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UNILEVER, SEAC AND SAFETY ASSESSMENT WITHOUT ANIMALSCURRENT APPROACHES AND RESEARCH NEEDS
The funders’ perspective – The remit of the joint awards
Andrew Scott
NC3Rs/Unilever PhD Studentship Launch event2nd April 2019
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CONTENT OVERVIEW
• Unilever
• SEAC
• How we assure safety - Next Generation Risk Assessment
• Research activities and needs
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UNILEVER IS A GLOBAL COMPANY AND WE MAKE MANY OF THE WORLD’S FAVOURITE BRANDS
2018 TURNOVER €51BN
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“Building brands through benefit-led innovations,unlocked by science &
technology”
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Protecting Consumers, Workers & our Environment by ensuring Unilever’s Products & Processes are Safe & Sustainable by Design
SEACSAFETY & ENVIRONMENTAL ASSURANCE CENTRE
Scientific Excellence And Collaboration
➢ Centre of Excellence in Safety & Sustainability Sciences
▪ Deploy expertise on higher risk business projects
▪ Collaborate with leading external research teams to develop new capability
▪ Leverage science & global networks for consumer trust & freedom to operate
➢ Unilever Safety Governance▪ Provide scientific evidence to manage
safety risks & environmental impacts
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SEAC
SEAC’S CAPABILITYChemistry, Environmental Safety, Environmental Sustainability, Exposure Science, Informatics, Life-Cycle Impact Assessment, Microbiology, Modelling, Process & Occupational Safety,Risk Assessment, Toxicology
70%DEGREES OR HIGHER
30%PhDs
>600PUBLICATIONS SINCE 2005
>15LANGUAGES
4HONORARYPROFESSORS
>20NATIONALITIES
FUTURE TALENTworking with Universities to supportdevelopment of future scientists
LEADING EDGE SAFETY & ENVIRONMENTAL SCIENCES CAPABILITY
PARTNERSHIPSour innovation ecosystems involve >50 collaborators & service providers across the world
17 PhDs10 POST-DOCS
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SCIENTIFIC PARTNERSHIP
www.tt21c.org
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8https://www.unilever.com/news/press-releases/2018/unilever-supports-calls-for-a-worldwide-animal-testing-ban-on-cosmetics.html
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OUR APPROACH TO SAFETY SCIENCEASSURING SAFETY WITHOUT THE USE OF ANIMALS
30+ Years Investment
50+ Collaborations
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CAN WE USE AN INGREDIENT SAFELY?
• Can we safely use x% of ingredient y in product z?
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MAXIMISING USE OF EXISTING INFORMATION AND NON-ANIMAL APPROACHES
• All available safety data
• in silico predictions
• Exposure-based waiving approaches
• History of safe use
• Read across
• Use of existing OECD in vitro approaches
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• Using new tools and approaches to build a risk assessment to enable decisions to be made (without animal tests)
• An exposure-led risk assessment solution to biological pathway-indicated hazard concerns
Exposure led Mechanistic Hypothesis driven
NEXT GENERATION RISK ASSESSMENT (NGRA)
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ICCR PRINCIPLES OF RISK ASSESSMENT WITHOUT ANIMAL TESTING
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ICCR NINE PRINCIPLES OF NEXT GENERATION RISK ASSESSMENT (NGRA)
• Main overriding principles: • The overall goal is a human safety risk assessment • The assessment is exposure led • The assessment is hypothesis driven• The assessment is designed to prevent harm
