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3D cell culture environments allow cells to proliferate and interact with their extracellular surroundings. These techniques are gaining traction in tissue engineering and drug development due to their ability to provide more physiologically relevant information and predictive data for in vivo studies. As an alternative to extensive and costly animal testing, cell-based assays are crucial in the drug development process, offering a quicker, simpler, and more cost-effective solution.
The rapid advancement of AI technology has led to the emergence of products that fully automate cell culture studies. AI-powered software can not only create 2D and 3D cellular models but also automate the feeding and passaging of cells throughout their lifecycle. Machine learning algorithms effectively monitor and guide automated processes for organoid production, image analysis, and application outcomes, significantly reducing human error and hands-on time in laboratories.
For example, in April 2024, Predictive Oncology Inc. launched an advanced 3D cell culture model designed to streamline the discovery of cancer treatments. This model features organ-specific in vitro systems that closely mimic human tissue, potentially improving clinical outcome predictions and expediting drug development.
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