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Expert Opin Drug Discov. 2019 Feb;14(2):115-125. doi: 10.1080/17460441.2019.1559147. Epub 2018 Dec 24.

Enabling drug discovery and development through single-cell imaging.

Author information

1
a Analytical Sciences & Imaging , Novartis Institutes for BioMedical Research Inc ., Cambridge , MA , USA.
2
b Global Discovery Chemistry , Novartis Institutes for BioMedical Research Inc ., Emeryville , CA , USA.
3
c Cancer Therapeutics , Genomics Institute of the Novartis Research Foundation , La Jolla , CA , USA.
4
d Alliance Management and Partnering , Novartis Institutes for BioMedical Research Inc ., Emeryville , CA , USA.

Abstract

Single-cell imaging-based assays are an area of active and growing investment in drug discovery and development. This approach offers researchers the capability to interrogate rare subpopulations of cells with minimal sample consumption and multiplexed readouts. Recent technological advances in the optical interrogation and manipulation of single cells have substantially increased the throughput and sensitivity of these assays. Areas covered: In this review, the authors focus on three classes of single-cell imaging-based analyses: single-cell microscopy combined with microfluidics, mass spectrometric imaging for subcellular compound localization, and imaging mass cytometry (IMC). They provide an overview of each technology and recent examples of their utility in advancing drug discovery, based on the potential for scalability, multiplexing, and capability to generate definitive data on cellular heterogeneity and target engagement. Expert opinion: Understanding target engagement and heterogeneity at the single-cell level will enable the development of safer and more effective therapies, particularly for new modalities like CAR-T cell therapies and gene editing approaches (AAV, CRISPR). Successful adoption of new single-cell imaging-based approaches in drug discovery will require tandem investment in advanced computational analysis and bioinformatic approaches, due to the complexity and multivariate nature of single-cell imaging data.

KEYWORDS:

Bioinformatics; CAR-T; fluorescence microscopy; image analysis; imaging mass cytometry; imaging mass spectrometry; immuno-oncology; microfluidics; multiplexing; oncology; tissue

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