# Validating a Scalable, Open Science Framework for Collecting Laboratory-Grade Data Remotely in Specialized Populations

> **NIH NIH R21** · PURDUE UNIVERSITY · 2021 · $230,498

## Abstract

PROJECT SUMMARY
The limited repertoire of clinical outcome measures suitable for children with intellectual and
developmental disabilities (IDD) is compromising the promise of clinical trials. Non-standardized
laboratory techniques that capture “spectral” signals – such as psychophysiological assays –
are increasingly recognized as promising methods for monitoring patient responses over time.
However these tools require specialized equipment and personnel to administer and are not
easily deployed via telehealth, biasing spectral studies toward patients who are able and willing
to travel to clinics. Thus, there is a significant gap in available telehealth-based protocols for
collecting laboratory-grade data remotely in IDD populations. The present study addresses this
gap by developing a comprehensive training protocol for PANDABox (Parent Assisted
Neurodevelopmental Assessment), an open-science, telehealth-based assessment protocol that
PI Kelleher developed for remotely collecting high quality, integrated clinical, behavioral, and
spectral assays from participants with IDD. Published findings indicate that PANDABox is highly
feasible and acceptable to caregivers and generates high quality, integrated, “laboratory-grade”
data at low cost. Already, PANDABox is being deployed in a variety of treatment and natural
history studies across IDD populations and is being translated to Spanish to promote
accessibility. The present study aims to enhance the scalability of PANDABox by accomplishing
two specific aims. First, we will develop and validate an open-science training protocol and
peer-to-peer reliability network to facilitate standardized, cross-laboratory implementation of the
PANDABox protocol in IDD. This protocol will include both a virtual training hub for self-paced
training, as well as a reliability network to facilitate cross-site calibration. Second, we will create
user-friendly software program to support users to efficiently process the PANDABox attention
assay, which has produced promising outcomes in clinical trials but requires computational
expertise to analyze, limiting its scalability. Addressing these gaps would shift the status quo of
clinical science in IDD by (1) providing a scalable, accessible protocol for collecting laboratory-
grade data remotely in IDD populations and (2) producing standardized data outputs necessary
for large scale, multi-site, collaborative science.

## Key facts

- **NIH application ID:** 10289016
- **Project number:** 1R21HD106701-01
- **Recipient organization:** PURDUE UNIVERSITY
- **Principal Investigator:** Bridgette Lynne Kelleher
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $230,498
- **Award type:** 1
- **Project period:** 2021-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10289016

## Citation

> US National Institutes of Health, RePORTER application 10289016, Validating a Scalable, Open Science Framework for Collecting Laboratory-Grade Data Remotely in Specialized Populations (1R21HD106701-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10289016. Licensed CC0.

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