This description is only available in English.

  • Autumn Semester

    Start
  • 10 months

    Duration
  • ETH Zurich
    Location
  • English
    Tuition language
  • 07.04–07.07.2024

    Application period

  • CHF 13,900

    Programme fee

In brief: The CAS ETH in Digital Clinical Trials

Participants will learn from ETH and international experts how to transform a research idea into a comprehensive clinical research approach utilising novel, digital technologies.

Structure and content

Programme description

The CAS ETH in Digital Clinical Trials (CAS ETH DCT) will guide participants through designing a digital clinical study. Participants will use their own or a given clinical problem to learn how modern study concepts, real-​world data, precision medicine, digital measures, and remote monitoring will add to a digital study design. All modules include input lectures, remote preparation, and onsite workshops to discuss the individual approaches.

Objectives

  • To understand and apply all aspects of clinical research methodology
  • To understand the potential of novel, digital technology, e.g., digital measures, real-​world data, remote monitoring, to improve clinical research
  • To create a novel clinical research study utilising digital technology in the area of interest

Professional perspectives

The course will significantly increase the knowledge in and chances for a professional carrier in clinical research. Medical doctors and health care professionals will benefit from the know-​how but also the international expert network for their work in this area.

Structure and format

The course is organised in a modular way built on each other. Each module includes input lectures, followed by blended learning and at least one onsite workshop with all participants and lecturers to discuss specific course content and progress in study planning.  

Additional information

The CAS ETH in Digital Clinical Trials consists of 7 modules:

  • From clinical problem to research question
  • Modern study concepts
  • Real-​world data (RWD)
  • Precision medicine
  • Digital measures
  • Remote monitoring
  • Digital study design

Tuition language(s)

English

Credits

15 ECTS credits

Target group and admission

Target group

The CAS is designed for physicians, health care providers, and professionals in start-​ups, MedTech and pharma companies who want to specialize in clinical research utilising novel, digital technology.

Requirements

Master's degree acknowledged by ETH or equivalent educational qualifications in life science. At least two years of postgraduate work experience in a relevant field. Sufficient prior knowledge in statistics and Good Clinical Practice (GCP).

Required language skills

Language(s) of performance assessment

English

Dates and venue

Start

Every Autumn Semester

Duration

10 months

Application period

07.04–07.07.2024

Location

ETH Zurich

Fees

Programme fee

CHF 13,900

Application fee

CHF 50 for persons with a Swiss university degree, CHF 150 for persons with another university degree (non-​refundable, credit card payment only)

Withdrawal fee

  • within 30 days after admission: free of charge
  • after 30 days after admission: CHF 6,585
  • after programme start: CHF 13,900

Application

Questions about the application

ETH Zurich, School for Continuing Education, HG E 17–18.5, Rämistrasse 101, 8092 Zurich, Tel. external page+41 44 632 56 59call_made, E-mail

Application documents

Additional application documents

  • Good Clinical Practice (GCP) certificate(s)
  • Certificate(s) in statistics

Applicants who do not have prior knowledge in medical statistics and GCP will be admitted with conditions and must successfully complete the corresponding courses.

Organiser

Programme management

Professor Christian Wolfrum
Programme Director
Professor Christian Wolfrum
Dr Sabine Goldhahn
Programme Manager
Dr Sabine Goldhahn

Contact

Dr Sabine Goldhahn
  • +41 44 655 72 92

ETH Zurich
Institute of Food, Nutrition and Health
Schorenstrasse 16
SLA C 5
8603 Schwerzenbach

Responsible body

ETH Zurich, D-​HEST
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