High Throughput Testing-The NRC Vision, The Challenge of Elucidating Real Changes in Biological Systems, and the Reality of Low Throughput Environmental Health Decision-Making

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High Throughput Testing-The NRC Vision, The
Challenge of Elucidating Real Changes in
Biological Systems, and the Reality of Low
Throughput Environmental Health Decision-Making

• Dale Hattis
• George Perkins Marsh Institute
• Clark University

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Outline

• The Older NRC Vision Based on High-Throughput
  Testing and Safety-Type Risk Analysis
• One Goal of This Talk is to Illuminate
  Alternatives
• An Alternative Vision for Toxicology Based on
• Quantitative Modeling of Homeostatic Biological
  Systems, and Problems in Their Early Life Setup
  and Late Life Breakdown
• Interactions of Toxicant Actions and Normal
  Background Chronic Pathological Processes
• Variability/Uncertainty Analysis Transforming
  Current Risk Analyses Used for Standard Setting

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The Older NRC Vision Based on High Throughput
Testing Results

• Decades-long period for future development.
• Ensemble of high-throughput assays to represent a
  large number (100) of toxicity pathways.
• Well adapted to rapid screening of new chemicals
  and old chemicals with no prior testing.
• Supports decisions on what concentrations of
  agents will sufficiently perturb specific
  pathways to be of concern.
• Relate concentrations causing those perturbations
  to in vivo concentrations using
  physiologically-based pharmacokinetic modeling.
• No quantitative assessment of health risks or
  benefits of exposure reductions for existing
  agents.

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Traditional Toxicological Model Leading To
General Expectations of Thresholds in Dose
Response Relationships for Toxicants

• Biological systems have layers on layers of
  homeostatic processes (think of a thermostat)
• Any perturbation automatically gives rise to
  offsetting processes that, up to a point, keep
  the system functioning without long term damage.
• After any perturbation that does not lead to
  serious effects, the system returns completely to
  the status quo before the perturbation.

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Caveats--There might not be no-adverse-effect
thresholds for

• Tasks that challenge the maximum capacities of
  the organism to perform (e.g., 100 yard dash
  perhaps learning to read)
• Circumstances where some pathological process has
  already used up all the reserve capacity of the
  organism to respond to an additional challenge
  without additional damage (e.g. infarction causes
  heart muscle cell death that may be marginally
  worsened by incremental exposure to carbon
  monoxide)

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Other Caveats

• The ground state of the system is not a stable
  equilibrium, but a series of cyclic changes on
  different time scales (e.g. cell cycle diurnal,
  monthly).
• Sometimes continuous vs pulsatile patterns of
  change carry important signaling information in
  biological systems (e.g. growth hormone signaling
  for the sex-dependent pattern of P450 expression)
  
• Therefore there must be resonance systems that
  respond to cyclic fluctuations of the right
  period.
• (Think of the timing needed to push a child on a
  swing)
• Therefore the effective dose may need to be
  modified by the periodicity to model dose
  response relationships.

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Potential Paradigm Change for Applications to
Therapeutics

• Historical Paradigm--The Magic Bullet
• Find a molecule that will kill the nasty bacteria
• Find a spot in the brain that, if electrically
  stimulated, will control Parkinsons disease
  symptoms
• New Paradigm--Understand and exploit natural
  resonances to enhance or damp system oscillations
• Potential for pulsatile systems for drug release
• Potential for sensor-based systems for drug
  release (e.g., smart pumps that release insulin
  in response to real time measurements of blood
  glucose)
• Potential for timed or sensor-based electrical
  stimulation of target tissues (e.g., heart
  pacemakers)

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Key Idea for Transforming Risk Assessment for
Traditional Toxic Effects

• Quantitatively characterize each uncertainty
  (including those currently represented by
  uncertainty factors) by reducing it to an
  observable variability among putatively analogous
  cases.
• Human interindividual variability--kinetic and
  dynamic
• Variation in sensitivity between humans and test
  species
• Adjustment for short- vs. longer periods of
  dosing and observation
• Adjustment for database deficiencies (e.g.
  missing repro/developmental studies)
• This general approach is not without
  difficultyneed rules for making the analogies
  (defining the reference groups to derive
  uncertainty distributions for particular cases).
  
• However it does provide a way forward for health
  scientists to learn to reason quantitatively from
  available evidence relevant to specific
  uncertainties.

