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reveal the same pattern. It is clear that while the Ames test and in vivo chromosome
aberration assessments have high specificity, the in vitro mammalian tests for
mutation and chromosome aberration have poor specificity. These tests produce
misleading positive results for many noncarcinogens (Figure 7.1, derived from data
in Ref. 8). Perhaps the most alarming statistic to emerge from that study was that the
most frequently used combination of the Ames test and the micronucleus test,
produced twin negative results for only 5% of noncarcinogens. At the regulatory
level, this problem has been recognized in proposed revisions to the ICH S2
guidance [9], which include a new option for the registration of new pharmaceuticals
whereby the Ames test is the only required in vitro assay (Table 7.1). The
implications for this are discussed in Section 7.5. Fortunately, recognition of
the poor specificity problem has also stimulated assay developers to improve the
methodologies for existing tests and to develop new high-specificity tests. These are
addressed in later sections.
7.1.8 Defense Against Genotoxic Damage
The hazards associated with exposure to genome-damaging agents are met by highly
evolved and largely conserved cellular mechanisms for the recognition of damage,
and its repair. These involve the repair of double-strand breaks by recombinational
repair or nonhomologous endjoining, as well as base excision and nucleotide excision
repair for damage that does not cause breakage. The detection of DNA damage also
triggers a delay in cell division so that repair can be completed before chromosomes
are segregated. If these processes are overwhelmed, apoptosis (programmed cell
death, or cell suicide) may be triggered. Damage/change to the genes encoding the
proteins of DNA repair active in these processes can also lead to tumorigenesis.
% Sensitivity ( ) Specificity ( )
Ames MNMLAIVC
Ames
IVC
MLA
IVC
Ames
MLA
MLAMNAmes
MN
Figure 7.1 The sensitivity and specificity of the in vitro regulatory tests in the prediction of
rodent carcinogenicity. Upper dark circles, sensitivity; lower light circles, specificity; IVC, in
vitro chromosome aberration; MLA, mouse lymphoma assay; MN, micronucleus test.
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There are also the more generic metabolic responses to xenobiotics. These are
generally described as mechanistically distinct phases, though there may be quite
complex reactions involving both phases. In Phase 1, oxidative reactions catalyzed by
the cytochrome P450 monooxygenase enzymes, may activate target molecules. The
resulting molecules may be more reactive and/or genotoxic than the original
compound. In Phase 2, the Phase 1 oxidation products are conjugated, for example,
to glutathione, glucuronic acid, or to acyl, methyl, or sulfate groups. Xenobiotics that
are themselves oxidative may be conjugated directly by Phase 2 enzymes. These
products may then be targeted for exclusion by the kidneys.
Humans are diverse, and each individual’s genome contains unique variations,
which might occur in the genes encoding the enzymes of DNA replication, repair, or
the genes encoding the metabolic enzymes of xenobiotic defense. These variations
can affect our susceptibility to genot oxin-induced illnesses, and the identification of
such variations is just one of the challenges for personalized medicine. This is of
particular sign ificance when the treatment of a life-threatening disease might involve
the use of genotoxic chemicals.
7.1.9 Mechanisms of Genotoxic Damage
The chemistry of genotoxins is diverse, and discussed in a later section. However, the
underlying mechanisms of direct DNA damage are limited—DNA is a fairly
homogeneous target.
TABLE 7.1 Comparison of Current and Proposed Revised ICH Guidelines
ICH S2B
ICH S2 (R1)
Option 1 Option 2
Ames and repeat Ames one complete assay Ames one complete assay
5 mg per plate Tested to first precipitating
dose
Tested to first precipitating
dose
In vitro mammalian cell assay In vitro mammalian cell assay No in vitro mammalian
assay
Chromosome aberrations, OR
tk mutations in mouse
lymphoma cells
Chromosome aberrations, OR
tk mutations in mouse
lymphoma cells OR in vitro
micronucleus assay
10 mM 1 mM or 0.5 mg/mL top
concentration
In vivo cytogenetic assay In vivo cytogenetic assay
integrated into 28 day
rodent toxicity study,
provided it is adequate to
support clinical trials and
sampling within a day of
last day of dosing
In vivo cytogenetic assay
and a second in vivo
endpoint, integrated
with 28 day rodent assay
and first in vivo endpoint
if possible
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Oxidative damage can modify bases, particularly guanine. Modified bases that are
not excised can lead to replication errors due to failures in base pairing. Oxidative
damage can also cause DNA double-strand breaks (clastogenesis).
