Dietmar Schaffarczyk: Catalogue data in Autumn Semester 2024 |
| Name | Dr. Dietmar Schaffarczyk |
| Address | Wiss.Integrität u. Forschungsethik ETH Zürich, WEC E 17 Weinbergstrasse 9/11 8092 Zürich SWITZERLAND |
| Telephone | +41 44 632 54 07 |
| dietmar.schaffarczy@sl.ethz.ch | |
| Department | Health Sciences and Technology |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | ||||||||||||||||||||||||||||||||||||||||||||||||||
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| 376-0300-00L | Essentials in Translational Science  | 3 credits | 2G | J. Goldhahn, N. K. Brasier, D. Schaffarczyk | ||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Translational science is a cross disciplinary scientific research that is motivated by the need for practical applications that help people (e.g. Medicines). The course should help to clarify basics of translational science, illustrate successful applications and enable students to integrate key features into their future projects. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | After completing this course, students will be able to understand: Principles of translational science including medical device development, intellectual property, regulatory environment and project management Students should be able to apply this knowledge in drug development programs in Pharma, Biotech or their own spin-off. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | What is translational science and what is it not Including: How to identify need? How to choose the appropriate research type and methodology How to measure success? How are medical devices developed? How to handle IP in the development process? How does the regulatory environment impact innovation? How to manage complex development projects? Positive and negative examples will be illustrated by distinguished guest speakers. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Literature | Principles of Biomedical Sciences and Industry Translating Ideas into Treatments https://doi.org/10.1002/9783527824014 | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Prerequisites / Notice | 4x online input lecture followed by case preparation and symposium | |||||||||||||||||||||||||||||||||||||||||||||||||||||
Competencies |
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| 395-0103-00L | Precision Medicine and AI | 2 credits | 3G | A. Fontecedro-Curioni, A. Ghosh, J. Goldhahn, S. Modica, K. Ormond, D. Schaffarczyk | ||||||||||||||||||||||||||||||||||||||||||||||||||
| Abstract | Tailored medical treatments based on disease characteristics but also on patients’ individual features is becoming clinical routine. Personalised medicine utilises genetic, environmental and lifestyle factors to optimise approaches in healthcare. The use of AI will be essential to enhance personalised medicine to improve patients’ journey from diagnosis to treatment and the outcome. | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Learning objective | After taking this course, participants will be able to - Understand genomics and it implications in healthcare - Interpreting genetic testing and the correlated treatment plans - Know the available AI technologies applied to healthcare including concepts of machine learning, natural language processing - Comprehend the use of AI in diagnostics and treatment planning and follow up - Understand how AI can enhance the data analysis and prediction - Make real examples of AI applications in healthcare - Define challenges and limits to data of use of AI in healthcare | |||||||||||||||||||||||||||||||||||||||||||||||||||||
| Content | The module “Precision Medicine and AI” provides knowledge on personalised medicine and explains its significance in modern healthcare. It identifies how genetics can determine disease diagnosis and treatment responses, describes the various AI technologies applicable in healthcare, dissects the ethical considerations and challenges associated with AI, and provides clinical examples of the use of personalised medicine and AI. The topics are - Screening and diagnosis in precision medicine - Pharmacogenomics in precision medicine - Precision oncology - Multiomics approaches in precision medicine - Machine learning in precision medicine - Radiomics - Precision oncology in clinical practice - AI concepts - AI in digital pathology - AI in radiology - AI for clinical data | |||||||||||||||||||||||||||||||||||||||||||||||||||||