• Principles describe how a NGRA should be conducted: • Following an appropriate appraisal of existing information• Using a tiered and iterative approach• Using robust and relevant methods and strategies•
• Principles for documenting NGRA: • Sources of uncertainty should be characterized and documented• The logic of the approach should be transparently and documented
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Plasma concentration
Uncertainty
Uncertainty
10x -
100x -
10x -
100x -
SYSTEMIC & BIOLOGICAL EFFECTS – WHAT IT MIGHT LOOK LIKE
Low
High
Ex
po
su
re /
Do
se
POD from various in vitro assays(range characters multiple cell lines)
Toxicity markers from Cell-based assays
Marker 3 2.9-3.3µM
Marker 2 2-3µMMarker 1
1.97µM
Tissueconc
1.5µM
0.05µM withclearance
without clearance
Uncertainty
Refinement of internal exposure
do ADME studies
PBK prediction0.0001µM
20µM
BioSpyderTranscription profile
In vitro assays
Oxidative Stress NOAEC
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NGRA CORE ELEMENTS
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IN VIVO KINETICS
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UNDERSTANDING CONSUMER EXPOSURE
Systemic Exposure In vitro Assays:Kinetic SolubilityThermodynamic SolubilityMetabolic Stability-Human Hepatocytes-Human CYP450 Isoforms-Human Hepatic MicrosomesStability in Human PlasmaPlasma Protein BindingPartitioning in Human Blood
• Predicting systemic exposure• Enabling us to select and test relevant doses• Increased role for clinical work to confirm systemic exposure levels
PBK Modelling
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INPUTS: DERMAL PENETRATION
Dermal Kinetics
Sk
in B
ioa
vail
ab
ity
ex vivo human
skin
Understanding delivery to the systemic circulation following dermal application
Understanding the kinetics of an ingredient in the skin to allow risk assessments for local endpoints
Davies et al (2011) Toxicol Sci 119, 308-18
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INPUTS: IN VITRO SYSTEMS FOR METABOLISM STUDY
In vitro model
HL fraction
S9
2D
suspensionsSandwich
culturePlated 2D
HepatoPac
3D
spheroids
Advanced
2DCo-cultured hepatocyteheterologously-
expressed system
microsomes
Typical Incubation period
~ 2 hours~ 4 hours
~ 24 hours ~ 7 days 1 ~ 2 (3) days~ 24 hours
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OutputPopulationPBK
ModelPrediction
methodInput
Uncertainty
PBK MODELLING CHALLENGES
In silico
In vitro
Physico-chemicalCL/metabolismProtein binding
Dermal penetration
TransportersPhysiologyExposure
No established in silico method for predicting Clearance rate
How to account for population variability, e.g. differences metabolism?
Several options for in vitro clearance. What is best for a compound?
Need to understand uncertainty through process, e.g. parameter & model uncertainty.
Unclear when transporters important.
Assumption that plasma concentration is the most relevant metric for QIVIVE. Is this always true?
Commercial? Open source?Many tissues or simple compartmental?What are the domains of
applicability/confidence?
Clinical PK data
Need to account for limited population coverage.
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IN VITRO KINETICS
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IN VITRO ASSAYS IN RISK ASSESSMENT
0-10% serum
single cells / microtissues
high concentrations
short exposure time
no bioaccumulation
limited metabolism
100% serum
connected cells / tissues
low concentrations
long / pulsed exposure
tissue bioaccumulation over time
full metabolic pathways
What metrics can we use to compare effects
in vivo to effects in vitro to improve QIVIVE?