Intrinsic, programmed alkylation of DNA is a normal frequent phenomenon.
However, inappropriate alkylation of bases such as methylation can lead to replication
errors and mutation. Repair of methylated bases can also lead to single-strand breaks,
which can become double-strand breaks during replication.
Hydrolysis of bases can lead to depurination, depyrimidination, and deamination,
which in turn can lead to error prone repair and mutation/damage.
The covalent linking of xenobiotic molecules to DNA, adduct formation, is often
associated with their conversion to reactive molecules by metabolism. The cytochrome P450 monooxygenase enzymes are particularly active in this respect. Adducts
that are not removed can also lead to collapse of replication forks and replication
errors.
Proteins provide many indirect targets for genotoxins. Interference or inhibition of
the enzymes of DNA metabolism, including those required for replication, repair, and
precursor supply as well as the topoisomerase enzymes, can lead to mutation or
clastogenesis depending on the target. Interference with proteins of the mitotic
machinery, for example, tubulins that are polymerized and repolymerized during
the functioning of the mitotic spindle apparatus, can lead to loss of chromosome
attachment, missegregation, and aneugenesis.
7.1.10 Genotoxicity Assessment Occurs after Medicinal Chemistry
Optimization
Until recently, genotoxicity has been conducted during preclinical safety assessment
where GLP test results are generated for regulatory submission. This is often preceded
by relatively small scale screening exercises with a subset of compounds (25) from a
discovery program. The compound collection represents a limited number of
chemistries. The screen reduces the number of compounds to a main candidate and
a backup in the same chemistry as well as an example from a different chemistry.
These screens are usually streamlined, pre-GLP versions of the regulatory assays. The
results provide some basic mechanistic classification for safety assessment of a drug
candidate (mutagen, clastogen, or aneugen). At this stage in a development program,
active chemical optimization by medicinal chemists has been completed. In the earlier
screening stage of a program, generally a broader chemical space is considered.
More importantly, it is still possible then to engineer chemical modifications during
hit-to-lead and lead optimization phases.
If there was genetic toxicology hazard information during earlier phases of active
chemistry, then routine strategies could be implemented to separate useful pharmacology from a genotoxic hazard. Instead, the discovery of genotoxicity during
preclinical safety assessment leads to either abandonment of the candidate (or a
whole program) or additional mechanistic studies and in vivo testing to better evaluate
human risk. The costs of these studies are high, but dwarfed by the costs of delay in
bringing a product to market. For these reasons, it appears to be valuable to obtain
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genotoxicity data early in discovery, to ensure that candidate pharmaceuticals carry a
low risk of genotoxicity failure during preclinical safety assessment.
7.2 LIMITATIONS IN THE REGULATORY IN VITRO
GENOTOXICITY TESTS
Aside from the confounding effects of poor specificity, there are other practical and
technical limits to the data that genetic toxicology can supply for the medicinal
chemist. They require hundreds of milligrams of compound, are labor-intensive and
time-consuming. These alone serve as significant barriers to their use in screening.
However, there are also limitations to their biological utility. These and other
challenges are explored below.
7.2.1 Biology Limitations of In Vitro Tests
Bacterial and mammalian cells can both produce viable mode ls for the identification
of direct-acting genotoxins. Bacteria are prokaryotes and provide a less complete
model for the detection of indirect agents and aneugens that are expected to affect
human or eukaryotic cells. Prokaryotic cells lack the membrane-bound nucleus of the
eukaryotes, have less complex packaging of DNA and have a single circular
chromosome. Together these properties have led to the evolution of structurally
different enzymes that intera ct with DNA, compared with the multiple linear
chromosomes in eukaryotes and their more complex chromatin. Agents that affect
replication, recombination, and repair of DNA in bacteria might not have similar
effects in mammals. Bacteria also lack mitosis, the conservative segregation of
replicated chromosomes during cell division, and meiosis. They are therefore
deficient in the detection of important events in the development of cancer, including
karyotype instability and aneugenesis. Finally, the mechanisms for chemical defense
have followed evolutionarily different pressures between the free-living bacteria and
the often more protected metazoan eukaryotic cells. This is partially reflected by
differences in xenobiotic metabolism that can impact on the relevance of genotoxicity
results from different species.