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Examples of Data Bases Assembled/Analyzed
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Additional Data Bases Analyzed And/Or Assembled
Type of Projection Parameters Original Authors
Interspecies Sensitivity--Multi-Dose and Carcinogenesis Human Maximum Tolerated Dose and Putative Animal Equivalents for 61 Anti-Cancer Agents Price et al., 2001 Hattis et al., 2002
Pharmacokinetics in Pregnancy--Parameters Derived from PBPK Model Fits or Direct Observations Fetal Growth, Placental/Fetal Transfer, Maternal Tissue Growth, Partition Coefficients Hattis, 2004 Report to EPA
Adult/Early Life Stage Carcinogenic Animal Bioassay Sensitivity for 9 Mutagenic Agents Ionizing Radiation Cancer Transformations Per PPM, per dose/ (body weight) 0.75 or per rem ionizing radiation EPA (2005) cancer guidelines Hattis et al., (2004, 2005)
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The Straw Man Quantitative Probabilistic
Framework for Traditional Individual Threshold
Modes of Action

• It is ultimately hopeless to try to fairly and
  accurately represent the compounding effects of
  multiple sources of uncertainty as a series of
  point estimate uncertainty factors.
• Distributional treatments are possible in part by
  creating reference data sets to represent the
  prior experience in evaluating each type of
  uncertainty.

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Interpretation of Dose Response Information for
Quantal Effects in Terms of a Lognormal
Distribution of Individual Threshold Doses
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Analytical Approach for Putative Individual
Threshold-Type Effects

• Select Point of Departure (ED50), then define
  needed distributional adjustments
• LOAEL to ED50 or NOAEL to ED50
• Acute/chronic
• Animal to human
• Human variability, taking into account the
  organ/body system affected and the severity of
  the response
• Incompleteness of the data base

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Elements of the Straw Man Proposal--Tentatively
it is suggested that the RfD be the lower (more
restrictive) value of

• (A) The daily dose rate that is expected (with
  95 confidence) to produce less than 1/100,000
  excess incidence over background of a minimally
  adverse response in a standard general population
  of mixed ages and genders, or
• (B) The daily dose rate that is expected (with
  95 confidence) to produce less than a 1/1,000
  excess incidence over background of a minimally
  adverse response in a definable sensitive
  subpopulation.

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Results of Application of the Straw Man Analysis
to18 Randomly-Selected RfDs from IRIS
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Recent Results from Application of the Straw
Man Approach to Value of Information Testing of
the IPCS Data-Derived Uncertainty Factor Formulae

• Split of PD/PK variability should be closer to
  52, rather than 3.13.1 as implied by the IPCS
  proposal (if one wishes the product to multiply
  out to the traditional 10-fold uncertainty factor
  assigned for interindividual variability
• Approximately equal protectiveness would be
  achieved by substitution of the following values
  for the interindividual variability factor 10 for
  RfDs with the following characteristics Quan
  tal Endpoint Continuous EndpointOverall
  UF 100 17
  43
• Overall UF 1000 7.4
  19

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More Details of Our Analysis are Available in

• Hattis, D., Baird, S., and Goble, R. A Straw Man
  Proposal for a Quantitative Definition of the
  RfD, Drug and Chemical Toxicology, 25 403-436,
  (2002).
• Hattis, D. and Lynch, M. K. Empirically Observed
  Distributions of Pharmacokinetic and
  Pharmacodynamic Variability in HumansImplications
  for the Derivation of Single Point Component
  Uncertainty Factors Providing Equivalent
  Protection as Existing RfDs. In Toxicokinetics
  in Risk Assessment, J. C. Lipscomb and E. V.
  Ohanian, eds., Informa Healthcare USA, Inc.,
  2007, pp. 69-93.
• Detailed Data Bases and Distributional Analysis
  Spreadsheetshttp//www2.clarku/edu/faculty/dhatt
  is

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Implications for Information Inputs to Risk
Management Decision-Making

• Increasingly cases such as airborne particles,
  ozone, and lead are forcing the recognition that
  even for non-cancer effects, some finite rates of
  adverse effects will remain after implementation
  of reasonably feasible control measures.
• Societal reverence for life and health means
  doing the very best we can with available
  resources to reduce these effects.
• This means that responsible social
  decision-making requires estimates of how many
  people are likely to get how much risk (for
  effects of specific degrees of severity) with
  what degree of confidencein cases where highly
  resource-intensive protective measures are among
  the policy options.
• The traditional multiple-single-point uncertainty
  factor system cannot yield estimates of health
  protection benefits that can be juxtaposed with
  the costs of health protection measures.

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Alternative Vision2--Multiple Directions for
Improvement for Toxicology and Risk Assessment

• New Pharmacodynamic Taxonomies and Approaches to
  Quantification
• Taxonomy based on what the agent is doing to the
  organism
• Taxonomy based on what the organism is trying to
  accomplish and how agents can help screw it up
• Quantitative Probabilistic Framework for
  Traditional Individual Threshold Modes of
  Action

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Taxonomy Based on What Organisms Need to
Accomplish to Develop and Maintain Functioning,
and What Can Go Wrong

• Establishment and Maintenance of Homeostatic
  Systems at Different Scales of Distance, Time,
  Biological Functions, Involving
• Sensors of Key Parameters to Be Controlled
• Criteria (E.g. Set Points) for Evaluating
  Desirability of Current State
• Effector Systems That Act to Restore Desirable
  State With Graded Responses to Departures
  Detected by the Sensors
• Some Examples of Perturbations
• Hormonal Imprinting by Early-Life Exposure to
  Hormone Agonists
• The Tax Theory of General Toxicant Influences
  on Fetal Growth, and Possible Consequences

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Key Challenges for Biology in the 21st Century

• How exactly are the set points set?
• How does the system determine how, and how
  vigorously to respond to various degrees of
  departure from specific set points?
• Could all this possibly be directly coded in the
  genome?
• Or, more interestingly, does the genome somehow
  bring about a learning procedure where, during
  development, the system learns what values of
  set points and modes/degrees of response work
  best using some set of internal scoring system?
• How exactly are the set points, etc., adjusted to
  meet the challenges of different circumstances
  (allostasis states--see Shulkin 2003,
  Rethinking Homeostasis).

