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| Building on the Promise of Genomics | ||||
 Below, Dr. Peter S. Kim provides a brief overview of the genomics field and discusses the impact on Merck’s research and development now and in the future. For our non-scientific readers, please provide some background on the basics of genetics. DNA is the material that forms the more than 30,000 genes in human cells – the sequences of code that constitute the blueprints for proteins. DNA is built from four building blocks, usually referred to by the first letter of their chemical bases: A, C, G and T (adenine, cytosine, guanine and thymidine). The base A in one strand of DNA will only pair with T on another strand and C will only pair with G. This “pairing” phenomenon can be used to identify sequences of DNA as well as sequences of RNA, which is DNA’s chemical cousin. RNA directs the production of specific proteins. How does the recent identification of the human genome affect drug discovery? In 2000, scientists announced the complete sequence of the DNA that makes up the human genome. In the case of humans, the genome is a 3-billion-letter “sentence.” In that, scientists estimate that there are about 35,000 genes. Scientists need to pay attention to each of them and try to decipher which are going to be important in drug discovery. So, once you identify the important genes, you’re well on your way toward discovering a new drug? The information obtained from sequencing the genome is not all the information needed to discover new drugs. The DNA in cells is converted to information in the form of another polymer called RNA. Then, the information in that RNA is used to direct the production of a specific protein. If we have 35,000 genes in humans, it means that cells have the capacity to make at least 35,000 different proteins. But this 35,000 is only the core set; cells can make many variants on this set. The important thing to recognize is that each of those proteins is potentially a new drug target. However, the functions of almost half of the proteins operating inside human cells are not known. So, while having the sequence of genes (from which we can infer the sequences of the corresponding proteins) is useful, there is still a lot of work to be done. A critical element to understand is how changes in gene expression are related to disease states. Gene expression refers to the process by which the DNA is used to produce RNA, and then RNA is used to produce protein. When a gene is “expressed,” it is turned “on” and the result is that the protein specified by the gene is produced inside the cell. The activity of genes is highly variable. For example, every cell in the body contains exactly the same DNA. But, of course, a brain cell is very different from a skin cell. The difference comes from whether certain genes in the cells are turned “on” or “off” because that change leads to a change in what the cell looks like and how it behaves. This regulation – turning genes on and off – also occurs regularly in normal cells. In diseased cells, this regulation often goes awry. Sometimes genes are turned on at a level that is too high. That happens with many cancers, for example, in which cells divide uncontrollably. In other diseases, certain genes are turned down or are what we call “repressed.” Scientists need to understand gene expression patterns that are associated with disease because it provides tremendous biological insights into how to correct a problem. How do you identify gene expression patterns? Gene expression patterns (which occur as genes are turned on or turned off in normal states as well as in disease states) can be followed using various technologies such as DNA microarrays, SNPs and gene expression profiling. One technology that Merck scientists are extremely excited about involves the use of gene expression arrays or “DNA chips.” The little black one-half inch by one-half inch area in the middle of the chip contains pieces of DNA that allow the monitoring of 25,000 different genes at once. Merck scientists can open a specific human cell, under specific conditions, take the contents of the cell and put them on a DNA chip. Then, using special scanners, they can determine which genes were “on” or “off” in the cell at the precise moment that it was opened. Using pattern recognition methods and computer algorithms, our scientists can then analyze these patterns of gene expression in ways never possible to do by just looking at one gene at a time. This technology provides us with tremendous biological insights into what is going on in the cell and into what goes wrong in diseased cells. It also allows us to identify new potential drug targets. DNA microarrays These are also known as DNA or gene chips; the chips can track tens of thousands of molecular reactions in parallel on a single tiny chip. The chips can be designed to detect specific genes or to measure gene activity in tissue samples. Gene expression profiling By measuring the amounts of different mRNAs in a tissue sample, scientists can produce an expression profile. Expression profiling has proven invaluable in understanding how tissues compensate in a disease state as well as understanding the functions of genes. Single Nucleotide Polymorphisms (SNPs) Another key aspect of the field