Integrative CRISPR Cas9 and machine learning Approaches for Target Discovery and Therapeutic Development in Malignant Brain Tumor

Malignant brain tumours, such as glioblastoma, remain among the most challenging cancers to treat due to their heterogeneity, aggressive progression, and resistance to conventional therapies. The integration of CRISPR-Cas9 gene-editing technology with advanced machine learning (ML) approaches offers a transformative framework for identifying novel therapeutic targets and accelerating drug development. CRISPR-Cas9 enables precise genetic perturbations to uncover critical genes and pathways driving tumorigenesis, while ML algorithms analyze high-throughput genomic, proteomic, and clinical data to predict key molecular targets and optimize therapeutic strategies. This synergistic approach facilitates the identification of tumor-specific vulnerabilities, enhances the design of personalized therapies, and improves the prediction of drug efficacy and resistance mechanisms. By combining CRISPR-based functional genomics with ML-driven data integration, this strategy holds immense potential to advance precision medicine for malignant brain tumors, paving the way for more effective and tailored treatment options.