Syllabus for Computational Pharmaceutics

Datorbaserad farmaceutisk modellering


  • 7.5 credits
  • Course code: 3FG005
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Pharmaceutical Sciences A1N, Drug Discovery and Development A1N

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle

    • G1N: has only upper-secondary level entry requirements
    • G1F: has less than 60 credits in first-cycle course/s as entry requirements
    • G1E: contains specially designed degree project for Higher Education Diploma
    • G2F: has at least 60 credits in first-cycle course/s as entry requirements
    • G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    • GXX: in-depth level of the course cannot be classified

    Second cycle

    • A1N: has only first-cycle course/s as entry requirements
    • A1F: has second-cycle course/s as entry requirements
    • A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    • A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    • AXX: in-depth level of the course cannot be classified

  • Grading system: Fail (U), Pass (G), Pass with distinction (VG)
  • Established: 2020-10-20
  • Established by:
  • Revised: 2022-03-02
  • Revised by: Programme Coordinator Jamie Morrison
  • Applies from: Autumn 2022
  • Entry requirements: In the Master of Science Programme in Pharmacy and the Master's Programme in Chemical Engineering the student should have at least 150 credits in the program, and passed the course(s) in physical chemistry. In the Master's Programmes in Pharmaceutical Modelling and Drug Discovery and Development the student should have passed the course in Molecular Biopharmaceutics, as well as compulsory parts in the course Molecular Physical Pharmacy. Freestanding course: 150 credits including at least 6.5 credits in physical chemistry. Knowledge in English equivalent to that required for basic eligibility to Swedish higher education.
  • Responsible department: Department of Pharmacy

Decisions and guidelines

The course is part of the Master's programme in Biopharmaceuticals

Learning outcomes

After having completed the course, the student should:

  • Apply knowledge about in silico simulation techniques to understand dynamics in pharmaceutical and biological drug systems.
  • Apply knowledge about how modeling and simulation can be used to understand features of pharmaceutical delivery systems, and how this knowledge can be applied for delivery of macromolecules.
  • Describe how barriers relevant to drug absorption can be studied with in silico methods, and further how such methods are used to explore the interactions between barrier properties, drug permeability and bioavailability.
  • Analyze how modeling and simulation can be used to address specific challenges with biological drugs, such as structural changes, aggregation and formulations of therapeutic macromolecules.
  • Describe how different modeling techniques can be used to study binding and interactions between larger biological drugs, such as antibodies, and ligands.
  • Describe how modeling and simulation can be used for the purpose of studying dynamics in the interactions between nanoparticles and macromolecules.
  • Utilize, assess, summarize in writing and orally present relevant scientific literature within drug delivery systems, in correct English.


In the course different simulation and modeling techniques (such as molecular dynamics, monte carlo, dissipative particle dynamics, lattice-Boltzmann-methodology) are studied, and how these can be used in the process of drug development. Examples include how in silico-methods can be used for efficient design and understanding of pharmaceutical formulations for e.g. biological drugs, and how modeling and simulation thereby can be used as a means toward less trial-and-error and more knowledge-based formulation development. The course contains the following:

Basic understanding of physics-based simulation and modeling methodology, applicable on pharmaceutical and biological problems. In the course, the mathematical foundations for the lattice-Boltzmann method are presented, which is away to model pharmaceutical systems at the intersection between individual molecules and macroscopic variables. Lattice-Boltzmann is applied later in the course to e.g. stud diffusion of drugs, formulation components and delivery systems under the influence of different external forces.

Further and understanding is built during the course of the differences and similarities that exists between different simulation and modeling techniques, and examples are used to illustrate how the choice of a particular approach affects the conclusions that can be drawn around a certain pharmaceutical question.

A particular emphasis during the course is on physics-based modeling and simulation of orally administered drugs, especially therapeutic macromolecules such as peptides and proteins. These are studied both with and without any delivery system, with the purpose of understanding how innate molecular properties affect them and their interactions with each other (binding, structural changes), and also how such properties affect interactions with formulation components (e.g. permeation enhancers), and finally how these processes are affected by e.g. concentration gradients and the surrounding physiology.


The teaching is based on lectures, computational laboratory work and a literature study.
Some teaching will take place online.
The course is given in English. .
Compulsory sections: laboratory work, literature study.


Written examination is performed at the end of the course (4 credits). In addition, passing the course requires approved examination of laboratory work (2.5 credits) and literature study (1 credit). .

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the University's disability coordinator.

Syllabus Revisions

Reading list

Reading list

Applies from: Autumn 2022

Some titles may be available electronically through the University library.

  • Ouyang, Defang; Smith, Sean C. Computational pharmaceutics : application of molecular modeling in drug delivery

    Chichester, West Sussex, United Kingdom: John Wiley & Sons Ltd., 2015

    Find in the library