techniques applied mainly in clinical drug development. In this 2-days hands-on workshop, basic elements of pharmacometrics are introduced and explored.
To alleviate or cure human diseases, drug treatment plays a major role. However, the development of innovative drugs is becoming more and more challenging. Traditional experimental methods alone cannot cope with the increasing factual knowledge about the functioning of a diseased human being. Particularly, how drugs exert their action and how they are optimally administered is a problem too big for pure experimentation. Actually, drug development suffers from many costly failures.
A natural means to overcome such shortcomings is to combine experimentation with mathematical modeling. Over the last 30 years, different groups within and outside the pharmaceutical industry suggested the application of “Model-based drug development”, “Systems Biology”, or “Quantitative Systems Pharmacology”. All these terms address the importance of mathematical modeling in the development of drugs.
Progress has been made in that nowadays the outcome of a clinical trial is simulated beforehand leading to better trial designs. Simulating clinical trials outcome comprises the quantitative consideration of how the drug reaches the site of action, how it acts on the body, and how disease processes are affected. Importantly, between and within variability in all measured responses needs to be taken into account.
Reference: Ronald Gieschke, Daniel Serafin. Development of Innovative Drugs via Modeling with MATLAB. Springer (2014)
Prerequisites: Basic knowledge of Ordinary Differential Equations (numerical treatment) and Statistics (distributions, parameter estimation)
Course Software: Berkeley Madonna. Bring your own notebook to the course or use a computer from the CIP-cluster. Install Windows Version 8.3.18 (C-based) or Version 9.1.9 (macOS) from https://berkeley-madonna.myshopify.com/pages/download and explore its features; use “Continue in demo mode”