Despite its potential, AI-driven simulations face several challenges. One of the main issues is the quality and availability of data. For AI to make accurate predictions, it requires high-quality, comprehensive datasets, which can be difficult to obtain. Moreover, the complexity of cancer biology means that even the most sophisticated models can struggle to capture all the nuances of the disease. There is also a need for more interdisciplinary collaboration to integrate AI tools effectively into cancer research and clinical practice.
