SKBK18001U Pharmacometrics

Volume 2024/2025
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

Content

Lectures will be covering:

Subjects related to a clinical setting such therapeutic regimens, dose-time-effect relationships, therapeutic drug monitoring (TDM), dose adjustments, missed dose and dosing in special patient groups as children and elderly patients.  

Subjects related to early drug development such as PK-PD relationships, effect at receptor and ion channel level and other effect measurements (such as changes in the level of biomarkers and other endogenous hormones or enzymes).

Subjects related to clinical trials, as trial designs, the many aspect of pharmacokinetic and pharmacodynamic variability, population PKPD modelling methods, and simulation of PK-PD relationships.

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

Learning Outcome

The aim of the course to give the students a thorough understanding and hands-on competences of pharmacometric (i.e. pharmacokinetics and pharmacodynamics) methods as it is used in all phases of the drug development process, in the clinical settings and in the regulatory decision making process.

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 in the clinic and in drug research.

 

Competences

  • design dosing strategies in different clinical situations based on their knowledge about PKPD (e.g. taking variations such as demographics, organ function, pharmacogenetics, co-morbidity and interactions into account).
  • Adjust dosing on individual level to different patients (precision dosing) based on demographics and laboratory values as drug plasma concentration, assessment of renal function based on measurement of creatinine clearance (CrCl), serum creatinine (sCr) and/or cystatin C and estimation of GFR (eGFR)
  • design and analyze experiments for drug research and development based on their knowledge about PKPD
  • contribute to design and analysis of clinical PKPD studies based on their knowledge about PKPD
  • M. Rowland and T. Tozer, Clinical Pharmacokinetics and Pharmacodynamics, ed. 5, 2020 
  • Notes and lecture hand-outs available on the course homepage
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.
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
Lectures: 20 lectures
Tutorials/computer sessions: 16 hours
  • Category
  • Hours
  • Lectures
  • 20
  • Preparation
  • 167
  • Theory exercises
  • 16
  • Exam
  • 3
  • Total
  • 206
Oral

Oral feedback will be given at tutorials and computer excercises

Credit
7,5 ECTS
Type of assessment
On-site written exam, 3 hours under invigilation
Type of assessment details
Examiners: Course teachers
Aid
Written aids allowed

Permitted aids: Textbooks, all written course material from the homepage.

There is access to the following at the exam in KUs exam houses:

  • R – Statistical programme
  • MathType formel programme
  • Maple

  • Digital Notes (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).

Find more information about written on-site exams in the exam rooms, incl. information about standard programs on the exam PCs at KUnet: MSc in Quantitative Biology and Disease Modelling - KUnet

Marking scale
7-point grading scale
Censorship form
No external censorship
Re-exam

10 or fewer students registered for reexam:

Type of assessment: Oral examination

Assessment details: 30 minutes examination

Preparation: 30 minutes

Aids: All aids allowed (no internet)

Criteria for exam assesment

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