Automated Identification of Novel Therapeutic Targets for Pancreatic Cancer via CRISPR-Enhanced Transcriptomic Profiling and Machine Learning Integration

**Abstract:** This research presents a novel framework for identifying effective therapeutic targets for pancreatic cancer by combining CRISPR-based gene knockout screening with high-throughput transcriptomic analysis and a cascade of machine learning algorithms. The process automates target identification, circumventing traditional bottlenecks in drug discovery and offering a significantly accelerated route from genetic screening to clinical candidate validation. This approach promises to deliver more effective therapeutics and address the dismal survival rates associated with pancreatic cancer. --- *This document is a part of the Freederia Research Archive. Explore our complete collection of advanced research at [en.freederia.com](https://en.freederia.com), or visit our main portal at [freederia.com](https://freederia.com) to learn more about our mission and other initiatives.*