Even within the eukaryotes, different evolutionary paths indicate that individual
targets for particular genotoxic compounds are not present in all cell types, or even in
all mammals. The corollary to this is that no single test is effective in the identification
of all genotoxins. For pharmaceutical safety assessment, Homo sapiens is the species
of interest, but genetic toxicologists are ultimately constrained by the use of different
animal models. These models do not always reproduce human patterns of tumor
development and chemical sensitivity. As a result, broader differences in drug
absorption, receptor distribution, distribution, excretion, and metabolism are obtained
(Chapter 4). The assessment of metabolites often requires complex preclinic al
studies, and cell-based assays are not particularly effective in reproducing the
in vivo metabolism of the human liver or other tissues. The rodent S9 liver extracts
used as an exogenous source of metabolism are incomplete metabolic surrogates and
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their properties are inappropriate for handling on an automated HTS no need of the
expanded form platform.
7.2.2 Hazard and Safety Assessment have Different Requirements
The need to use more than one test is not a problem when assessing low numbers of
compounds. However, in larger scale screening exercises when there are still perhaps
thousands of hits, a reliable positive hazard result from just one assay (i.e., a positive
result that is predictive of in vivo genotoxicity/carcinogenicity) can be extremely
valuable. It can trigger a round of chemistry development, or be used as an attrition
tool. Breadth of chemistry and clinical indication dictate the choice of leads in a
discovery campaign. Any drug discovery program needs the genotoxicity hazard
screening assays with high specificity. Wrongly classifying noncarcinogens as
carcinogens could lead to the loss of potentially valuable drugs.
In later candidate selection (safety), when there may be fewer than 20
compounds left in contention, reliable safety results (i.e., a negative result that
is accurately predictive of negative in vivo genotoxicity/carcinogenicity) are
required to carry the drug forward into development and FTIH (first time in
human) studies. Thus, safety assessment groups require high sensitivity, wrongly
classifying carcinogens as noncarcinogens will allow compounds to continue their
ever more expensive progress to the clinic via animal studies before the liability is
identified.
The medicinal chemist is concerned with activity, attrition, and hazard, while the
safety expert is concerned with saving compounds, and hence the relevance of the
underlying hazard mechanisms to humans. The safety expert’s concerns are obviously
much more costly to address. In reality, there is a trade-off between specificity and
sensitivity. High specificity often comes at the expense of sensitivity. This is less
concerning in a strategy without the early screen, since in later GLP studies missed
genotoxins will be detected, albeit in fewer compounds. This compromise needs to be
understood and recognized when developing testing strategies at different stages in
discovery and development.
7.2.3 The Data from Genetic Toxicologists
Genetic toxicity testing generates quantitative data. Genotoxic compounds may
generate no-effect levels (NOELS) and lowest effective concentrations (LECs).
These might be in the submicromolar or millimolar range for potent or weak
genotoxins, respectively. The measured effects also vary in magnitude that reflect
increases in mutation rate, the incidence of chromosome abnormalities, or increased
expression of genes associated with the response to DNA damage. In making a safety
assessment, both exposure and dose are considered, that is, a weak genotoxin might be
an acceptable drug if the therapeutic dose is low enough. In addition, genotoxicity in
pharmaceuticals can be tolerated in the case of life-threatening diseases. In the
particular cases of antivirals and antineoplastic agents, genotoxicity can also be a
consequence of the mechanism of action.
