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4 Screening Technologies II: Toxicogenomics
Pages 28-49

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From page 28...
... Four speakers from three different companies -- Iconix, Bristol-Myers Squibb, and Abbott Pharmaceuticals -- explained how their firms are developing and applying toxicogenomic tools for drug safety. The goal was to describe the range of drug safety data now being supplied by toxicogenomics -- from preclinical safety assessments to the clinic.
From page 29...
... (FDA, 2006:9) Halbert explained that the fundamental underlying principle of toxicogenomics is that compounds with similar mechanisms of toxicity and efficacy will have similar gene expression profiles.
From page 30...
... It allows researchers to identify the mechanisms of toxicity of novel compounds through comparison with the database's reference set of compounds, to benchmark the effects of unknown compounds against these reference compounds, and to identify potential biomarkers that can be used to predict both toxicological and pharmacological end points in rats. The DrugMatrix database was assembled by accumulating standardized information on more than 640 compounds across nine different tissues in male Sprague-Dawley rats.
From page 31...
... To use these biomarkers, a gene expression profile is generated for a test compound. If the test compound matches any biomarker for a particular end point, this indicates that the test compound causes gene expression changes in that tissue, changes similar to those caused by compounds in the class used to build that biomarker.
From page 32...
... As is well known, the renal tubules are a major site of toxicity and can be damaged by a variety of drugs. Working with a set of 119 compounds that caused the kind of delayed kidney damage of interest -- that is, no histopathological injury at day 5 but measurable injury at day 28 -- the researchers identified a multigene biomarker that could predict the kidney damage from gene expression patterns that were apparent on day 5.
From page 33...
... In this experiment, gene expression levels were measured after five days, prior to any indication of histopathological injury to this tissue. Many of the individual genes that had increased expression are relevant to the types of injury that would be expected in nephrotoxicty.
From page 34...
... As a result, expression profiling is increasingly being incorporated into standard lead optimization and preclinical studies, and is being used as part of the general evaluation performed when one is deciding whether to take a particular compound forward. More specifically, toxicogenomics is being applied in a variety of ways to drug discovery and the development interface.
From page 35...
... . In the graph of that PCA, control treatments can be seen clustered near the bottom, all in the same color; the TNF-treated cells can be seen clustered near the top of the graph, again in the same color; and scattered around the graph are clusters of other colored dots representing the outcomes of various treatments.
From page 36...
... The control treatments (non-TNF-treated cells) are clustered near the bottom, in orange; the TNF-treated cells are clustered near the top of the graph, in yellow; and scattered around the graph are clusters of other colored dots representing the outcomes of various drug treatments.
From page 37...
... The various tools also have different abilities to distinguish the signals from the noise. With the goal of learning how toxicogenomic data compare with results achieved through standard toxicology assessments, BMS now includes transcriptional profiling as part of routine toxicology assessments and prior to conducting GLP (good laboratory practices)
From page 38...
... Thus the researchers concluded that analyzing gene expression at a global level in this way can provide types of information similar to those gleaned during standard toxicology assessments. Different compounds can display very different patterns when viewed from this global perspective (see Figure 4-4)
From page 39...
... The marks at the bottom in green represent genes that were repressed, while those at the top in red represent genes that were induced. Within the liver, 222 or 1.4 percent of transcripts changed at p <0.01 level.
From page 40...
... The first resulted in expression changes in 11.4 percent of the measured genes and was indicative of a nonspecific compound that was hitting multiple targets; the second resulted in a 2.9 percent expression change, which was associated with potent pharmacology as well as myopathy; the third led to a 1.4 percent expression change and was determined to be a highly selective compoundFigure 4 -4 off-target effects; and although with no obvious the fourth resulted in an 8.8 percent expression change, it was determined that these changes were associated with an acute phase response at the site of injection, which was largely irrelevant to the pharmacology of the drug and absent when color the drug was delivered via a different route. SOURCE: Cockett, 2007.
From page 41...
... Thus BMS has learned to use global transcriptional profiling in its drug safety work. Generally speaking, increases in transcriptional change correlate with increasing pathology and increasing dose, and a level of transcriptional change greater than 3 percent suggests drug-related pathology.
From page 42...
... In short, Abbott uses this technology for lead optimization rather than for safety assessments. Before the researchers could begin using this technology, they had to develop a hepatotoxicity reference set by administering various doses of multiple known hepatotoxicants and multiple known nonhepatotoxicants to rats, and then observing gene expression changes in a set of 40 genes.
From page 43...
... The real question was whether gene expression patterns observed earlier in the process could predict hepatotoxicity prior to its physical manifestation. To answer this question, the researchers compared the results of shortterm gene expression assays -- performed 3 or 5 days after exposure -- with the results of 2-week toxicology studies.
From page 44...
... Toxicogenomics can be useful for this purpose because various gene expression patterns have been associated with specific mechanisms. An important caveat is that toxicogenomics should be relied upon not as a way of identifying mechanisms of toxicity, but as a way of generating a hypothesis that This section is based on the presentation of Dr.
From page 45...
... Spear pointed out that the gene expression assay was used to generate a hypothesis -- that the mechanism of toxicity was inhibition of mitochondrial function -- but other tests were then used to test this hypothesis. The test for toxicology is still clinical chemistry and histopathology, and gene expression studies are not going to replace in vivo toxicological studies.
From page 46...
... During the lead optimization process, molecules are characterized with a battery of in vitro and in vivo assays to evaluate various physical, chemical, pharmacological, metabolic, pharmacokinetic, and toxicological properties. If assays are to be used to help make go/no go decisions early in the development process, they must have two important characteristics: they must utilize limited quantities of compound (milligram to gram range)
From page 47...
... Gene expression profiles were created from the livers of the rats treated for 1 or 5 days, while the livers were examined histopathologically for the rats treated for 28 days to determine whether treatment with a particular compound had led to bile duct hyperplasia. Then the researchers looked at how often the signature correctly predicted the presence or absence of bile duct hyperplasia after 28 days of dosing.
From page 48...
... They then used the DrugMatrix database to evaluate the gene expression profiles at the various doses. At doses greater than 200/mg/kg/day, there was a significant correlation with several gene expression profiles in the database that were induced by hepatic toxicants, such as dipyrone and econazole.
From page 49...
... These gene expression assays, however, apply only to rat models, and the next challenge is to transition from prediction of toxicity in rats to prediction of toxicity in humans.


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