Robotics & Machine Learning Daily News2024,Issue(Oct.2) :22-23.

Jackson Laboratory for Genomic Medicine Reports Findings in Robotics (Developmen t of an automated 3D high content cell screening platform for organoid phenotypi ng)

Robotics & Machine Learning Daily News2024,Issue(Oct.2) :22-23.

Jackson Laboratory for Genomic Medicine Reports Findings in Robotics (Developmen t of an automated 3D high content cell screening platform for organoid phenotypi ng)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Robotics is the subjec t of a report. According to news originating from Farmington, Connecticut, by Ne wsRx correspondents, research stated, “The use of organoid models in biomedical research has grown substantially since their inception. As they gain popularity among scientists seeking more complex and biologically relevant systems, there i s a direct need to expand and clarify potential uses of such systems in diverse experimental contexts.” Our news journalists obtained a quote from the research from Jackson Laboratory for Genomic Medicine, “Herein we outline a high-content screening (HCS) platform that allows researchers to screen drugs or other compounds against three-dimens ional (3D) cell culture systems in a multi-well format (384-well). Furthermore, we compare the quality of robotic liquid handling with manual pipetting and char acterize and contrast the phenotypic effects detected by confocal imaging and bi ochemical assays in response to drug treatment. We show that robotic liquid hand ling is more consistent and amendable to high throughput experimental designs wh en compared to manual pipetting due to improved precision and automated randomiz ation capabilities. We also show that image-based techniques are more sensitive to detecting phenotypic changes within organoid cultures than traditional bioche mical assays that evaluate cell viability, supporting their integration into org anoid screening workflows. Finally, we highlight the enhanced capabilities of co nfocal imaging in this organoid screening platform as they relate to discerning organoid drug responses in single-well co-cultures of organoids derived from pri mary human biopsies and patient-derived xenograft (PDX) models.”

Key words

Farmington/Connecticut/United States/North and Central America/Biochemicals/Biochemistry/Chemicals/Emerging Techn ologies/Machine Learning/Robotics/Robots

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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