Toxicogenomics Data: The Road to Acceptance
Questions abound regarding the use by regulatory agencies of data from microarray
experiments. How does a regulator deal with risk assessment data that scientists
are often unable to interpret--data that some companies are anxious to submit
and others to withhold? How does this same regulator evaluate information that
is produced without universally recognized standards for laboratory protocols
or data formats? Pharmaceutical and chemical companies have their own questions.
Do you submit all your data voluntarily, without knowing whether regulators
will be able to understand it, and if and exactly how they will use it? Will
submission of such complex data slow down approvals? What if data that cannot
be interpreted now are later shown to indicate toxicity, perhaps at low levels
that couldn't be detected in animal testing? Could lawsuits follow? Regulatory
penalties?
These and other questions have been discussed at numerous meetings between
industry, environmental groups, the Food and Drug Administration (FDA), which
regulates medications, and the Environmental Protection Agency (EPA), which
regulates pesticides and industrial chemicals. Discussions have progressed
significantly in the last two years, according to John Leighton, supervisory
pharmacologist in the Division of Oncologic Drug Products of the FDA Center
for Drug Evaluation and Research (CDER). At an FDA-sponsored workshop held
in May 2002, Leighton says, the take-home question was whether microarray technology
was sufficiently developed for scientific purposes. Within 18 months, at a
follow-up workshop in November 2003, he says, "the issues had shifted from
'Is the technology useful?' to 'How is it useful?'"
Proving that microarray data, or "expression signatures," can be valid measures
of environmental exposure is a major accomplishment of a 1999-2003 research
program by the Health and Environmental Sciences Institute (HESI) of the nonprofit
International Life Sciences Institute. The HESI experiments, published in the
March 2004 toxicogenomics issue of EHP, showed that patterns of gene
expression detected in microarray experiments can give insight into biologic
mechanisms, and can even distinguish between damage found in different cell
types. Although most expression signatures still can't be interpreted or linked
to biologic effects, officials at both the FDA and the EPA express optimism
that the use of microarray data could help them better protect public health.
Industry, however, taken as a whole, may not be quite so sure.
Efforts to encourage communication between regulators and industry have included
workshops held by the National Research Council (NRC) Committee on Emerging
Issues and Data on Environmental Contaminants, which is funded by the NIEHS.
Since its establishment in April 2002, the committee has held seven workshops
to discuss issues related to the future use of toxicogenomics data in government
risk assessment and regulatory decision and policy making. These issues include
the many challenges that remain to
be resolved before these tools find direct application in chemical risk assessment,
says David Eaton, chair of the NRC committee and director of the NIEHS Center
for Ecogenetics and Environmental Health at the University of Washington.
Because of the expense involved in running microarray experiments, including
the costs of analyzing data, microarrays are generally not used in detailed
dose and time-course studies, says Eaton. As a result, current microarray data
often provide a limited snapshot of information that Eaton says can be very
useful in terms of generating hypotheses about mechanisms of exposure, although
the application of such information for regulatory purposes is fraught with
uncertainty.
Government's Take on Microarray Data
"We think there are powerful uses for genetic data, including microarray
data, in the real world of drug safety, to both test products and do 'forensic'
studies--that is, go back and investigate safety problems after marketing," says
CDER director Janet Woodcock. "In cases of some adverse drug effects, companies
may be able to go and look for specific genotypes that are distinctive and
at risk for an adverse event." Agency regulators, she adds, hope that intractable
drug toxicity problems, such as hepatotoxicity, could be solved through microarray
or gene expression technologies.
EPA representatives hope that microarray technology, along with proteomics
and metabolomics experiments, will help the agency better screen the vast number
of chemicals it is mandated to regulate. Using traditional tests, it can easily
take 3-4 years and $20 million to test the toxicity of a pesticide, says
Robert Kavlock, director of the Reproductive Toxicology Division in the EPA
Office of Research and Development. "In the long run, we expect that the use
of 'omics' technologies can be applied to a variety of bioassays, some in
vitro, some in vivo, that will help us prioritize chemicals for
testing in the more lengthy, expensive, and animal-intensive testing batteries,
and perhaps even to guide selection of which tests should be done within those
batteries," says Kavlock. "By doing so, we will become more efficient and effective
in our utilization of animal tests."
