Building improved in-vitro exposure assessment capability ... · • Screening / prioritization •...
Transcript of Building improved in-vitro exposure assessment capability ... · • Screening / prioritization •...
SEACSAFETY & ENVIRONMENTAL ASSURANCE CENTRE
Building improved in-vitro exposure assessment capability: Towards the development and implementation of enhanced QIVIVE tools
Todd Gouin1, Michelle Embry2, Jon Arnot3
1Safety and Environmental Assurance Centre, Unilever, Colworth Science Park, Sharnbrook, Bedfordshire, U.K., MK44 1LQ2ILSI Health and Environmental Sciences Institute (HESI), Washington DC, USA
3ARC Arnot Research & Consulting, Toronto, ON, Canada
• Assessing hazard based on AOPs are meant to be non-chemical specific• Assessing exposure based on AEPs necessitates the need to consider the
properties of the chemical• Critical for linking exposure to hazard and QIVIVE modelling tools
Background
• Risk assessment in the 21st Century calls for improved mechanisticunderstanding of toxicity pathways and integration of this informationinto risk assessment
• Testing all endpoints and chemicals in an efficient and resourceappropriate manner poses substantive challenges that cannot be metwith traditional testing approaches
• High-throughput screening and testing methods may provide asolution to this challengeo Focus on a multiple target matrix approacho Integration of in silico models, biochemical assays, cell-based in
vitro assays, and non-mammalian animal models• Currently, this high-throughput information can provide guidance to
assess toxicological hazards• Combining high throughput in vitro data with mechanistic insight
regarding exposure dose in vivo is a substantive challenge• Translation and use of this high-throughput data in a risk context
requires quantitative in vitro to in vivo extrapolation• Chemical exposure to the organism via respiration, diet, intravenous,
or dermal routes is used as a surrogate for the concentration of thechemical at the site of toxicological action
• Key challenges exist to appropriately translate data between in vitroand in vivo systems and there are ongoing efforts to identify andaddress these issues
TargetExposure
ProteinOrganelle
CellTissueOrgan
InternalExposure
Amount AbsorbedIntake Amount
Amount in Blood
ExternalExposure
Contact AmountDaily Intake
Inhaled Amount
ExposureMedium
Air, Water, Soil
Food, Drink, Cosmetics
Source
Industrial ReleaseWaste Water
Waste Site
ManufacturingIndustrial Production
Source Evaluation &
Mitigation
Aggregate Exposure Pathway (AEP)
Environmental ChemistryFate and Transport
Time, Space, Activity
Adsorption, Distribution, Metabolism, Elimination (ADME)
Molecular Initiating Event
Receptor activationProtein binding
DNA binding
Cellular
Responses
Gene activationProtein productionAltered signalingProtein depletion
Organ Responses
Altered physiologyDisrupted
homeostasisAltered tissue
development or function
Individual Responses
LethalityImpaired
developmentImpaired
reproductionCancer
Population
Responses
Structure Recruitment
Extinction
Adverse Outcome Pathway (AOP)In vitro data – use contexts & drivers
• Screening / prioritization• Classification / labeling• Product development• Grouping• Analogue read-across• Risk-risk comparison / chemical potency ranking• Hazard identification• Development of model input parameters• Risk assessment (e.g., prediction of in vivo effects)• Evaluation of metabolism
In vitro methods
Animal alternatives
Increased need for risk assessments
Innovation
Shift towards mechanistic toxicology
(AOPs, MOA)
Linking exposure to AOP – Quercetin case example
Aggregate Exposure Pathway (AEP): Linking exposure and hazard
Figure 1: Schematic highlighting key factors that influence estimating exposure within in vitro
and in vivo systems.
• Free concentration (Cfree) in vitro should be consistent with estimates of Cfree in vivo
• Important to understand differences / similarities in partitioning and degradation processes
Improving exposure estimation: considerations & approaches for in vitro test systems
Internal free concentration
Total internal concentration
Partitioning / binding
Biotransformation / excretion
Target site 1
Target site 2
Effect chemical activity threshold
Effect chemical activity threshold
Freely dissolved concentration
bioavailabilitypartitioning / binding
Total external concentration
biouptake
Cfree (in vitro) = Cfree (in vivo)
Exposure assessment: Key elements to consider
• Quercetin is a naturally occurring flavanoid present in green tea and avariety of berries, fruits, and vegetables.
