Computational Drug Discovery and Development
The discovery and development of new drugs is in a stage of rapid acceleration, due to the confluence of four factors: easy access to big data through internet, an explosion of biological structural information, advanced modeling, and extremely cheap computer power through clouds. In one sweep, the course takes the student from the inception of a target and a potential drug candidate, to clinical trials.
The student will learn the following concepts:
the organization of pharmaceutical molecular research in the discovery pipeline workflow paradigm
the sourcing of (structural and property ) data through webportals
important molecular property calculations, such as charge and pK, and calculation of derived properties such as solubility and logP
the principle of screening ultra-large databases, and relation with chemical informatics concepts such as similarity and molecular fingerprinting
docking, and the relation to fragment based drug discovery and high-throughput screening
correlation models for toxicity and relevance for clinical trials.
In the course, we will make frequent reference to real business cases, from small companies from the local Leiden BioScience Park and international pharma. In particular, we will use the development of new kinase inhibitors for cancer therapies as testbed. In short, the returning theme is: why are new cancer medicines so horribly expensive? And what can we do to improve on that?
The course is in the form of 12 lessons, of each 2 times 45 minute lectures. In addition, there will be three blocks of practical courses, of each 2 hours. It is the intention to invite guests from the Leiden BioScience Park to illustrate the abstract teaching materials.
At the end of the course, the student will be familiar with the way pharmaceutical research is organized, and will have a good overview of the most common calculation methodologies. The student will be able to digest presentations from recent conferences, some of which will be used in the course as supporting materials.
No prior knowledge in quantum chemistry or thermodynamics is required. But the student is advised that the learning is steep, and that the focus is on the mathematical background of the various methods.
Mode of Instruction
Lectures and hands-on workshops.
The teacher will provide a reader (collection of papers), a powerpoints and examples of exam questions. Students interested in more background are advised to acquire ‘Molecular Modelling, principles and applications’ from Andrew leach, second edition (Pearson/Prentice hall, 2001)
Exam is 3 hours closed-book, with one question per lesson. Example questions will be distributed during the course.
Some of the teaching material is based in the course ‘Molecular Modeling’, given in previous years by the same teacher. Presence at the lectures and workshop is obligatory.
Leiden, Gorlaeus Laboratories