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Challenges and Opportunities of Integrating AI in Life Sciences
Exploring the hurdles faced by diverse teams integrating AI in life sciences, from data sharing challenges to mindset shifts, and predicting AI's essential role in regulatory tests for drug discovery. The chapter highlights the power of AI technology to streamline drug discovery processes by unifying databases and emphasizing the need for multiple models to optimize specific scientific questions. It also discusses the practical implications of phenotypical drug discovery, data stratification, and creating knowledge graphs for more effective processes.