"Genomics won't replace animal testing, not yet," adds William Benson, director
of the Gulf Ecology Division of the EPA National Health and Environmental Effects
Research Laboratory. "But we hope it will allow us to use animals more wisely."
Microarrays and other "omics" technologies could also be used in environmental
monitoring, such as water testing. As the technology decreases in cost, local
regulators may be able take a microarray chip into the field, apply water samples,
and get an answer right there regarding the presence of bacteria, viruses,
and other pathogens, according to Kerry Dearfield, senior scientist for science
policy in the EPA Office of the Science Advisor. Dearfield, along with Benson
and Kathryn Gallagher, science policy council staff in the Office of the Science
Advisor, wrote a March 2004 EPA draft white paper on the impact of genomics
technologies on EPA regulatory activities.
Although both the EPA and the FDA have discussed possible uses of microarray
data, only the FDA has issued requirements for the submission of such data.
At press time the agency was working on a final version of its "Guidance for
Industry: Pharmacogenomic Data Submission," released in draft form in November
2003. Under the draft guidance, companies may be required to submit microarray
data used to determine differential dosing of a medication by genotype during
development (a requirement that applies to animal testing as well as human
clinical trials). The guidance also encourages, but does not require, companies
to develop suitable genetic tests for such medications to allow physicians
to determine if a drug is appropriate for a given patient.
"The centers for drugs and devices are working together for the development
of drug-device combinations," says Atiqur Rahman, acting deputy director
for the CDER Division of Pharmaceutical Evaluation 1. "If a drug's approval
becomes based upon a specific test, you can't approve the drug unless the test
is available."
The draft guidance also encourages, but again does not require, voluntary
submission of microarray data from exploratory studies such as experiments
to screen multiple compounds for possible toxicity or efficacy. Companies are
also asked to supply research data resulting from general gene expression analyses
in cells, animals, and humans, as well as analysis of single-nucleotide polymorphisms
in trial participants.
In addition, all data on "known valid biomarkers," including those collected
during exploratory studies, must be submitted to the FDA. Although the guidance
does not specify the types of biomarkers that must be submitted, Woodcock clarifies
that the agency is mainly interested in so-called safety biomarkers, those
that indicate toxicity. "Companies don't have to submit any data on nonclinical
efficacy biomarkers," she says.
Currently, the EPA's official dictum on the regulatory use of microarray
data is limited to a four-page "Interim Policy on Genomics" issued in June
2002. The interim policy states that microarray data are expected to be valuable,
and that they "may be received as supporting information for various assessment
and regulatory purposes, e.g., identifying an environmental stressor's mode
or mechanism of action." But the interim policy does not provide any details
on potential required submissions of gene expression data. There is no current
effort at the EPA to expand or update the interim policy.
What It Means for Industry
Industry response to these regulatory efforts ranges from enthusiasm to extreme
caution. "Some companies will not test a drug with a microarray experiment
that has any chance of becoming part of a regulatory package," says Kurt Jarnagin,
vice president for biological sciences and chemical genomics at Iconix Pharmaceuticals. "And
then there are companies who view [submission of microarray data] as a positive,
who say the FDA gets more information, we get more information, and we might
find a positive aspect to our drug that we didn't know about."
There are already a number of drugs approved for people with specific genetic
variations. Most are powerful cancer drugs for which the boundaries between
efficacy and toxicity are narrow. One example is imatinib mesylate (trade name
Gleevec), which is approved for patients with a specific type of leukemia characterized
by a chromosomal rearrangement in the cancerous cells. Another example is trastuzumab
(trade name Herceptin), an intravenous treatment for advanced metastatic breast
cancer. Trastuzumab is effective in treating tumors that produce excess amounts
of the HER2 protein, a tyrosine kinase receptor.