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7.3 PRACTICAL ISSUES FOR GENOTOXICITY PROFILING
7.3.1 Vehicle
The practical aim of screening for genotoxic potential much earlier than safety
assessment should be to identify potent genotoxins. Those active at low concentrations would be the most challenging to carry forward in safety assessment. The in vitro
tests described in this chapter are performed in living cells. Hence, samples stored in
100% DMSO need diluting to around 1% DM SO to be tolerated by living cells.
Generally, a pharmaceutical library will be prepared between 10 and 50 mM in >98%
DMSO. Dilution sets the upper limit for testing between 100 and 500 mM, which is
considerably below the current 10 mM requirements for the regulatory tests. Thus, a
screen performed on such library cannot be expected to give an accurate prediction of
regulatory testing. Instead compounds will be identified that are potent genotoxins at
low concentrations, which is ultimately a goal for medicinal chemists.
7.3.2 Dilution Range
In contrast to the true high-throughput screening paradigm of single point data,
genotoxicity data is best derived from a range of compound concentrations. This is
because genotoxins usually kill cells at concentrations where genome damage
becomes overwhelming. In eukaryotic cells, this is often observed as a reduced
growth rate caused by cell cycle delay or death through apoptosis. Given the wide
range of potencies amongst known genotoxins, testing at a single concentration is
unlikely to coincide with the concentration at which genotoxicity is detected. It might
only allow the conclusion that a compound allows growth, or causes growth inhibition
or death. A range of concentrations provides the opportunity to generate useful
actionable data. In a lead optimization program, a range of exposures allows the
selection of modifications that progressively reduce genotoxicity or separates genotoxic effects from pharmacological efficacy.
The NIH set up the National Chemical Genomics Center (NCGC) in 2007 to
reproduce the state of the art in the pharmaceutical industry screening facil ities.
NCGC runs a variety of tests at 15 dilutions from a highest concentration of about
92 mM. Such screen conducted with the purpose of detecting genotoxins would detect
the genotoxicity of the most potent compounds, but not the least potent.
7.3.3 Purity
Purity, or potential impurity, can be a confounding factor for any in vitro screen and
poses a theoretical risk as a result of in silico predictions as well as synthetic
chemistry. There are particular issues with purity that are relevant to genotoxicity
screening. While most useful drugs are nonreactive by design, the synthesis of novel
small molecules is almost inevitably achieved through the use of reactive chemicals,
which might persist as contaminants in the library samples. Many compounds such as
alkylators, aromatic nitro, and aromatic amines are commonly active in mutagenicity
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assays. A potent genotoxic impurity might falsely identify the test compound as
hazardous.
A related challenge is the presence of intermediates in synthesis. Both readily
anticipated impurities, such as structural isomers, as well as unanticipated intermediates might pose a genotoxic hazard. The increased scale of production that is
required once a compound reaches development often follows a different synthetic
route and/or allows for greater investment in purity. In such cases, a positive result for
a discovery compound that arose because of an intermediate is not at all relevant.
This topic has been the subject of industry-wide discussion, leading to proposals
for the determination, testing, and control of specific impurities in pharmaceuticals [10] as well as some investigation of how structure-based assessment can support
safety assessment of impurities [11] (see below). The actual risk posed by an impurity
or intermediate will depend on whether or not it is actually present and in what
quantities. If the in silico prediction is to be followed up, the purification or de novo
synthesis of the intermediate for in vitro or in vivo testing requires the development of
new analytical methods to detect and measure the compound. A similar scenario
arises from the consideration of genotoxic metabolites that might either be predicted,
or detected in in vitro studies under metabolic activation conditions (e.g., with S9
fractions), or is inferred or detected in animals.
