One of the most important objectives of autism spectrum disorder (ASD) interventions is to improve spoken communicative language skills. Across all ages and levels of language, quantitative changes in the amount of intelligible speech, the length of speaker turns and better conversational turn-taking are key measures of advances in spoken language. Changes in these measures not only signify that a treatment is effective in improving language itself, but also leads to improvements in social communication.

Very early interventions for autism spectrum disorders (ASDs) have the potential to improve long-term outcomes by targeting emotion regulation, social learning and social communication. However, treatment studies currently rely upon long-term measures that are often far removed from the underlying targets of treatment and that are rather insensitive to short-term treatment effects. Measuring short-term outcomes would improve treatment research by speeding discovery and validation of early interventions, but such an approach is currently limited by diagnostic tools that are insensitive to small changes in behavior.

Research assessing the effectiveness of treatments in autism spectrum disorder (ASD) is limited by a lack of scalable and quantifiable autism-specific treatment response measures. Assessing treatment success would be benefited by the development of response measures that can be administered ‘blindly’ and are sensitive enough to capture change over short periods of time, flexible enough to be used across studies and are standardized in order to be comparable across sites.

Individuals with autism spectrum disorder (ASD) have difficulties engaging in social interactions, including problems making eye contact with other people and sharing attention with others about objects in their environment (joint attention). Many interventions aim to allow individuals to more effectively use gaze during social interactions. Currently, there is a shortage of objective, quick and reliable measurements that can detect changes in social communication behaviors. Without good measures to capture change, it is almost impossible to determine if a treatment is effective or is helping to ameliorate ASD symptoms. In addition, measures that are used to determine change are often time intensive, making them impractical to use in many clinical settings.

Medications for treating the core symptoms of autism spectrum disorder (ASD) continue to be an unmet need. The only medications approved by the U.S. Food and Drug Administration (FDA) for the treatment of individuals with ASD are effective in treating irritability and associated aggressive behaviors, but these medications can also cause severe long-term side effects such as diabetes and involuntary motor movements. Effective medications with more tolerable side effect profiles are highly desirable.

Eye-tracking is a well-established research tool that can be used to study social cognition in individuals with autism spectrum disorder (ASD). Previous work at the Yale Child Study Center has shown that eye-tracking techniques are robust measures of atypical social-information processing across the lifespan in individuals with ASD.

In this study, Carolyn Bridgemohan and colleagues assessed the feasibility of using platelet serotonin and urinary melatonin levels as biomarkers in children with ASD, including evaluating potential associations between these biochemical measures with physical, behavioral and cognitive profiles.

The Autism Biomarkers Consortium for Clinical Trials (ABC-CT) is a multicenter research study that aims to develop reliable and objective measurements of social function and communication in people with autism.