the under-responsive, but not the over-responsive group, was related to caregiver-reported social withdrawal (p < .01, r = - 0.3). LIMITATIONS: This exploratory study does not account for multiple comparisons, and future work will have to ascertain the strength and reproducibility of all results. Reduced displays of positive facial expressions do not mean individuals with ASD do not experience positive emotions. CONCLUSIONS: Individuals with ASD differed from the TD group in their facial expressions of positive emotion in response to "funny videos." Identification of subgroups based on response may help in parsing heterogeneity in ASD and enable targeting of treatment based on subtypes. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02299700. Registration date: November 24, 2014.

Relationship Between Sleep and Behavior in Autism Spectrum Disorder: Exploring the Impact of Sleep Variability.

OBJECTIVE: The relationship between sleep (caregiver-reported and actigraphy-measured) and other caregiver-reported behaviors in children and adults with autism spectrum disorder (ASD) was examined, including the use of machine learning to identify sleep variables important in predicting anxiety in ASD. METHODS: Caregivers of ASD (n = 144) and typically developing (TD) (n = 41) participants reported on sleep and other behaviors. ASD participants wore an actigraphy device at nighttime during an 8 or 10-week non-interventional study. Mean and variability of actigraphy measures for ASD participants in the week preceding midpoint and endpoint were calculated and compared with caregiver-reported and clinician-reported symptoms using a mixed effects model. An elastic-net model was developed to examine which sleep measures may drive prediction of anxiety. RESULTS: Prevalence of caregiver-reported sleep difficulties in ASD was approximately 70% and correlated significantly (p < 0.05) with sleep efficiency measured by actigraphy. Mean and variability of actigraphy measures like sleep efficiency and number of awakenings were related significantly (p < 0.05) to ASD symptom severity, hyperactivity and anxiety. In the elastic net model, caregiver-reported sleep, and variability of sleep efficiency and awakenings were amongst the important predictors of anxiety. CONCLUSION: Caregivers report problems with sleep in the majority of children and adults with ASD. Reported problems and actigraphy measures of sleep, particularly variability, are related to parent reported behaviors. Measuring variability in sleep may prove useful in understanding the relationship between sleep problems and behavior in individuals with ASD. These findings may have implications for both intervention and monitoring outcomes in ASD.

Publisher Correction: ASPI: a public-private partnership to develop treatments for autism.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Clinical Validation of the Autism Behavior Inventory: Caregiver-Rated Assessment of Core and Associated Symptoms of Autism Spectrum Disorder.

There is a need for measures to track symptom change in autism spectrum disorder (ASD). We conducted a validation study on a revised version of the Autism Behavior Inventory (ABI), and a short form (ABI-S). Caregivers of individuals (6-54 years) with confirmed diagnoses of ASD (N = 144) completed the ABI and other rating scales at 4 time points. Scale consistency for each domain, 3-5 day test-retest reliability, and construct validity, determined by comparison to pre-specified scales, were all good. Change in the ABI was congruent with changes in other instruments. Collectively, results suggest incipient suitability of the ABI as a measure of changes in core and associated symptoms of ASD.Trial Registration NCT02299700.

Plasma Neurofilament Light and Alzheimer's Disease Biomarkers in Down Syndrome: Results from the Down Syndrome Biomarker Initiative (DSBI).

BACKGROUND: Adults with Down syndrome (DS) are at very high risk for Alzheimer's disease (AD). Neurofilament light (NF-L) has emerged as a potential blood-based biomarker of neurodegeneration due to AD. OBJECTIVE: To understand the relationship between plasma NF-L with age, brain amyloid, and tau pathology, neurodegeneration as well as cognitive and functional performance. METHODS: We analyzed imaging data as well as cognitive measures in relation to plasma NF-L in adults with DS, ages 30 to 60 who were enrolled in the Down Syndrome Biomarker Initiative. RESULTS: We found significant correlations between NF-L plasma concentrations and amyloid pathology (r = 0.73, p = 0.007, pa = 0.041) and significant inverse correlations with regional glucose metabolism in 5 of 6 regions examined, which were Anterior cingulate (r = -0.55, p = 0.067, pa = 0.067), Posterior cingulate r = -0.90, p < 0.001, pa < 0.001), Lateral Temporal (r = -0.78, p = 0.004, pa = 0.012), Frontal cortex (r = -0.90, p < 0.001, p pa < 0.001), Parietal cortex (r = -0.82, p = 0.002, pa = 0.008), Precuneus (r = -0.73, pa = 0.010, pa = 0.020), and with hippocampal volume (r = -0.52, p = 0.084, pa = 0.084); and an inverse correlation with direct measures of cognition: CAMCOG (r = -0.66 p = 0.022, pa = 0.066) and positive correlation with CANTAB Paired Associates Learning (PAL) error rate (r = 0.68, p = 0.015, pa = 0.060). Finally, we found inverse relationships with informant-based functional measures (r = -0.57, p = 0.059, pa = 0.084) and OMQ-PF (r = -0.74, p = 0.008, pa = 0.041). CONCLUSION: Plasma NF-L is associated with progressive neurodegeneration as well as with declines in cognitive and functional measures in adults with DS.

Caregiver Daily Reporting of Symptoms in Autism Spectrum Disorder: Observational Study Using Web and Mobile Apps.

