Technology is the backbone of state of the art cancer labs. Artificial intelligence and machine learning algorithms are employed to analyze vast datasets, revealing patterns and correlations that might be overlooked by human researchers. Technologies like CRISPR-Cas9 allow for precise gene editing, which is invaluable for studying gene functions and developing targeted therapies. Additionally, the use of bioinformatics and computational models facilitates the simulation of cancer progression and response to treatment, providing insights that guide experimental work.
