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Autism Biomarkers for Clinical Trials


Ann Wagner, Ph.D.
Division of Translational Research


The goal of this initiative is to encourage the necessary next stages of development and validation of biomarkers with putative value for use in clinical trials for treatments of the core social deficits of Autism Spectrum Disorder (ASD), including multi-site testing and validation for a specific ‘context of use’ (e.g., diagnostic, enrichment, stratification) as a drug development tool. This initiative could facilitate coordination and partnerships with relevant public-private consortia efforts such as those of the Biomarkers Consortium Neuroscience Steering Committee, international efforts, foundations, and regulatory agencies.


The identification of biomarkers to reduce the heterogeneity of ASD participants in clinical trials (stratification or enrichment), and/or biomarkers as objective measures of treatment response, could greatly enhance pharmacologic trial design and signal detection. As such, the Foundation for the NIH (FNIH) Biomarkers Consortium (BC) Neuroscience Committee convened an ASD Biomarkers Working Group to assess the readiness of a range of biomarker candidates for use in ASD clinical trials of treatments for the core social deficits of the disorder. Resting state and task-based EEG and eye tracking measures emerged as the top biomarker candidates of interest for this purpose.

NIH issued a funding opportunity announcement to support a collaborative agreement for a multi-site study to evaluate the potential of these measures as biomarkers for stratification and/or clinical change in clinical trials. The Autism Biomarkers Consortium for Clinical Trials (ABC-CT) project was awarded to Yale University (PI: James McPartland; U19MH108206), co-funded by NIMH, NINDS, NICHD and FNIH/Simons Foundation Autism Research Initiative. The project was accepted by the BC Executive Committee as an official FNIH Biomarkers Consortium Project, allowing input on study design and analyses from BC partners. The ABC-CT is a five-site naturalistic study of 280 ASD and 119 typically developing (TD) children ages 6 – 11 years, with data collection at 5 sites. Biomarker and clinical measures are administered at baseline, 6 weeks, and 6 months. Candidate biomarkers are evaluated for feasibility of implementation, construct validity, reliability, discriminant validity, stratification, and sensitivity to change in comparison to conventional symptom measures. Data are deposited and shared through the NIMH Database for Autism Research (NDAR) in near-real time, and biosamples are deposited in the NIMH Repository and Genomics Resource for genotyping. 

In May 2019, based on results of pre-planned interim analyses, the FDA Biomarker Qualification Program approved a Letter of Intent for submission of EEG N170 to upright faces as a potential drug development tool to identify ASD subgroups for enrichment in clinical trials. The feedback encourages the group to pursue submission of a Biomarker Qualification Plan that addresses the scientific issues and recommendations outlined in the FDA LOI Decision Letter. The planned analyses will be completed within the next year. This initiative could provide for further development and validation of promising biomarker measures as final analyses identify the most promising biomarkers.  Continued coordination with the FNIH Biomarkers Consortium and FDA (through the BC) would be pursued with the goal of obtaining the evidence needed for FDA registration of one or more biomarkers for use in clinical trials of treatments for ASD.

Examples of areas of interest include:

  • Longitudinal extension of promising EEG and eye tracking measures in the same participants.
  • Replication and validation of biomarkers with a new cohort under the same rigorous standardization conditions.
  • Evaluate the generalizability of biomarker measures with independent sites under Good Clinical Practice.
  • Enhance the number of typically-developing participants for a more balanced distribution across TD and ASD, and to inform normative developmental trajectories on the most promising biomarker measures.
  • Evaluate the feasibility of obtaining the most promising EEG and eye tracking biomarker measures in additional cohorts (e.g, younger or older participants).
  • Evaluate sensitivity of biomarkers to change in social cognition or behavior.