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Drug data dilemma. Researchers and regulators alike are struggling
with the complexities--and uncertainties--of toxicogenomics data.
image credit: AstraZeneca
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In addition to determining who is most likely to respond to a drug, genetic
studies could also be used to screen out those most susceptible to toxic side
effects. One example is the case of the lung cancer drug geftinib (trade name
Iressa), which inhibits a tyrosine kinase that is overexpressed in non-small
cell lung cancer, the leading cause of cancer deaths in the United States.
After the drug was approved, the FDA received reports of severe, sometimes
fatal, toxicity in 0.3-2.0% of patients receiving the drug. In addition,
during clinical trials, the drug was effective in only 10-19% of persons
with non-small cell lung cancer. Preliminary results published 20 May
2004 in the New England Journal of Medicine indicate that the drug is
effective only in people who have heterozygous mutations in the tyrosine kinase
epidermal growth factor receptor, coded by the gene EGFR.
Microarray data were not submitted during the approval process for any of
these drugs, but could be used in the future to help develop population-specific
treatments, according to Rahman. "A certain type of gene expression constituting
a gene signature may help determine if a person is a candidate for treatment
with a particular drug and is likely to respond to the therapy," he says.
In
contrast to the pharmaceutical industry, "the chemical industry is not chomping
at the bit to use toxicogenomics data," claims Linda Greer, director of the
Natural Resources Defense Council public health program and a member of the
NRC committee. "The status quo works better for them rather than a system where
chemicals can be screened systematically," she adds. More than 90% of the industrial
chemicals in commerce have not been tested for their toxicity, Greer says,
and better screening might cause increased scrutiny of such compounds under
the Toxic Substances Control Act (TSCA) and the Federal Insecticide, Fungicide,
and Rodenticide Act (FIFRA).
TSCA gives the EPA authority to require reporting or testing of industrial
chemicals that may pose an environmental or human health hazard, and to ban
the manufacture and import of chemicals that pose high risks. However, the
EPA is not required--nor does it have the resources--to perform extensive toxicity
testing on every industrial chemical available for sale in the United States.
Nor can chemical companies increase their profits by determining genetically
based differences in responses to their general-use products. "What we sell
is going to be out there for the general population to use, so we're compelled
to protect the most sensitive individual," says George Daston, a senior toxicologist
in the Central Product Safety group of Procter and Gamble.
Risk exposure testing for industrial chemicals can also be less straightforward
than pharmaceutical testing, increasing challenges for both industry and the
EPA. In contrast to pharmaceuticals, which people generally are exposed to
at known doses for intended biologic effects, environmental exposures to industrial
chemicals among the general public are often quite low. In addition, people
are often exposed to mixtures of compounds--for example, to several pesticides
from a piece of fruit, or to hundreds of chemicals from swimming near a storm
sewer outfall. As a result, singling out the effects of a single industrial
compound can be extremely difficult.
Nevertheless, some chemical companies are conducting microarray experiments
to better understand mechanisms of toxicity, which could lead to better risk
assessment information regarding susceptible populations, co-mixtures of chemicals,
and low levels of exposure, according to Greer and Dearfield. For example,
Greer says, microarray studies could build on research published in the August
2004 issue of EHP linking exposure to the complex mixtures of disinfection
by-products in drinking water and low birth weight in children of women with
polymorphisms in the CYP2E1 and C677T genes.
Research such as this raises tough regulatory issues for the EPA, Greer adds--is
the EPA going to lower the standard of disinfection by-products to protect
what might turn out to be a substantial group, or are they going to warn people
and tell them to get tested for genetic susceptibility? "Our answer," she says, "is
that regulators need to protect the most susceptible individuals. You can't
tell people not to drink water or to buy bottled water."
Microarray data may also be able to detect cellular activity in whole animals
at levels far lower than those that cause discernible changes such as tumors
or weight loss. In recent studies, researchers at the Microarray Center of
the NIEHS National Center for Toxicogenomics (NCT) detected early indicators
of mitochondrial damage before any adverse effect could be detected through
traditional toxicity tests, says Microarray Center director Richard Paules.
