A multiparametric activity profiling platform for neuron disease phenotyping and drug screening

Area of Science:

• Neuroscience
• Biotechnology
• Drug Discovery

Background:

• Current preclinical models for disease lack comprehensive analysis of cellular activity, hindering therapeutic development.
• Existing methods often focus on single parameters, failing to capture complex disease phenotypes.

Purpose of the Study:

• To develop a cloud-based platform for analyzing intricate cellular activity profiles using GCaMP fluorescence.
• To discover molecules capable of correcting multiparametric disease phenotypes, specifically for amyotrophic lateral sclerosis (ALS).

Main Methods:

• Utilized GCaMP fluorescence recordings to capture intracellular calcium changes.
• Developed a cloud-based image processing and analysis platform for high-throughput screening.
• Screened compounds to identify those reverting 153 ALS-related cellular parameters to healthy profiles.

Main Results:

• Identified compounds that successfully reversed multiparametric disease profiles in patient stem cell-derived models.
• Demonstrated a novel, robust measure of therapeutic potential distinct from unidimensional screening.
• The platform effectively captures complex, disease-induced cellular disturbances.

Conclusions:

• The developed platform enables a more comprehensive assessment of cellular activity in disease.
• This multiparametric approach facilitates the discovery of therapeutics targeting multifaceted pathological features.
• The findings guide the development of effective treatments for complex neurological disorders like ALS.