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Since the Human Genome Initiative was announced in 1986 and with the increased maturity of related technology, human genetics and its applications have been receiving increased attention, both in academics and in industry. Statisticians with knowledge of statistical genetics are in demand. This short course will introduce the basic concepts of statistical genetics, with an emphasis on the pharmacogenomics area.
Pharmacogenomics (or pharmacogenetics) is one of the applications in the pharmaceutical area, both in academics and in industry. There are three goals for using the pharmacogenomics approach: (a) to identify genetic profiles for drug responders, (b) to identify genetic profiles for adverse events, and (c) to identify disease-causing genes for new targets. These activities usually take place in the exploratory clinical stage or discovery stage.
Statisticians who are new to this area often become disoriented due to a lack of background knowledge. In order for statisticians to work in these areas, they must have a basic understanding of statistical genetics. Without a proper understanding of the science, one can lose perspective on the problem. Statistical geneticists who move into industry often lack an understanding of the overall process and relevance. It is virtually impossible to implement some approaches in the industrial setting. Likewise, it is virtually impossible to implement certain approaches in different stages of the drug-development process. Statisticians and statistical geneticists need to be familiar with these limitations.
This full-day short course is designed to help statisticians (a) expand their fundamental knowledge of genetics, (b) understand the random mechanisms in genetics, (c) learn how statistical methods are applied to the study of genetic association, and (d) understand statistical issues and pitfalls. This course is also designed to help statistical geneticists learn how to apply statistical genetics in the pharmaceutical area. Two real examples, one from the discovery stage and one from the phase 3 trials, are provided to develop the whole picture and explain the restrictions of different approaches. Knowledge of basic statistics is requisite.
Microarray and proteomics will be introduced, but they will not be the focus of this course. Those who want to gain significant knowledge in these two areas should seek other short courses.
Fees: M- $325 ($430 after July 18), NM- $415 ($520 after July 18), SM- $200 ($325 after July 18)
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= Applied Session,
= Theme Session,
= Presenter