Such research doesn't necessarily indicate that such low doses are toxic, says
Paules, "but these gene expression changes could be an indication that higher
or longer exposures have the potential to cause adverse effects and should
be studied more closely."
Signatures of mechanisms of toxicity in different species may also improve
researchers' ability to compare the results of animal studies and human health
outcomes. A chemical that causes, say, cancer in a rat may not have the same
effect in people if the two species process the compound differently. Such
research is especially important for the manufacturers of industrial chemicals,
who do not test their products on humans, according to Jim Bus, director of
external technology at The Dow Chemical Company and a member of the NRC committee.
Concerns Voiced
Although the use of microarray data and acceptance by regulators can be beneficial
for pharmaceutical and other chemical manufacturers, many industry representatives
still express concerns about the use of such data by the FDA and the EPA. One
of these concerns--which runs contrary to the optimism expressed by government--is
that submission of complex expression data will slow processing and approval
of applications rather than streamline the process. Current FDA approval times
for regular drug applications are about 18 months, down from 30 months several
years ago. Approval for priority drugs with a public health benefit, such as
AIDS medications, can take as little as 6 months, according to Woodcock.
Pharmaceutical and chemical companies have also expressed concern that the
FDA and the EPA might overreact to microarray data. The primary issue, according
to Daston, is determining what type of signature constitutes an adverse effect;
the challenge is to distinguish adverse responses to a chemical exposure from
homeostatic responses--that is, normal changes that may indicate a cell is
disposing of a toxicant in a way that will not lead to lasting damage or that
may not be related to the exposure at all.
Dearfield explains further: "Gene expression changes all the time. You can
walk from a dark room into the sunlight, and you're going to get all kinds
of genomic signature changes. Is that bad? No--it's the way the body normally
operates. You need to sort out that kind of change from a change caused by
an adverse stressor."
Similarly, there is concern that
the agencies will be "excessively reactive" to single gene changes, says Jarnagin. "Hypothetically
you do a microarray expression on a potential drug's effect, and lo and behold,
the oncogene RAS is elevated five- or tenfold. Using a [toxicogenomics] database,
you can see that there are many approved drugs that elevate RAS. Every drug
in our database elevates at least one known oncogene. None of these drugs are
known to cause cancer at therapeutic doses."
Although the FDA draft guidance states that voluntary submissions of data
will not be used for regulatory purposes, some companies still are reluctant
to part with the results of exploratory microarray experiments. Some companies
fear that proprietary data from one application will be used to judge data
in another. In response, Woodcock says, "We cannot apply proprietary data to
another application; we can't make it public." However, she says, regulators
do learn from the reviews they conduct. And although they can't directly compare
data from one application to another, problems they see in one application
might cause them to more carefully scrutinize another application with similar
results.
Legal concerns include the potential for being sued if microarray data that
couldn't be interpreted at the time of submission later turn out to indicate
toxicity in some people or under some conditions. The fear of lawsuits is such
that some companies haven't gone to the next stage in using microarrays for
evaluating the effects of drugs under development, for either good or bad effects,
says Roger Ulrich, president of Rosetta Inpharmatics, a subsidiary of Merck
and Company.
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Chemical conundrum. The EPA is moving cautiously toward considering
toxicogenomics data in chemical regulation.
image credit: Corbis
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Manufacturers of industrial chemicals are also concerned about EPA penalties.
If a company discovers a previously unknown adverse effect for a given chemical,
the company is required under TSCA to submit a report to the EPA within a few
days, says Bus. The same is true if toxicity is detected at concentrations
lower than previously found. "Say you're dosing animals with a chemical where,
historically, an effect has not been seen below a dose of ten milligrams per
kilogram," Bus explains. "You do another study and suddenly, you find a unique
effect at one milligram per kilogram. Under TSCA, you're required to report
that." If such a report were delayed because the significance of the microarray
data wasn't understood at the time of testing, manufacturers could conceivably
face retroactive fines and penalties. If penalties are levied per day and a
significant amount of time has passed, fines can be substantial, says Bus.
