Hasso-Plattner-Institut20 Jahre HPI
Hasso-Plattner-Institut20 Jahre HPI

Personalized Medicine (Sommersemester 2019)

Dozent: Prof. Dr. Erwin Böttinger (Digital Health - Personalized Medicine) , Hanna Drimalla (Digital Health - Personalized Medicine)
Website zum Kurs: https://hpi.de/digital-health-center/teaching/winter-term-201819/data-management-for-digital-health.html

Allgemeine Information

  • Semesterwochenstunden: 4
  • ECTS: 6
  • Benotet: Ja
  • Einschreibefrist: 01.04.2019 bis 26.04.2019
  • 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


Personalized medicine 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 data sciences, pervasive computing/connected health, and intelligent (virtual) assistance systems.

This course addresses all specialization areas of the Digital Health Master program. It is designed to equip students with core competencies in comprehending and/or applying basic concepts, methods and technologies, and key applications of personalized medicine health and disease. Students will learn about key developments driving the evolution of personalized medicine. The teaching format involves 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, revolution in sequencing and data technology, modern real-world biobanking, and developments in health IT platforms and digital health technologies for personalized medicine. Students will study real-world applications of Personalized Medicine, including pharmacogenomics, population genetics, precision oncology and mental health, drug discovery and development, and advanced therapies.

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

Learning Objectives:

  • Understand and apply the concepts, definitions, approaches and terms in personalized medicine
  • Ability to critically assess impact of personalized medicine topics in engineering and implementing digital solutions
  • Critically assess impact of challenges and opportunities for personalized medicine in digital health context
  • Learn to make and communicate assessments and decisions of personalized medicine n development and 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


Final written exam & project component


Block Course (every Wednesday morning), Starting April 10

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