Hasso-Plattner-InstitutSDG am HPI
Hasso-Plattner-InstitutDSG am HPI
  
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Personalized Medicine (Sommersemester 2020)

Dozent: Prof. Dr. Erwin Böttinger (Digital Health - Personalized Medicine) , Dr. Girish Nadkarni (Digital Health - Personalized Medicine) , PharmD Aniwaa Owusu-Obeng (Gastdozenten oder Dozenten der Uni-Potsdam) , Dr. Claudia Schurmann (Digital Health - Personalized Medicine) , Dr. rer. nat. Stefan Konigorski (Digital Health - Machine Learning) , Dr. Hanna Drimalla (Digital Health - Personalized Medicine)

Allgemeine Information

  • Semesterwochenstunden: 4
  • ECTS: 6
  • Benotet: Ja
  • Einschreibefrist: 06.04.2020-22.04.2020
  • Lehrform: Vorlesung / Übung
  • Belegungsart: Wahlpflichtmodul
  • Lehrsprache: Englisch

Studiengänge & Module

Digital Health MA
  • DICR-Concepts and Methods
  • DICR-Technologies and Tools
  • DICR-Specialization
  • APAD-Concepts and Methods
  • APAD-Technologies and Tools
  • APAD-Specialization

Beschreibung

Lecture starts 04/29/20

HOT TOPIC: The Coronavirus Pandemic presents unprecedented challenges for health systems, societies, economies, and most of all individual citizens. We will introduce and discuss new insights, stakeholder perspectives, and how we may deploy digital solutions to improve infection control and coronavirus disease 19 (Covid19) from a personalized health and public health viewpoint.  

Personalized medicine (PM) combines lifestyle, environment, genomic, and biologic information to identify molecular disease mechanisms with the aim of improving prevention, diagnosis and therapy while leading to a more efficient health system. Personalized Medicine is intensely data-driven and leverages health information systems, genomics, data sciences, and digital health methodologies and technologies. Real-world implementations of personalized medicine applications typically integrate digital health technologies and tools.  

This course addresses the specialization areas ‘Digitalization of Clinical and Research Processes (DICR)’, ‘Acquisition, Processing and Analysis of Health Data (APAD)’, and ‘Scalable Computing Algorithms for Digital Health (SCAD)’ of the Digital Health Master program. It is designed to equip students with core knowledge and competencies in data-driven personalized medicine.

The course will deploy a mixed teaching format with lectures, seminars, and case studies with active student participation. Students will learn about foundations for Personalized Medicine, including the Human Genome Project and genomic sciences, emerging study designs for personalized health evidence generation, modern real-world biobanking, health IT platforms and digital health technologies for personalized medicine. Students will study in-depth the landmark Topol Report on ‘preparing the personalized, digital future of healthcare’

Learning Objectives:

  • Understand and apply the concepts, definitions, approaches and terms in data-driven personalized medicine
  • Critically assess impact of challenges and opportunities for personalized medicine
  • Learn to make and communicate assessments and decisions on personalized medicine requirements in development and/or implementation of digital health solutions
  • Ability to assess scope and sustainable benefits of digital tools, applications, and information in health behavior, prevention and management of disease

Topics for the lecture (changes may occur)

Literatur

  • Ashley E. Towards precision medicine: applications of next generation sequencing. Nature Reviews Genetics 17:507-522, 2016
  • Pritchard et al. Strategies for integrating personalized medicine in healthcare practice. Personalized Medicine Vol 14(2) Published Online 19 Jan 2017
  • Personalized Medicine Coalition. Public perspectives on Personalized Medicine. Survey of U.S. public opinion May 2018
  • Personalized Medicine Coalition. The Personalized Medicine Report 2017   
  • NHS The Topol Review. Preparing the healthcare workforce to deliver the digital future. An independent report on behalf of the Secretary of State for Health and Social Care, February 2019
  • Nikles J, Mitchell G (eds) (2015). The essential guide to N-of-1 trials in health. Dordrecht: Springer.
  • https://www.who.int/emergencies/diseases/novel-coronavirus-2019

Lern- und Lehrformen

Characteristics of Class Meetings/Lectures: Two back-to-back lectures/seminars/case studies once a week

Due to Corona pandemic we will use Zoom Meetings and openHPI course room (link to the course on openHPI will be provided after registration deadline to all registered participants )

Leistungserfassung

Student presentation: 50% of the final grade.
Written final exam: 50% of the final grade.

Termine

Block Course (every Wednesday morning),  Starting April 29

  • Lecture/Seminar/Case Study #1:  9:15-10:45 am
  • Lecture/Seminar/Case Study #2: 11:00-12:30 am

Note: we may postpone lectures to an afternoon session, starting 15:15h pm, for the interactive parts with our lecturers from New York (05/20/20 & 06/17/20)

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