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)