Detailed reiteration of other issues related to impurities is beyond the scope of the
present discussion. It is relevant, however, to consider the concept of a threshold of
toxicological concern (TTC) as it relates to genotoxicity. A TTC defines a level of
acceptable exposure to known carcinogens. It is expressed as a level of daily dose that
would increase the number of cancers in the population by only a negligible level. The
European Medicines Agency has proposed that “a TTC value of 1.5 mg/day intake of a
genotoxic impurity is considered to be associated with an acceptable risk (excess
cancer risk of <1 in 100,000 over a lifetime) for most pharmaceuticals. From this
threshold value, a permitted level in the active substance can be calculated based on
the expected daily dose. Higher limits may be justified under certain conditions such
as “short-term exposure periods” [12]. Delaney [13] summarized a variety of reasons
to view this as an overcautious limit, including inappropriate linear extrapolation from
TD
50
values, and reliance on carcinogenicity data from rodent studies that substantially overestimates human risk. A more direct focus on the absurdity of this virtually
zero-risk approach is that the actual lifetime risk of all cancers in human is 30–40,000
per 100,000, and that humans consume gram quantities of known rodent carcinogens
every day [5].
7.4 COMPUTATIONAL APPROACHES TO GENOTOXICITY
ASSESSMENT: THE IN SILICO METHODS
7.4.1 General Considerations
Accurate in silico (computational) methods provide cost-effective and fast virtual
screening for drug candidates that allow profiling molecules for genotoxicity before a
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compound has been synthesized. Thus, chemists can theo retically avoid the time and
expense of synthesis of compounds with readily predictable liabilities, and instead
focus their efforts on compounds with reduced risks. The current predictive power of
computational methods derives from traditional regulatory genotoxicity datasets and
generally tends to overpredict in vivo hazard. In silico methods should be used in
concert with accurate in vitro genotoxicity assays. The results of such tests can then
feed back into the development of ever more sophisticated tools.
The prediction of genotoxicity based on chemical structure began in earnest after
Ashby and Tennant [14, 15] established that there are correlations between chemical
structure, Salmonella mutagenicity and carcinogenicity. Their work produced the
theoretical “supermutagen” (Figure 7.2), which remains a valuable reference of how
not to design a new drug! The distinction between genotoxic and nongenotoxic
carcinogens does not follow the same rules. In the subsequent early development of in
silico methods there was an inevitable reliance on the Ames and rodent carcinogenicity data because these provided the most readily available datasets. This is a rapidly
evolving field, but before considering the state-of-the-art, the challenges that are now
being addressed such as the biological relevance of the carcinogenicity and genotoxicity test data used to construct models and the breadth of chemistry in the
molecular structures should be explored.
O
H
2
N
N
NO
2
OS
H
2
C
O
OCH
3
N
N
N
CH
3
CH
3
O
CH CH
ClH
2
CCH
CH
2
H
C
HN
CH CH
2
NCl
O
O
N(CH
2CH2
Cl)
2
Cl
NCH
2
CH2OH
CH
CHO
NH N
CH
3
CH
3
CH
2
CH
2
O
ONH
2
N
N
H
3
C
O
Figure 7.2 Theoretical “Supermutagen.”
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As mentioned above, historical carcinogenicity data was often derived from
animals exposed to chronic sublethal doses of a test chemical. This can lead to cell
damage and cell death, which in turn requires cell division to replace lost cells.
DNA replication is intrinsically very accurate, but mutations occur in every cell at
every division and can increase the risk of cancer independently of the cause of
increased cell division. An expectation that a molecule will never reach such
concentrations in man is likely to overestimate this hazard. Similar problems arise
from the in vitro data. The Ames test has high specificity, so Ames positive
compounds are quite likely to be genotoxic carcinogens and their structures are of
value in modeling. However, its relatively low sensitivity indicates that there are
many Ames negative compounds, which are both in vitro and in vivo genotoxins
and carcinogens. Without data from these Ames negative genotoxic compounds,
the predictive model will be deficient. This gap is increasingly filled by the
inclusion of data from the current regulatory in vitro mammalian genotoxicity
tests, though their poor specificity contributes to the risk of a model generating
false predictions of hazard.
From a chemical perspective, reactive molecules are not generally good drug
candidates. The original Ashby and Tennant rules were derived from industrial
chemicals including pesticides, herbicides, and others chemicals of environmental
concern as opposed to drug-like molecules. These are often highly electrophilic and
reactive. While drug-like molecules are usually nonreactive, reactive molecules are
important in the synthesis of drugs as reactants or intermediates and may remain as
impurities. They may also be generated by the metabolism of drugs. Putative reactive
derivatives might not exist and be detectable, and can certainly be challenging and
costly to synthesize. However, a study of the potential value of in silico methods in risk
assessment of impurities found that in silico methods are actually quite effective in
this application [11].