Under TSCA, the EPA has the authority to levy fines of up to $27,500 per day
for nondisclosure of required information.
Fine-tuning the Process
The FDA is working to alleviate some of industry's concerns. To facilitate
its ability to handle microarray data and keep approvals moving, the agency
has collaborated with private firms on training exercises. Through a material
transfer agreement, Iconix has given the CDER access to its proprietary relational
toxicogenomics database, DrugMatrix, for evaluative and educational purposes,
says Karol Thompson, molecular toxicology team leader in the CDER Division
of Applied Pharmacology Research. The DrugMatrix database contains expression
information related to more than 600 substances, including many approved medications.
Iconix also led two workshops on microarray technology in February 2003 and
January 2004 for members of the Nonclinical Pharmacogenomics Subcommittee of
the CDER Pharmacology/Toxicology Coordinating Committee. The pharmacogenomics
firm Gene Logic also has provided the FDA with expression data from its proprietary
GeneExpress system database as part of a collaborative project with CDER research
scientists and statisticians to identify endogenous genes that can serve as
indicators of microarray sample quality.
In addition, the FDA worked with the company Expression Analysis on a mock
submission using toxicology data developed by Schering-Plough Corporation for
a candidate drug that did not go on to clinical trials. The submission included
microarray data, histology data, clinical chemistry data, and phenotype data.
The exercise served as a practice run to help the FDA understand the format
and content of future drug submissions containing microarray data.
"I think the FDA, Expression Analysis, and Schering-Plough gained a tremendous
amount from this collaboration," says Steve McPhail, CEO of Expression Analysis,
which provides commercial microarray testing, analysis, and data management
services. "We gained a great perspective in working with the FDA and in beginning
to understand their thinking on how this type of data should be formatted for
future regulatory submissions. And I think the FDA gained value from the submission
from our experience with lots of clients and users of data and the way that
they need to become prepared for submission."
Although regulators and industry are working hard to hammer out the issues
around the submission of gene expression data, such submissions are still somewhat
premature, says William Mattes, a researcher on the HESI effort and senior
scientific director of toxicogenomics at Gene Logic. For example, researchers
and regulators have not yet even decided how to report data. The ultimate goal
is to "submit data in some tabular format that is computer-friendly and will
allow regulators to crunch the data, analyze it with software," he says. "We
have not seen the FDA truly, openly discuss what data standards would be. .
. . The issue is hugely in flux."
Mattes serves on a committee on pharmacogenomics standards sponsored by the
Interoperable Informatics Infrastructure Consortium, Health Level Seven, and
the Clinical Data Interchange Standards Consortium, nonprofit organizations
developing data standards for health care and clinical trials. According to
Mattes, the joint committee is discussing high-level questions regarding the
kind of data that should be included in microarray submissions. Other groups
are promoting the use of specific data formats such as the MIAME (Minimum Information
About a Microarray Experiment) standards for content, as well as the accompanying
MAGE (MicroArray and Gene Expression) data format standards developed by the
Microarray Gene Expression Data Society. The European Bioinformatics Institute,
the NCT, and HESI have proposed definitions for MIAME/Tox, which would add
toxicogenomics annotations to the basic MIAME content framework.
Agreement on data formats will do industry and regulators little good if
experimental protocols are weak or inconsistent. The HESI studies found significant
variation among results of microarray experiments that were caused by differences
in procedures among participating laboratories, including different operating
procedures for isolating and labeling mRNA samples, nonstandard settings on
hardware and software, and differences in gene coverage and annotation across
different technology platforms. Jarnagin and others say the standardization
problems found in the HESI experiments, some of which were conducted 3-5
years ago, are not as serious now. "There's been substantial advancement in
the field in the last few years," says Jarnagin.