effect in vitro effect in vivotarget site
intracellular
free concentration
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MECHANISTIC UNDERSTANDING, DOSE RESPONSE AND DECISION MAKING
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PATHWAY CHARACTERISATION(TARGETS)
EXAMPLES:3D and organotypic cell modelsMolecular dynamic simulations
Integrated in vitro systems
IN SILICO-FIRST
EXAMPLES:MIE in silico Atlas & QSARsSkin haptenation modellingIn silico receptor screening
Tier 1
In silico-first approaches for identifying pathways of
concern, building weight of evidence and formulating
hypotheses for testing
PATHWAY IDENTIFICATION(TARGETS AND OFF-TARGETS)
EXAMPLES:HT-Transcriptomics
In vitro screening panelsHigh content imaging
SPME free concentration
Tier 2
Identifying/characterising lead MIEs and pathways
through experimental data generation, informatics data
mining and computational modelling
Tier 3
Characterisation of response in biologically
relevant in vitro systems or complex computational
models for decision making
A TIERED AND ITERATIVE APPROACH
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UNILEVER/US EPA 2015-2020: JOINT CRADA
CASE STUDY CHEMICALS
1. Caffeine
2. Curcumin
3. Bisdemethoxycurcumin
4. Tetrahydrocurcumin
5. 6-Gingerol
6. Coumarin
7. Hydroquinone
8. Doxorubicin
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CELL STRESS PANEL
• Range of biomarkers covering ~10 cell stress pathways:
Mitochondrial Toxicity: MitoSOX, PGC1α, MMP, ATP, Glu/Gal
Oxidative Stress: GSH, ROS, SRXN1, NRF2
DNA damage: pH2AX, p53
Inflammation: TNFAIP3, ICAM1, NFkB p65, IL-1β, IL-8, HMGB1
ER Stress: PERK, ATF4, CHOP, XBP1, BiP, ER Tracker
Metal Stress: MTF-1, Metallothionein
Osmotic Stress (NFAT5); Heat Shock (HSP70); Hypoxia (HIF1α)
Cell Health: LDH, Phospholipidosis, Steatosis, pHrodo indicator, apoptosis (caspase-3/7) & necrosis (ToPro-3)
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NOTEL* is the derived concentration of a compound that does not elicit a meaningful change in gene expression (i.e. the threshold of the concentration that elicits minimal mechanistic activity).
HIGH THROUGHPUT TRANSCRIPTOMICS
Recommended approaches in the application of toxicogenomics to derive points of departure for chemical risk assessmentFarmahin et al (2017) Arch Tox 91, 2045-65
Thomas et al (2013). Toxicol Sci, 134, 180-94
*NOTEL = No observed transcriptional effect level
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HIGH THROUGHPUT TRANSCRIPTOMICS
Fold change >1.5Genes in pathway >3Fishers exact test >0.1(3 independent experiments)
HepG2BMD minimum – 295BMD medium– 450BMD maximum 962
MCF7BMD minimum – 117 BMD medium – 167BMD maximum 290
HepaRGBMD minimum –237BMD medium – 344BMD maximum 913
POD - NOTEL value
Conc. Phenoxyethanol (µM)
Acc
um
ula
tio
n
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NGRA – EXPOSURE-DRIVEN CASE STUDIES
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NGRA – EXPOSURE-DRIVEN CASE STUDIES
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In-vitro cell culture
Characterise stress response
Low-risk exposure
• Which cell model? 2D or 3D? • Primary or cell line?• Which pathways/biomarkers?• How many time points/dose points?
• How do we calculate the tipping point?• Number of pathways (coverage)• Duration of response
• Cells in media vs tissue?
• Chronic vs acute exposure
Characterise uncertainties to facilitate decision making
Prof B. van de Water, U. Leiden
UNCERTAINTY AND DECISION MAKING
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RESEARCH NEEDS
The remit of the joint awards
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RESEARCH NEEDS – POTENTIAL AREAS FOR PhDs
Exposure
• What is the impact of clearance mechanisms (other than skin and liver) on systemic bioavailability, e.g. renal clearance?
• What is the impact of active transport mechanisms (intracellular) to enable IVIVE?
• What is the most relevant metric of exposure in vitro for IVIVE?
Inhalation
• What pathways should we be concerned about for respiratory toxicity? Beyond Fibrosis?
• What is the impact of receptors on respiratory toxicity?
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RESEARCH NEEDS – POTENTIAL AREAS FOR PhDs(CONTINUED)
Immune Effects
• What is the influence of the microbiome on Oral Immunity?
• Local Exposure - Skin, Lung & Oral cavity – can we challenge the assumption that our risk assessment should be based on 100% bioavailability
Uncertainties
• Biological coverage - Right choice of Cells /Cell Model?
• Repeat dosing – considerations for local exposure and IVIVE?
• Influence/relevance of clearance in our models?
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THANK YOU…
www.tt21c.org