Snyder and coauthors [16] analyzed the extent to which the above limitations
might influence the accuracy of three different in silico methods (DEREK for
Windows, TOPKAT, and MCASE) by using them to predict the genotoxicity of
394 marketed pharmaceuticals. Their general conclusions were that the in silico
methods had poor sensitivity in the prediction of genotoxicity of pharmaceuticals.
Since this report there have been concerted efforts to improve the models by
populating the chemical structure databases with more drug-like molecules, and
collecting data from chemical classes that have alerting structures, but are not all
genotoxic or carcinogenic.
Two branches of genotoxicity assessment based on molecular structure have
emerged. The first branch is based on mathematical algorithms, which generate a
statistical assessment of risk by the definition of quantitative structure–activity
relationships (QSAR), based on correlations between molecular structure and
genotoxicity endpoints. Examples of these are MC4PC (MultiCASE), MDLQSAR (MDL), BioEpisteme (Prous Science), and Predictive Data Miner (LeadScope) [17, 18]. In general, these methods have high specificity and low sensitivity.
The second branch adds research information gathered by human experts to the
structure. These include molecular context of the alert, as well as mechanisms of
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genotoxicity, activities, and reactivities to build knowledge-based expert system
rules for correlation with genotoxicity endpoints (DEREK for Windows, LHA SA).
These methods have a lower specificity but higher sensitivity. Similar to the in vitro
tests, presumably the best strategy is to consider a combination of in silico
approaches [18].
Yang and coauthors [18] have undertaken a comprehensive effort to integrate
genotoxicity data from multiple databases, incorporating private databases from
four private industrial sources, including pharmaceuticals. The latter considerably
increases coverage of pharmaceutical space despite only using general structure
feature statistics rather than actual chemical structures. Principal component
analysis (PCA) was applied to reveal multiple domain correlations between
chemical structures/features with semimechanistic data from the following genotoxicity tests: Bacterial (Ames) and mammalian (MLA) mutation, in vitro chromosome aberration, and in vivo (rodent) micronucleus formation. The broader
chemical space and multiple genotoxicity endpoints should result in generation of
an in silico genotoxicity hazard profile containing a recommendation on follow-up
testing.
7.4.2 The Chemistry of Genotoxins
To ascertain the cancer risk of specific structural moieties in a molecular substrate, it is
essential to understand the relationship (if any) between those structural alerts and
mutagenicity and/or carcinogenicity. It is generally recognized that there are approximately 30 alerting groups based on structural motifs [15, 19–21]. The different
classes expand or contract, depending on the perspectives of different research
groups. These moieties are cataloged in Table 7.2.
Electrophilic compounds (including those derived via metabolic activation) have
long been associated with carcinogenic potential [22, 23]. Cheeseman and colleagues [20] found that if they removed those compounds containing highly alerting
structures from the 709 compounds (in their database) exhibiting carcinogenicity, that
the median adjusted log value (MALV) of remaining compounds within the database
fell to 4.85 (the same value as for substances testing negative in the Ames assay);
whereas, the MALV for those containing a structural motif of concern increased to
6.18. The authors indicated that there was a 20-fold decrease in potency between those
compounds with structural alerting motifs compared with those that did not contain
these moieties. The authors contended that this allowed regulatory bodies to build
structural alerts database that could trigger a level of concern even in the absence of
alerting biological data.
Cheeseman and colleagues [20] examined highly alerting structural motifs and
demonstrated that 8 out of 19 subgroups in their database alerted for carcinogenicity.
These subgroups were further scrutinized and stricter controls were proposed. These
included N-nitroso compounds, endocrine disrupters, strained heterocyclics, for
example, epoxides and aziridines, heavy metals, a-nitrofuryl compounds, hydrazines
(and related triazenes, azides, and azoxy compounds), polycyclic amines, and
organophosphorous compounds.
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