Artificial Intelligence in Preclinical Design and Execution: Investors and Startups by marinatalamanou

Artificial Intelligence in Preclinical Design and Execution: Investors and Startups

The most common challenges faced by all AI startups in design and execution of preclinical experiments have to do with:
1) reduce time, money, and uncertainty in planning preclinical experiments,
2) decode open and closed access data on reagents and get actionable insights,
3) automate selection, manipulation and analysis of cells, and
4) automate sample analysis with robotic cloud laboratory.
For more here
https://medium.com/@avocado_2015/artificial-intelligence-in-preclinical-design-and-execution-investors-and-startups-2bee3400ee6b![1*jgvxztjtBsymEYEsBBuH1Q.jpeg](https://cdn.steemitimages.com/DQmX1nGTZngXz443CnMphVMFyqtHGaSNmYxWiviwCdo21oj/1*jgvxztjtBsymEYEsBBuH1Q.jpeg)

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