# BRITE-Eye: An integrated discovery engine for CNS therapeutic targets driven by high throughput genetic screens, functional readouts in human neurons, and machine learning

> **NIH NIH R44** · QUIVER BIOSCIENCE INC. · 2024 · $1,278,054

## Abstract

Project Summary
Neurological disorders affect millions of patients worldwide and represent a major unmet medical need. Recent
progress on developing new classes of central nervous system (CNS) therapeutics has lagged compared to
other disease areas. A key obstacle in the CNS drug discovery process has been a need for cellular models,
assays, and technologies that can more reliably assess disease-relevant neurophysiological parameters in a
human cellular context at the level of individual neurons and synapses, with the scale and resolution to capture
the complexity and variability of these systems. We propose to address this need through the integration of three
key technologies – (i) our high throughput BRITETM platform for all-optical physiology in human neurons, which
achieves single-cell and single-action-potential resolution with a throughput of ~500,000 neurons per day per
instrument; (ii) genomic screens using CRISPR nuclease to disrupt gene function; (iii) machine learning for
identification of fingerprints that represent complex physiological phenotypes with single-cell resolution. This
Phase II program includes four key objectives. 1) Establish CRISPRn screening conditions in human neurons.
We will select 20 candidate target genes, including epilepsy and neurodevelopmental targets to further optimize
assay conditions compatible with all-optical physiology phenotyping, including timing of genetic disruption and
concentration of CRISPRn/gRNA components for effective knockdown of gene targets. 2) Build deep-learning-
powered analytical tools for single-cell phenotyping. We will use deep neural networks to learn a compact vector
representation of neuronal behavior after pharmacological intervention that leverages our single cell resolution
measurements and accommodates potential heterogeneity in the population of neurons. 3) Identify genetic
modulators of neuronal function using a genome-wide CRISPRn screen. We will combine experimental
conditions and analytical models established in Aims 1-2 to carry out a genome-wide CRISPRn screen (>18,000
gene targets) with arrayed gRNA libraries in wild-type human iPSC-excitatory neurons. We will identify gene
targets whose downregulation leads to significant changes in functional parameters. Potential hits and specificity
of target knockdown will be confirmed in independent rounds using single gRNA and qPCR and immunoblotting
assays. 4) Predict and validate phenotypic rescue in a human iPSC-neuronal model of Fragile X Syndrome.
Finally, we will assess the predictive value of the functional fingerprints developed in Aim 3 to generate a
candidate list of gene targets that can rescue (suppress) phenotypic parameters we have identified in a human
cellular model of the neurodevelopmental disorder, Fragile X syndrome. We will modulate the expression of
these potential genetic suppressors with CRISPRn in FMR1-/y iPSC-neurons and benchmark phenotypic rescue
using genetic re-introduction of FMRP. Successful com...

## Key facts

- **NIH application ID:** 10931401
- **Project number:** 5R44MH135521-02
- **Recipient organization:** QUIVER BIOSCIENCE INC.
- **Principal Investigator:** CAITLIN LEIGH LEWARCH
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,278,054
- **Award type:** 5
- **Project period:** 2023-09-19 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10931401

## Citation

> US National Institutes of Health, RePORTER application 10931401, BRITE-Eye: An integrated discovery engine for CNS therapeutic targets driven by high throughput genetic screens, functional readouts in human neurons, and machine learning (5R44MH135521-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10931401. Licensed CC0.

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