• Purported to have antioxidant, anti-inflammatory,chemotherapeutic and chemoprotective effects
• There is general interest in the use of flavonoids in theprevention and treatment of cancer
• There is disparity between in vitro and in vivo observations for quercetin• In vivo (animal studies): retardation of tumour growth and
inhibition of the effects of known carcinogens• In vitro (mouse & human cell lines): increase of point mutations
in mouse lymphoma L5178Y cells and micronuclei in MCF-7 cells.
• Illustrates the importance of better understanding differences in exposurewhen attempting to apply QIVIVE tools.
• Differences in partitioning and degradation mechanisms• Dose-response relationship of DNA damage and subsequent
initiation of cellular response that may prevent permanentmutation in vivo.
Quercetin
• Low tier approaches which simply assume exposure concentration in vitro isequivalent to in vivo exposure may fail to appreciate differences in partitioningand degradation mechanisms, leading to high level of uncertainty with respectto informing the risk assessment
• Filling key data gaps can help to reduce uncertainty and apply appropriatemodels, although this can come at a cost of increasing time and resources.
• Level of uncertainty that is acceptable will be driven by the context and driversfor performing the in vitro study.
• Quercetin case example highlights the importance of addressing each of theelements in above table.
References• Adeleye, Y. et al. (2015). Implementing Toxicity Testing in the 21st Century (TT21C): Making safety decisions using toxicity
pathways, and progress in a prototype risk assessment. Toxicology, 332, 102-111.• Armitage, J. M. et al. (2014). Application of mass balance models and the chemical activity concept to facilitate the use of
in vitro toxicity data for risk assessment. Environ Sci Technol, 48(16), 9770-9779.• Gouin, T. et al. (2016). Addressing the challenge of exposure science in the 21st century: A strategy for developing more
robust exposure assessment tools. SETAC Orlando World Congress. Tuesday November 8th, 2016, 3:20 pm, ID 329• Groothuis, F. A. et al. (2015). Dose metric considerations in in vitro assays to improve quantitative in vitro-in vivo dose
extrapolations. Toxicology, 332, 30-40.• Teeguarden, J. G. et al. (2016). Completing the Link between Exposure Science and Toxicology for Improved Environmental
Health Decision Making: The Aggregate Exposure Pathway Framework. Environ Sci Technol, 50(9), 4579-4586.
Legend: Mass distribution (MD), enrichment factors (EF), and depletion factors (DFs) as a function of partitioning in bulk medium with no serum and a serum (fetal bovine serum, FBS) volume fraction of 0.10.
The approximate partitioning properties of nitrobenze (NB), carbon tetrachloride (CCl4), styrene (St), naphthalene (NaP), phenanthrene (PHE), hexachlorocylohexanes (HCH), decane (Dc), hexachlorobenzene (HCB), 1-tetradecene (1T), polychlorinated biphenyls (PCBs), brominated flame retardants (BFRs), and decamethylcyclo-pentasiloxane (D5) are indicated on the EF panels. (Armitage et al. (2014)
Figure 3: Flow chart to aid in choosing an appropriate dose metric for a specific in vitro toxicity
test. Chart from Groothuis et al. (2015)
Follow our themed session on QIVIVE across various societies
Source
Classification of personal care
product category
Skin / Hair / Oral Use Scenario
ExposureMedium
Human health: Dermal / Inhalation /
Oral
Environment: Air / Water / Soil
ExternalExposure
Product inclusion level per capita usage
Inhaled amountEnvironmental
release scenario
InternalExposure
Characterize amounts available:
SystemicallyBody burden residues
TargetExposure
ProteinOrganelle
CellTissueOrgan
Applied DoseChemistry
Environmental FateTemporal & Spatial
PBPK ModelllingIn vitro kinetic models
Bioaccumulation models
Figure 2: Demonstration of the importance of
interactions between chemicals an components of the in vitro matrix as shown using an equilibrium, steady-state mass balance model
• Illustration of the applicability domain, where Cnominal serves as a good approximation of Cfree
(see Figure 3 for more specifics)
• Limitations include:
• Assumption of equilibrium and steady-state
• Lack of inclusion of dynamic processes (e.g., transfer across cell membranes & degradation kinetics)
• Identifies important refinements needed to decrease uncertainty in QIVIVE
1. Dose type should be chosen based on the characteristics of the chemical and available knowledge
2. Dose metric can be integrated or averaged for time-dependent exposure and irreversible mechanisms, or steady reduction over time. Peak concentration is defined as the maximum concentration reached during the exposure period.
3. Toxicokinetics/toxicodynamicsmay be applied to model partitioning and assess concentration changes over time.
Gouin et al. (2015)
Teeguarden et al. (2016)
Adeleye et al. (2015)