Description
The Role of Smart Genomics and AI in Improving Cancer Care explores how the integration of advanced genomic profiling and artificial intelligence is transforming precision oncology. The session will highlight how AI-driven data analysis enhances early detection, risk stratification, and personalized treatment planning. Experts will discuss real-world applications in tumor profiling, targeted therapy selection, and predictive outcome modeling. Designed for healthcare professionals, this webinar aims to bridge the gap between molecular science and clinical decision-making to improve patient outcomes in cancer care.
Summary Listen
- Precision medicine aims to provide the right treatment to the right patient at the right time, driven by advances in genomics that identify specific cancer drivers and mutations. Early cancer detection improves survival rates, but technology costs have significantly decreased, allowing for more comprehensive multi-omic analyses of individual genes, proteins, the gut biome, and transcriptome information.
- The evolution of cancer management has shifted from a one-size-fits-all approach to personalized care, spurred by genomic insights and targetable therapies. Identifying mutations across the genome landscape enables the development of targeted treatments, with a growing pipeline of cancer drugs actively pursued by pharmaceutical companies.
- Biomarkers in cancer management span diagnostics, prognostics, prediction, and resistance, and are increasingly derived from liquid biopsies (blood or other bodily fluids) rather than traditional tissue biopsies. Liquid biopsies offer a non-invasive approach to capture biomarkers like circulating tumor DNA, RNA, and circulating tumor cells (CTCs).
- Liquid biopsies address the limitations of tissue biopsies, such as accessibility challenges, tumor heterogeneity, and sample inadequacy. They provide a means to assess the overall heterogeneity of tumors and target different mutations present in various parts of the body.
- Circulating tumor cells (CTCs) hold significant value as they contain the molecular and functional imprint of the tumor, offering a direct visual evidence of cancer. Novel techniques are being developed to enrich and analyze CTCs, including the identification of organ-specific markers for improved diagnosis.
- AI-powered decision support systems are critical in cancer care due to the vast amounts of bioinformatic data generated from complex patient profiling. AI models can identify molecular signatures of cancer, aiding in therapy guidance and monitoring for drug resistance.
- Integrating AI into healthcare, particularly in diagnostics (digital pathology, genomics, radiology) and therapy (tumor-agnostic approaches), is transforming cancer care. These technologies must be validated, data-driven, and ethically implemented, with ongoing awareness of their limitations.
- Challenges in implementing smart genomics and AI in cancer care include the lack of trained genetic counselors, the need for data privacy, and the risk of unsupervised use of AI technologies. Education and awareness are crucial for healthcare professionals and patients to understand the benefits and limitations of these advancements.
Sample Certificate
About the Speakers
Dr. Vineet Datta
Senior Director Global Strategy, Datar Cancer Genetics Limited, London
Comments
Comments
You must be logged in to leave a comment.