John Hwa is a professor of medicine and the director of cardiovascular pharmacogenetics at Yale School of Medicine. Along with Dartmouth genetics professor Jason H. Moore, Hwa recently coauthored an editorial in the journal Current Molecular Medicine. The article, titled Pharmacogenetics and Molecular Medicine: So Close and Yet So Far introduces a new review series of eight articles contributed by different researchers in the field of pharmacogenomics. The News sat down with Hwa and his colleague, Yale postdoctoral fellow Jeremiah Stitham, to understand the latest advances in the field. <\/p>\n
Q. How would you define the fields of pharmacogenomics and personalized medicine to the general public? What are the basic underlying principles and ideas? <\/p>\n
H. About 100,000 people die each year from adverse side effects to medications, and millions of others have some sort of harmful drug reaction. The idea of pharmacogenetics is to try and figure out, based on genetics, who is going to suffer problems and who will benefit the most from taking a particular drug. Though there are actually many definitions out there, the simplest definition is that it is a combination of pharmacology and genetics: pharmacogenetics. It is the use of genetic data to understand how a disease process is influenced by genetics, progresses as a result of genetics, and responds to drugs. In terms of the pharmacology, there are two main components, pharmacodynamics and pharmacokinetics: the former dealing with how genetics influences the drugs effect on the disease and the latter dealing with how genetics influences the metabolism of the drug. <\/p>\n
Q. As your lab specializes in cardiovascular medicine, what has been the core focus of your research in particular? <\/p>\n
H. Commonly used drugs that are taken for pain, arthritis and fever can have a profound effect on the cardiovascular system and one of the main reasons for this is because of problems with [the molecules] prostacyclin and thromboxane. This has become a very major concern in cardiovascular medicine and the clinical sciences. I am part of a large consortium based at the University of Pennsylvania that has come together to address this problem. We are trying to figure out who would benefit from these common drugs without adverse side effects and who should be careful about taking these medications: essentially the concept of personalized medicine. Currently, my lab is focusing our efforts on the diabetic population, because they are particularly at risk for cardiovascular diseases. We have all the tools now and are beginning to make sense of the data. There is not doubt that in the near future, we will be able to predict who is going to have adverse side effects as a result of a drug and who is going be fine and benefit from the treatment. <\/p>\n
S. That is basically the third component of pharmacogenomics: the first two being how genetics affects drug response and drug metabolism and the final component being how it is going to affect people with adverse reactions. <\/p>\n
Q. Which recent advances and discoveries have been game-changers? Have any new experimental techniques and technologies really impacted the way the scientific community studies this field? <\/p>\n
H. One major advance has been the advent of genetic sequencing. Back in 2001, sequencing used to cost a fortune, but now prices have gotten significantly lower. Whole-genome sequencing now costs a few thousand dollars, and the price is going to drop even further. I have no doubt that one day everyone will sequence his or her genome. <\/p>\n
In many ways, we are overwhelmed with data from all of these sources. The real question now is the hypothesis-generation procedure: how are you going to make sense of all of this information? Certainly with an area like pharmacogenetics, there is a vast amount of data that is being collected, at multiple levels, and ultimately it is going to be a cross-disciplinary collaboration between the basic scientists, the translational scientists, the clinicians, the bioinformaticists, and the outcomes specialists. It is going to be a collaboration that makes sense of the massive data sets that are being generated and applies this knowledge to clinical practice. <\/p>\n
Q. In the title of your editorial, you state that the scientific community in this field is so close and yet so far. What are the major challenges currently faced by the fields of pharmacogenomics and personalized medicine? <\/p>\n
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