The quality and consistency of microarray chips has improved since the HESI
experiments were conducted, agrees Brenda Weis, who along with William Suk
administers the Toxicogenomics Research Consortium (TRC), a component of the
NCT. "The commercial products are particularly good," she says. "The manufacturing
is at a very high level."
Testing different microarray types was an important part of initial standardization
experiments by the TRC, which involves researchers at five academic centers
across the country, as well as the NIEHS Microarray Center. The consortium's
work builds on the HESI studies by systematically addressing different steps
of the microarray experiment to see where variability is most likely to be
introduced, says Weis.
In the consortium's first set of experiments, reported in the March 2004
toxicogenomics issue of EHP, the centers used a total of 12 different
microarray platforms. In the multifaceted experiments, all six consortium centers
used two common platforms: an oligo microarray manufactured at one of the centers
and the commercial Agilent mouse microarray platform, developed by TRC investigators
working collaboratively with Agilent and the NCT microarray resource contractor,
Paradigm Genetics. There were also 10 other "resident" cDNA- or oligo-based
platforms that were manufactured at and used by the individual centers.
Other variables addressed in the experiments have included the use of spike-in
RNA and RNA reference samples, known sequences of RNA used as controls in microarray
experiments (spike-in RNA is added to samples at a known concentration whereas
reference RNA is kept separate from the samples but run through the same microarray
experiment). The goal was "to see if they provided utility in helping us understand
how the different platforms performed," says Paules.
There are still other aspects of microarray analysis that can introduce variability
into results, according to Weis. During the TRC studies, as during the HESI
studies, researchers found that the way each individual center handled the
RNA--including the labeling of the samples, the hybridization and wash conditions,
and variables in the scanning and analysis--all had an impact on the eventual
outcomes, says Paules. Results and recommendations for improving standardization
have been submitted for publication.
Now that studies have addressed the technology, the consortium has begun
another series of experiments focusing on the replication of genomic signatures.
Each center will receive common reference RNA samples, Agilent microarray chips,
and compounds (acetaminophen and its nontoxic isomer) to test using experimental
animals. All of the centers will use standardized protocols for the microarray
analyses. The hope, says Weis, is "to standardize the technical aspects of
the experiment in order to address the issue of reproducibility of the biological
response across multiple research groups. Whether or not we can do this successfully
is important information for the regulatory community."
Other groups that are studying method standardization include the External
RNA Controls Consortium, a volunteer group sponsored by the National Institute
of Standards and Technology. The group is working to develop methods to evaluate
the performance of gene expression assays based on the measurement of external
RNA controls, such as spike-in controls.
Standardization of animal models is another concern in microarray experiments.
Researchers with the National Toxicology Program (NTP), an interagency organization
based at the NIEHS, are studying changes in microarray results caused by homeostatic
responses in Fisher 344 rats, one of the primary animal models used by the
NTP. Results thus far, currently in press at Toxicologic Pathology,
show differences in microarray signatures in samples taken from the left lobe
of the liver compared to those from the median liver lobe of the same animal.
"You may get the same overall story from the two samples, but not the same
number of genes or the same intensity of expression," says Gary Boorman, a
research scientist with the NTP and the NIEHS Environmental Toxicology Program,
and a coauthor of the forthcoming paper. These results indicate that when labs
coordinate their efforts, they should not only look at the technical issues,
such as the microarray platforms each group is using, but also make sure that
their methods for sampling animal models are uniform, says Boorman.
The NTP group is also studying variables including the time of day that tissue
is collected, and the life stage and sex of the animal. The goal is to describe
how normal variability in an animal strain can affect the interpretation of
studies using microarray technology, says Nigel Walker, chair of the NTP's
toxicogenomics faculty and a staff scientist with the NIEHS Environmental Toxicology
Program. "We're trying to define 'normal,'" says Walker, "so we know when the
change in a gene is beyond the range of normal physiological variability."