is related to the analysis of SNPs (pronounced ‘snips’). To understand them, let’s go back to DNA. The sequence of the letters A, C, G or T – the nucleotides discussed previously – is similar, but not exactly the same, in different people. Indeed, variations in our DNA are what make us individuals. Nucleotides differ, on average, once every 1,000 or so letters in each person. These differences are given a fancy name: single nucleotide polymorphisms (abbreviated SNPs), referring to a place where a single base – A, C, G or T – has been changed and is different, for example, between each one of us. Right now, scientists have catalogued several million different SNPs. These SNPs may offer a tremendous advantage in analyzing the genetic basis of human disease. Because SNPs of healthy people can be compared with SNPs from people with a certain disease, better identification of human disease genes can occur. We can identify the “markers” that make the difference. For example, there is one SNP – a variant in a particular gene called Apo-E – that predisposes a person toward the development of Alzheimer’s disease. Scientists also have identified another SNP that makes people resistant to HIV infections. These are examples of simple SNP correlations. Most correlations are much more complicated – such as those involved in hypertension – that involve many different genes. Scientists have to determine how these factors interact because many of the diseases we tackle will involve multiple genes and multiple SNPs. Merck is currently using SNP technology and developing it further. Given the sequence of the human genome, our goals are to incorporate these technologies and this information into our laboratories to accelerate our drug discovery and development programs. While these new technologies will accelerate drug discovery, that is not the only aspect of research that will be affected. How so? Also exciting is the opportunity to develop genomic analyses for preclinical studies (drug testing before human trials) to evaluate the safety and effectiveness of experimental compounds. Now, preclinical testing takes a long time and a lot of different studies. Merck is aiming to develop genomic methods to predict which molecules will have bad characteristics (such as undesirable side effects) so that those molecules can be removed early in the process and we can focus on improving success for the ones that are taken forward. This technology is also going to allow us to do better and faster clinical trials because we can identify genetic markers that are predictive of an outcome in the clinic. In some cases, SNP markers may also allow differences between individuals (for example, variations in the enzymes that metabolize drugs) to be taken into account in clinical trials to understand why some patients do not respond well to some of our drugs. Lastly, the potential exists for us to develop pharmacogenomic tests that will enable physicians to help choose drug therapies based on a genomic analysis of patients’ DNA, and thereby allow physicians to individualize drug therapies for their patients by selecting drugs most suited for their condition. Will the acquisition of Rosetta Inpharmatics help Merck advance in these areas? The Rosetta Inpharmatics acquisition in 2001 will help to rapidly advance these technologies in Merck laboratories. Rosetta has an outstanding group of scientists who have developed innovative genomic technologies and excellent computational tools to analyze genomic information. The acquisition of Rosetta fits Merck’s objective of expanding our lead in cutting-edge science by continuing to enhance our internal research capabilities. Rosetta will be a tremendous asset in helping us more efficiently analyze gene data and intelligently select drug targets. We also continue to aggressively scan the scientific universe seeking to expand our science capabilities through external alliances, licensing arrangements and niche acquisitions that will augment our existing product franchises and help us create new ones in markets with unmet medical needs. So far, you’ve talked about the impact on science and drug discovery, but what does all this new technology mean for patients and their health? Today, pharmacogenomics is making its greatest impact in the field of oncology, where there exists a tremendous and urgent clinical need to identify specifically which drugs will increase survival rates for cancer patients. Another early application is likely to be in variations in drug metabolism. In general, pharmacogenomics will be used first in those diseases and conditions that have the greatest clinical need to determine patient responsiveness to pharmaceutical products. In its next stage, genomic and pharmacogenomic technologies may have several potential applications, including the prediction of disease, prediction of disease progression and prediction of therapeutic efficacy. The promise of this technology is significant with many potential applications, for example:
You’ve said you want Merck to lead in this field. How does the Company compare to its competitors? |
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| Copyright © 1995-2002 Merck & Co., Inc., Whitehouse Station, NJ, USA. All rights reserved. |
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