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In Silico ADME and Predictive Toxicology
In silico methods, defined as experiments and compound testing performed via computer simulation, have become an important tool in drug discovery and in the development of medicines. Predictive in silico methods are getting considerably more reliable, they cover a broader spectrum of predictive endpoints and are getting easier to use also for non-specialists. Reliable predictive models may replace costly experiments and thereby contribute to a cost-reduction of the drug discovery and development process. This course will provide the participants with a comprehensive overview of in silico methods in drug discovery and development as well as where they can be used and what their strengths and limitations are. Additionally, students will get hands-on experience with several predictive in silico methods, e.g. web-based tools to predict simple ADME/Tox endpoints and purpose-developed software to predict more complex ADME/Tox endpoints. This course and the other single courses of the SafeSciMET programme are part of a new European Master for Advanced Safety Sciences for Medicines degree and also provide new opportunities for Continuous Professional Development (CPD). Part-time study, spread over 2-5 years, is possible.
Key areas covered by this course are:
- Computational tools used in drug discovery and development, with focus on ADME/Tox,
- Absorption and distribution from a PK point of view,
- Critical analysis of experimental data,
- Prediction of absorption and distribution,
- Phase I and II metabolism – the Cytochrome P450 enzymes,
- Prediction of metabolism,
- Prediction of site of metabolism,
- Prediction of toxicity (e.g. genotoxicity, phospholipidosis, hERG, etc.),
- Genomic effects on metabolism and toxicity,
- Different QSAR systems available.
The closing date to register for this course is April 18, 2016.
On successful completion of the course, participants should have an integrated hands-on experience with in silico methods for prediction of various ADME/Tox relevant end- points. More specifically, participants will be able to:
- Gain comprehensive overview of up-to-date in silico methods used in drug discovery and development,
- Explore and understand the diversity of large datasets,
- Critically analyse experimental data,
- Use web-based tools to predict simple ADME/Tox endpoints like drug-likeness, solubility, absorption, genotoxicity, phospholipidosis, etc.,
- Use purpose-developed computational tools for prediction of complex ADME/Tox endpoints like prediction of metabolism and site of metabolism,
- Understand the principles of the most commonly used types of predictive methods.