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Taxonomy Built from the Fundamental Ways that
Chemicals Act to Perturb Biological Systems

• For preclinical stages or subclinical levels of
  effect, is the basic action reversible or
  irreversible, given a subsequent period of no
  exposure?
• Reversible (enzyme inhibition receptor
  activation or inactivation--Traditional Acute or
  Chronic Toxicity--traditional toxicology/homeostat
  ic system overwhelming framework (individual
  thresholds for response)
• Irreversible (DNA mutation destruction of
  alveolar septa destruction of most neurons)

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Subcategories for Nontraditional (Based on
Irreversible Changes) Modes of Action

• How many irreversible steps are needed to produce
  clinically recognizable disease?
• (few--up to a dozen or so) ?molecular biological
  diseases--mutations, cancer via mutagenic
  mechanisms
• (many--generally thousands) ?chronic cumulative
  diseases (emphysema and other chronic lung
  diseases cause by cumulative loss of lung
  structures or scarring, Parkinsons and other
  chronic neurological diseases produced by
  cumulative losses of neurons)

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Special Features of Chronic Cumulative Disease
Processes

• Clinical consequences depend on the number of
  irreversible steps that have occurred in
  different people (often little detectable change
  until a large number of steps have occurred).
• Effects occur as shifts in population
  distributions of function.
• Thresholds for the causation of individual damage
  steps must be low enough that the disease
  progresses with time in the absence of exposures
  that cause acute symptoms.
• Different kinds of biomarkers needed for
• Accumulated amount of damage/dysfunction (e.g.
  FEV1)
• (most powerful for epidemiology based on
  associations with short term measurements of
  exposure) Todays addition to the cumulative
  store of damage (e.g.
• excretion of breakdown products for lung
  structural proteins
• blood or urine levels of tissue-specific proteins
  usually found only inside specific types of cells
  such as heart-specific creatinine kinase for
  measurement of heart cell loss due to infarctions)

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Toward Risk Assessment Models for Chronic
Cumulative Pathological Processes

• Describe the fundamental mechanism(s) that causes
  the accumulation of the individual damage events
  (especially the quantitative significance of
  various contributory factors). Key
  aid--biomarkers of the daily progress of damage
  (e.g. key enzyme released from a dying neuron of
  the specific type involved in the disease)
• Quantitatively elucidate the ways in which
  specific environmental agents enhance the
  production of or prevent the repair of individual
  damage events
• Describe the relationships between the numbers,
  types, and physical distribution of individual
  damage events and the loss of biological function
  or clinical illness. Key aid--biomarkers for the
  accumulation of past damage, e.g. FEV1.

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Motivation to Move On

• Younger generation of analysts will ultimately
  not tolerate older procedures that fail to
  provide a coherent way to use distributional
  information that is clearly relevant to the
  factual and policy issues.
• Younger generation of analysts will have greater
  mathematical and computational facility,
  particularly as biology becomes quantitative
  systems biology with quantitative feedback
  modeling--increasingly an applied
  engineering-like discipline.
• Legal processes will ultimately demand use of the
  best science as this becomes recognized in the
  technical community.
• Newer information/communication tools will foster
  increasing habits and demands for democratic
  accountability experts worldwide will
  increasingly be required to expose the bases of
  their policy recommendationsleaving less room
  for behind-the-scenes exercise of old boy
  safety factor judgments.

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Contributions of High-Throughput Testing in
Different Decision Contexts

• Preliminary evaluation of large numbers of new,
  and old but untested, environmental agents--good
  promise to be helpful.
• Evaluation of contaminated sites (e.g.
  superfund)--support for decision-making based on
  complex mixtures is highly dubious.
• Assistance to epidemiological research to locate
  contributors for human disease (e.g.
  asthma)--also doubtful.
• Assessment of relative risks of different
  industrial processes--fanciful because of the
  need to guess the relative weights to be assigned
  to numerous dissimilar findings on short term
  tests without established quantitative
  connections to adverse health effects.
• High profile choices of degrees of
  control/exposure reduction to be mandated for
  specific agents (slow throughput
  decision-making)--Likely to muddy the waters by
  raising difficult mode of action questions that
  can only be resolved by expensive and slow in
  vivo testing--e.g. using knockout mice. This
  is in fact the most likely near term
  contribution.