FA811: Application of PBPK Modeling in Pharmaceutics - Biopharmaceutical Data Science

Students following the course are expected to

• have knowledge of basic organic physical chemistry, human physiology and basic pharmacokinetics
  
• be able to use scientific methods to assess and carry out experimental studies
• be able to use simple statistical or probability-theoretic models to describe and analyze a given data material
• be able to use selected physical models and explain the models' prerequisites and properties for collecting, calculating and interpreting data

General study skills:

The course requires active participation and knowledge of dialogue-based lectures.

The course will include extensive use of functions in SDU's e-learning system. Participation in the course therefore requires that the student masters these functions.

In addition, it is expected that the student:

• has knowledge of quantitative and qualitative methods for data production
  
• can collaborate in different learning situations
• can search for information on academic subjects in relevant databases
• can assess the relevance and reliability of the information found
• is familiar with SDU's digital learning platform and can use digital tools for professional production, knowledge sharing and professional presentation

The course is planned for student that have passed a bachelors degree in Pharmacy, Biomedicin or similar thereby having obtained a basic chemical background equal to KE501 and KE535 and human physiology and basic pharmacokinetics, such as SU503 or SU520. If students have completed BB511, then notes on pharmacokinetics can be provided before the start of the course. It is beneficial if the student have knowledge of physical chemistry, such as KE538 or BMB540, but this is not a prerequisite. 

• Physiochemical properties and cheminformatics
• Introducing the biopharmaceutical drug classification system (BCS). Permeability and solubility effect in the bioavailability of the compound.
• Dissolution, permeation, and absorption
• Introducing absorption distribution metabolism excretion (ADME), Defining absorption and all related terms in this context.
• Pharmacokinetic principles
• Defining distribution and elimination in the context of ADME in addition to volume of distribution.
• Physiological effects
• Introducing population estimates for age-related physiology (PEAR) and permeability limited models vs. perfusion limited models.
• Metabolism and transporters
• Defining metabolism in the context of ADME in addition to the Michaelis-Menten equation.

• Understand what biopharmaceutics is and the basic science behind biopharmaceutics.
• Have knowledge of in vitro methods used to assess drug behavior in vivo.
• Know about the biopharmaceutical drug classification system. 
• Define the fundamental parameters of biopharmaceutical drug disposition classification system (BDDCS).
• Have an idea of how Log D, solubility and pH and pKa interact in the in vivo systems.
• Understand the principle of liberation, absorption, distribution, metabolism, and excretion (LADME).
• Understand drug dissolution, permeation, and absorption which is a prerequisite for drug formulation development and estimation of drug bioavailability.
• Be able to identify factors affecting drug dissolution, permeation, and absorption.
• Be able to combine experimental and in silico data from a drug formulation with PBPK modeling to mechanistically interpret and predict the complex biophenomenon happening in vivo. 
• Understand the main drivers of distribution and elimination.
• Learn the methods to calculate the volume of distribution and clearance from intravenous pharmacokinetic data.
• Understand how the volume of distribution and clearance is related to the pharmacokinetic profile.
• Understand the physiological meaning of volume of distribution and clearance.
• Identify various body tissues and describe their properties in terms of composition and perfusion.
• Be able to discuss the relationship between physicochemical properties, tissue composition, and tissue partitioning of drugs.
• Discuss the rate-limiting steps in distribution and clearance and explain how these can be represented in a model system.
• Be able to evaluate how a specific compound, with a given physiology, would be expected to distribute throughout and be cleared from the physiology.
• List the main metabolizing enzymes and drug transporters.
• List the tissue specificities of important metabolizing enzymes and transporters.
• Explain the molecular basis for drugs acting as substrates for transporters.
• Interpret in vitro data for the kinetics of drug metabolism and transport.
• Use the in vitro data as input function in Gastro Plus to establish an in vitro - in vivo correlation IVIVC).
• Learn how to perform a mechanistically based simulation by using GastroPlus to predict drug absorption through various routes of administration in humans.

• Physicochemical properties and data collection with focus on biopharmaceutical data science
• Dissolution, permeation, and absorption in connection to biopharmaceutical data science
• Pharmacokinetic principles in connection to biopharmaceutical data science
• Physiological effects in connection to biopharmaceutical data science
• Metabolism and Transporters in connection to biopharmaceutical data science