Cutting-edge education: "Precision Medicine and AI"
Last week, our students in the current module, "Precision Medicine and AI," from the CAS ETH in Digital Clinical Trials, completed their second 3-day block course at ETH Zurich. The three days were packed with insightful lectures and hands-on activities, covering topics such as precision oncology in clinical practice, genetic testing, immunotherapy, and matching patients to clinical trials with the help of AI.
Students also learned about cutting-edge technologies, including Radiomics, and visited the MRI facility at ETH to explore the latest advances in MRI technology. In addition, they designed a clinical programme incorporating AI and precision medicine, and learned about the ethical, regulatory, and legal challenges in applying AI to medical research.
Some key takeaways from this block course include:
- Low Patient Enrollment in Trials: AI could play a pivotal role in screening and organizing this information to enable better matching, giving more patients a chance for good medication and researchers a better chance to have statistically significant effects.
- Foundation of Precision Oncology: Successful implementation of precision oncology requires three key components: access to high-quality, standardized testing, expertise to interpret results accurately, and access to effective treatments tailored to the patient.
- Economic Value of Effective Cancer Treatment: Although certain cancer therapies may initially appear expensive, they can be economically beneficial in the long term by enabling patients to live longer, healthier lives and contribute to society.
- Role of AI in Medical Imaging: AI not only interprets medical images but also generates synthetic images for creating digital twins. However, it is crucial to understand how these images are generated and to define the parameters based on specific investigative needs to ensure reliable and trustworthy information.
- Defining AI in Clinical Trials: Most aspects of AI evaluated in a clinical trial must be carefully defined during the AI's development and design phase.
- Start with Feasibility Studies: Before proceeding to a main clinical trial, conducting a feasibility study can provide valuable preliminary insights while avoiding a full-scale trial's complexities and regulatory requirements.
We are thrilled to see how our students are engaging with the practical applications of AI technology and would like to thank our excellent faculty for their inspiring lectures and workshops.