• Introduction: Define computational oncology and its promise in cancer treatment.

• AI & Genomics Integration: Discuss how AI analyzes big genomic datasets—cfDNA, liquid biopsies—to uncover tumor mutations.

• Case Study: Highlight a specific application, e.g., predictive modeling for immunotherapy response.

• Clinical Impact: Show how this translates to personalized treatment plans and improved outcomes.

• Future Outlook: Emerging trends—multi‑omics analysis, deep learning for spatial transcriptomics.

• Call to Action: Invite clinicians/researchers to collaborate via Dr. Kwatra’s lab or his precise pipelines.

Why it matters: Positions Dr. Kwatra as a thought leader, educates peers on cutting-edge approaches, and sparks inquiry.