BACKGROUND: Currently, no medications are approved to treat core symptoms of autism spectrum disorder (ASD). One barrier to ASD medication development is the lack of validated outcome measures able to detect symptom change. Current ASD interventions are often evaluated using retrospective caregiver reports that describe general clinical presentation but often require recall of specific behaviors weeks after they occur, potentially reducing accuracy of the ratings. My JAKE, a mobile and Web-based mobile health (mHealth) app that is part of the Janssen Autism Knowledge Engine-a dynamically updated clinical research system-was designed to help caregivers of individuals with ASD to continuously log symptoms, record treatments, and track progress, to mitigate difficulties associated with retrospective reporting. OBJECTIVE: My JAKE was deployed in an exploratory, noninterventional clinical trial to evaluate its utility and acceptability to monitor clinical outcomes in ASD. Hypotheses regarding relationships among daily tracking of symptoms, behavior, and retrospective caregiver reports were tested. METHODS: Caregivers of individuals with ASD aged 6 years to adults (N=144) used the My JAKE app to make daily reports on their child's sleep quality, affect, and other self-selected specific behaviors across the 8- to 10-week observational study. The results were compared with commonly used paper-and-pencil scales acquired over a concurrent period at regular 4-week intervals. RESULTS: Caregiver reporting of behaviors in real time was successfully captured by My JAKE. On average, caregivers made reports 2-3 days per week across the study period. Caregivers were positive about their use of the system, with over 50% indicating that they would like to use My JAKE to track behavior outside of a clinical trial. More positive average daily reporting of overall type of day was correlated with 4 weekly reports of lower caregiver burden made at 4-week intervals (r=-0.27, P=.006, n=88) and with ASD symptoms (r=-0.42, P<.001, n=112). CONCLUSIONS: My JAKE reporting aligned with retrospective Web-based or paper-and-pencil scales. Use of mHealth apps, such as My JAKE, has the potential to increase the validity and accuracy of caregiver-reported outcomes and could be a useful way of identifying early changes in response to intervention. Such systems may also assist caregivers in tracking symptoms and behavior outside of a clinical trial, help with personalized goal setting, and monitoring of progress, which could collectively improve understanding of and quality of life for individuals with ASD and their families. TRIAL REGISTRATION: ClinicalTrials.gov NCT02668991; https://clinicaltrials.gov/ct2/show/NCT02668991.

Automatic Recognition of Posed Facial Expression of Emotion in Individuals with Autism Spectrum Disorder.

Facial expression is impaired in autism spectrum disorder (ASD), but rarely systematically studied. We focus on the ability of individuals with ASD to produce facial expressions of emotions in response to a verbal prompt. We used the Janssen Autism Knowledge Engine (JAKE®), including automated facial expression analysis software (FACET) to measure facial expressions in individuals with ASD (n = 144) and a typically developing (TD) comparison group (n = 41). Differences in ability to produce facial expressions were observed between ASD and TD groups, demonstrated by activation of facial action units (happy, scared, surprised, disgusted, but not angry or sad). Activation of facial action units correlated with parent-reported social communication skills. This approach has potential for diagnostic and response to intervention measures.Trial Registration NCT02299700.

An Observational Study With the Janssen Autism Knowledge Engine (JAKE®) in Individuals With Autism Spectrum Disorder.

Objective: The Janssen Autism Knowledge Engine (JAKE®) is a clinical research outcomes assessment system developed to more sensitively measure treatment outcomes and identify subpopulations in autism spectrum disorder (ASD). Here we describe JAKE and present results from its digital phenotyping (My JAKE) and biosensor (JAKE Sense) components. Methods: An observational, non-interventional, prospective study of JAKE in children and adults with ASD was conducted at nine sites in the United States. Feedback on JAKE usability was obtained from caregivers. JAKE Sense included electroencephalography, eye tracking, electrocardiography, electrodermal activity, facial affect analysis, and actigraphy. Caregivers of individuals with ASD reported behaviors using My JAKE. Results from My JAKE and JAKE Sense were compared to traditional ASD symptom measures. Results: Individuals with ASD (N = 144) and a cohort of typically developing (TD) individuals (N = 41) participated in JAKE Sense. Most caregivers reported that overall use and utility of My JAKE was "easy" (69%, 74/108) or "very easy" (74%, 80/108). My JAKE could detect differences in ASD symptoms as measured by traditional methods. The majority of biosensors included in JAKE Sense captured sizable amounts of quality data (i.e., 93-100% of eye tracker, facial affect analysis, and electrocardiogram data was of good quality), demonstrated differences between TD and ASD individuals, and correlated with ASD symptom scales. No significant safety events were reported. Conclusions: My JAKE was viewed as easy or very easy to use by caregivers participating in research outside of a clinical study. My JAKE sensitively measured a broad range of ASD symptoms. JAKE Sense biosensors were well-tolerated. JAKE functioned well when used at clinical sites previously inexperienced with some of the technologies. Lessons from the study will optimize JAKE for use in clinical trials to assess ASD interventions. Additionally, because biosensors were able to detect features differentiating TD and ASD individuals, and also were correlated with standardized symptom scales, these measures could be explored as potential biomarkers for ASD and as endpoints in future clinical studies. Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT02668991 identifier: NCT02668991.