The Burden of Interpretation
Once results of microarray experiments are reproduced, scientists and regulators
are still faced with the difficulty of interpreting genomic signatures. "There
seems to be a lack of consensus on how data should be analyzed," says Timothy
Zacharewski, an assistant professor of biochemistry and molecular biology at
Michigan State University and a member of the NRC committee.
For example, although the FDA draft guidance requires the submission of all
data on "known valid biomarkers," the agency currently does not recognize any
genomic signatures as valid biomarkers, according to Leighton. "A lot of stuff
has been published, but not all of it is of the same quality, even though it's
in the peer-reviewed literature, either because of a small population study
or inadequate controls," he says.
The FDA draft guidance does not specify how genomic signatures are to be
validated as biomarkers. "It's an important issue, and we're discussing that," says
Leighton. "In the near future, we may need to come out with guidance on how
to validate a genomic signature." However, he says he doesn't anticipate such
guidance being issued soon; the agency doesn't want to act in haste lest a
less-than-optimal procedure be institutionalized prematurely.
There are logistical questions to consider. "How do you validate a safety
biomarker, say for liver injury? You can't run a clinical trial where you cause
liver injury," says Ulrich. Instead, scientists must compare genomic signatures
to traditional toxicity tests using animals. But some traditional biomarkers
can be subjective and often equivocal, says Ulrich. He cites the examples of
alanine aminotransferase and aspartate aminotransferase, biomarkers of liver
injury that also are occasionally associated with muscle injury. "Weight lifters
and long-distance runners express [these enzymes]," he says. "They're subjective
biomarkers because they're not liver-specific." (Leighton notes, however, that
the biomarkers industry and academia rely upon the most are less subjective. "Every
lab uses the same core set," he says, "and they've been in use for many years.")
Private companies have little motivation to validate safety biomarkers, in
part because they don't know how they'll be used, says one pharmaceutical representative
who asked to remain anonymous. "It's expensive to validate a genomic signature.
And if we make the investment and develop a better biomarker for toxicity,
all it will do is make it tougher to get approvals." As a result, the bulk
of validation efforts probably will be conducted and disseminated by nonprofit
groups, academia, and government labs.
One leader in this area is the NCT. In addition to studies of experimental
protocols and replicability, the NCT is also studying signatures generated
by specific exposures. The NCT's Microarray Center is focusing on liver toxicants
such as acetaminophen [see "Phenotypic
Anchoring: Linking Cause and Effect," EHP 111:A338-A339
(2003)]. Other government facilities are contributing as well. EPA research
into gene expression includes studies of sentinel species such as amphibians,
fish, and aquatic microbes. The Department of Energy is using microarray experiments
and other techniques to study microbial communities used in the remediation
of toxic waste. In the nonprofit realm, the public ArrayExpress database of
expression data, managed by the European Bioinformatics Institute, contains
all the results from the HESI experiments as well as expression data from other
studies.
There is also at least one commercial company that is contributing to public
domain information on safety biomarkers. In March 2004, Iconix announced plans
to publish five expression signatures of drug-induced toxicity in the liver,
kidney, and heart. Information on one of the signatures, for injury to renal
tubules, was presented that month at the annual meeting of the Society of Toxicology.
As industry and regulators wrestle with the intricacies of microarray data
formats and submission, even more complex challenges loom: the data produced
by proteomics and metabolomics research. "We're well aware that metabolomic
and proteomic data might be more important in the long term than the genomic
data," says Leighton. Among other reasons, samples are more readily available;
it's easier to collect blood and urine than to take a liver biopsy. "Then again," says
Zacharewski, "with proteomics and metabolomics you still have the problem of
large, complex data sets of which only a fraction can be interpreted as being
linked to any biological effect."
Issues of standardization and validation will be similar for all of the "omics" technologies.
So will tensions between concerns of industry and statutory obligations of
regulators. That means many more meetings between industry and agencies. "We're
absolutely committed to not setting standards in isolation," says Benson. "It
is essential for the agencies to work together and with industry and academia
when developing this regulatory framework."
Regulatory Resources
Kris Freeman
[Table of Contents]
Last Updated: August 10, 2004
