Pharmacometrics

Course content

Lectures covering PK-PD relationships, as well as distribution, metabolite kinetics, effect at receptor and ionchannel level, effect measurement, dose-effect relationships, population methods, simulation of PK-PD relationships and variability in PK-PD response and dosing to different patient populations.

Computer sessions for pharmacokinetic pharmacodynamic modeling using the program Phoenix WinNonlin, Berkeley Madonna and Microsoft Excel.

Education

MSc Programme in Quantitative Biology and Disease Modelling - mandatory in the Technological Specialization

MSc Programme in Medicinal Chemistry - elective

MSc Programme in Pharmacy (Danish programme cand.pharm) - elective

MSc Programme in Pharmaceutical Sciences (Danish programme cand.scient.pharm) - restricted elective

MSc Programme in Pharmaceutical Sciences (English programme) - restricted elective

Learning outcome

At the end of the course, students are expected to be able to:

Knowledge

  • demonstrate knowledge of pharmacokinetic (PK) and pharmacodynamic (PD) in the individual as well as the population
  • understand how to calculate PK and PD parameters and use them in a quantitative description of the interaction between a drug and the body over time.
  • obtain knowledge on variability in patient populations

 

Skills

  • obtain insight and hands-on experience with pharmacokinetic and –dynamic data analysis, based on different examples of plasma concentration-time course linked to therapeutic response.
  • obtain experience with the modelling software Phoenix WinNonlin and Microsoft Excel for data analysis.
  • apply knowledge on variability in patient populations to a PKPD analysis that can be used to describe variability in response in different patient segments and in drug research and illustrate development within the pharmaceutical industry.

 

Competences

  • design dosing strategies in different clinical situations based on their knowledge about PKPD (e.g. taking variations such as demographics, organfunction, pharmacogenetics, comobidity and interactions into account).
  • design experiments for the drug research and development based on their knowledge about PKPD

 

Lectures: 20 lectures
Tutorials/computer sessions: 16 hours

  • M. Rowland and T. Tozer, Clinical Pharmacokinetics and Pharmacodynamics, ed. 5, 2018 or ed. 4, 2011
  • Notes and lecture hand-outs available on the course homepage

Participation and exam in either Basic Pharmacology or Principles of Pharmacology or similar, as the student should be familiar with the basic pharmacokinetic parameters and calculations, concepts determining variability in order to suggest individual dosing as well as knowledge and competence for reasoning on PKPD information.

If you are applying for the course as a credit transfer student, you must have passed Basic Pharmacology or Principles of Pharmacology or have acquired similar competencies in another course. Documentation for corresponding competencies in the form of a course description and an exam result must be attached to your application.

Oral

Oral feedback will be given at tutorials and computer excercises

ECTS
7,5 ECTS
Type of assessment
Written examination, 3 hours under invigilation
Type of assessment details
Examiners: Course teachers
Aid
Written aids allowed

Find more information about written on-site exams in the exam rooms, incl. information about standard programs on the exam PCs at KUnet

Written on-site exam - KUnet

In addition to the standard programs digital notes are permitted for this exam. It is allowed to upload notes for the ITX exam via digital exam. You will find a link to this feature from your exam in Digital Exam.

 

Marking scale
7-point grading scale
Censorship form
No external censorship
Criteria for exam assessment

To achieve the grade 12 the student must be able to:

Knowledge

  • demonstrate knowledge of pharmacokinetic (PK) and pharmacodynamic (PD) in the individual as well as the population
  • understand how to calculate PK and PD parameters and use them in a quantitative description of the interaction between a drug and the body over time.
  • obtain knowledge on variability in patient populations

 

Skills

  • obtain insight and hands-on experience with pharmacokinetic and –dynamic data analysis, based on different examples of plasma concentration-time course linked to therapeutic response.
  • obtain experience with the modelling software Phoenix WinNonlin and Microsoft Excel for data analysis.
  • apply knowledge on variability in patient populations to a PKPD analysis that can be used to describe variability in response in different patient segments and in drug research and illustrate development within the pharmaceutical industry.

 

Competences

  • design dosing strategies in different clinical situations based on their knowledge about PKPD (e.g. taking variations such as demographics, organfunction, pharmacogenetics, comobidity and interactions into account).
  • design experiments for the drug research and development based on their knowledge about PKPD

 

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 20
  • Preparation
  • 167
  • Theory exercises
  • 16
  • Exam
  • 3
  • English
  • 206

Kursusinformation

Language
English
Course number
SFKK18010U
ECTS
7,5 ECTS
Programme level
Full Degree Master
Full Degree Master choice
Duration

1 block

Placement
Block 1
Schedulegroup
A
Capacity
54 students: 20 seats reserved Students studying the MSc Programme in Quantitative Biology and Disease Modelling - the Technological Specialization.
Studyboard
Study Board of Pharmaceutical Sciences
Contracting department
  • Department of Drug Design and Pharmacology
Contracting faculty
  • Faculty of Health and Medical Sciences
Course Coordinator
  • Trine Meldgaard Lund   (10-79776e736a33717a736945787a736933707a336970)
Study secretary: If you need to contact the study secretary, please the Student Affairs Department contact information (list in Danish only): Afdeling for Uddannelse og Studerende (AUS) – Københavns Universitet (ku.dk)
Teacher

Trine Meldgaard Lund
Eva Sverrisdóttir
Majid Sheykhzade
Uffe Kristiansen

Saved on the 31-03-2022

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