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Multi-enzyme Screening Using a High-throughput Genetic Enzyme Screening System

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Published on: August 8, 2016

Metabolic enzyme microarray coupled with miniaturized cell-culture array technology for high-throughput toxicity

Moo-Yeal Lee¹, Jonathan S Dordick, Douglas S Clark

¹Solidus Biosciences, Inc, Troy, NY, USA. lee@solidusbio.com

Methods in Molecular Biology (Clifton, N.J.)

|March 11, 2010

Summary

Developing novel high-throughput tools like the MetaChip and DataChip accelerates the identification of safer drug candidates by providing early predictive toxicology data, reducing drug discovery costs.

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Area of Science:

Drug discovery and development
Toxicology and pharmacology
Biotechnology and bioengineering

Background:

Late-stage identification of poor drug candidate safety profiles significantly hinders pharmaceutical development and increases costs.
There is a critical need for high-throughput tools that provide early predictive toxicology data to accelerate safer drug candidate progression.
In vitro cell-based systems mimicking human in vivo responses are essential for early toxicity and metabolism assessment, especially with European bans on animal testing.

Purpose of the Study:

To develop and validate novel high-throughput in vitro tools for predictive toxicology screening.
To accelerate the assessment of drug candidate safety and metabolism earlier in the drug development pipeline.
To provide reliable in vitro methods for industries phasing out animal toxicity testing.

Main Methods:

Development of a metabolic enzyme microarray (Metabolizing Enzyme Toxicology Assay Chip, MetaChip) with encapsulated enzymes to emulate liver metabolism.
Creation of a miniaturized 3D cell-culture array (Data Analysis Toxicology Assay Chip, DataChip) for cell-based toxicity screening.
Integration of MetaChip and DataChip for combined metabolic and toxicity profiling of drug candidates.

Main Results:

The MetaChip and DataChip systems enable high-throughput toxicity screening of compounds and their metabolites.
Combined use of DataChip with MetaChip yields in vitro toxicity results that show good correlation with in vivo rat data.
The developed platform accurately predicts drug candidate toxicity and metabolism in an in vitro setting.

Conclusions:

The MetaChip and DataChip represent effective high-throughput tools for early-stage predictive toxicology.
These integrated in vitro systems can significantly improve the efficiency and reduce the cost of drug discovery.
The technology offers a viable alternative to animal testing for toxicity assessment in pharmaceutical, cosmetic, and chemical industries.