# High-throughput Phenotypic Screening (HPS) Platform for Large-scale Drug Discovery in Whole-organism and Human Organoid-based Disease Models

> **NIH NIH S10** · JOHNS HOPKINS UNIVERSITY · 2020 · $1,938,041

## Abstract

PROJECT SUMMARY
S10 funds will be used to create a novel integrated instrumentation system enabling high-throughput
phenotypic screens (HPS) across a diverse array of whole-organism (e.g., worms, flies, mosquitos, fish) and
three-dimensional (3D) cell culture models (e.g., stem cell-derived “organoids”). Modern ‘omics technologies
and drug discovery methods create massive amounts of data and numerous compound ‘hits’, respectively.
This creates bottlenecks in testing the large numbers of predictions made due to current limitations in
experimental capacities, particularly for assays performed in vivo. The HPS platform addresses this issue by
supporting true high-throughput screening (HTS) rates for in vivo assays―i.e., tens of thousands of
specimens processed per day. This, in turn, enables large-scale genetic screens designed to test big data
predictions across entire gene networks as well as high-throughput chemical screens that place living disease
models at the start, rather than the end, of the drug discovery process to increase the pace of new drug
development. The HPS platform combines two complementary phenotypic screening methods designed to
accommodate living model systems: ARQiv (Automated Reporter Quantification in vivo), a plate reader-based
approach enabling true HTS rates in vivo, and VAST (Vertebrate Automated Screening Technology), an
automated microfluidics-based system facilitating rapid high-content imaging (HCI). We will update the
capabilities of these systems by updating them to support: 1) Faster throughput, 2) Longitudinal screens, and
3) High-resolution 3D imaging. For the latter, we will couple cutting-edge Light Sheet Fluorescence Microscopy
(LSFM, aka SPIM) to VAST. ARQiv and VAST systems will be integrated into a unified screening platform via
a custom-designed robotics workstation that automates all aspects of in vivo screening processes: 1)
Compound dispensing and dilution schemes, 2) Sorting and dispensing model systems into microtiter plates,
3) Plate handling, and 4) Microfluidics-based sample handling (e.g., sample orientation for imaging). The
proposed platform thereby provides both high-throughput screening capacities (via ARQiv) and high-content
imaging (via VAST/LSFM) for in vivo assay paradigms. Moreover, real-time data processing will facilitate a
hierarchical phenotypic screening strategy where VAST-based imaging will be limited to ARQiv-flagged
samples of interest (i.e., “hits”); enabling maximal throughput without sacrificing enriched data content and
addressing a key bottleneck in applying HCI methods to more complex 3D model systems. The platform will
anchor a HPS Core facility supporting cutting-edge in vivo discovery capabilities and unique training
opportunities for researchers at JHU and nearby academic institutions; expanding HTS-paced phenotypic
screening to multiple model systems and reporter-based assay paradigms, and facilitating collaborative cross-
species initiatives designed to reveal evol...

## Key facts

- **NIH application ID:** 9939116
- **Project number:** 1S10OD026909-01A1
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** JEFFREY MUMM
- **Activity code:** S10 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,938,041
- **Award type:** 1
- **Project period:** 2020-08-15 → 2022-08-14

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9939116

## Citation

> US National Institutes of Health, RePORTER application 9939116, High-throughput Phenotypic Screening (HPS) Platform for Large-scale Drug Discovery in Whole-organism and Human Organoid-based Disease Models (1S10OD026909-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9939116. Licensed CC0.

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