SYSTEMATIC APPROACH TO THE SAFETY ASSESSMENT OF … · lead MIEs and pathways through experimental...
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SYSTEMATIC APPROACH TO THE SAFETY ASSESSMENT OF NATURALS FOR USE IN CONSUMER PRODUCTS
SIVARAM TK
SAFETY & ENVIRONMENTAL ASSURANCE CENTRE, UNILEVER R&D, INDIA
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NATURALS
Natural substances are substances which occur in nature. There are various definitions,
• According to REACH (Art. 3 (39)) [1] ‘substances which occur in nature: means anaturally occurring substance as such, unprocessed or processed only by manual,mechanical or gravitational means, by dissolution in water, by flotation, byextraction with water, by steam distillation, or by heating solely to remove water orwhich is extracted from air by any means’
• As per the European cosmetics directive, Naturals are “ Raw materials which areisolated using only physical processes from a natural source which is unchangedfrom the way it occurs in nature”.
• Naturally derived
• Natural identical
• Organic
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NATURALS IN PERSONAL CARE PRODUCTS
• Naturals as cosmetic ingredients – No more a “Trend” but now in “Mainstream” with gained popularity in consumers
• There is now a growing consumer interest in food and cosmetic products which contain botanicals, often as an ingredient with established or perceived functional benefit.
• Common misconception on natural ingredients
• It’s natural so it will be safe
• It’s natural so it doesn’t contain any chemicals
• It’s easily biodegradable
• It’s a sustainable resource
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ALL NATURALS - ARE SAFE !
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Some see natural substances as alternatives to chemicals…
But all substances are just arrangements of the same 90-odd chemical elements.
THERE ARE NO CHEMICALS IN NATURAL PRODUCTS !
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Minerals are not biodegradable!
Some essential oils not easily biodegradable
Wood does notrapidly biodegrade
NATURALS ARE EASILY / QUICKLY BIODEGRADABLE !
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There can be environmental consequences…
e.g. Natural alpha-bisabolol (for sensitive skin) is extracted from Candeia plant…
…a scarce, exotic flora found in Amazonian rainforests.
ALL NATURALS - ARE EASILY SOURCED !
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E.g. Natural & Synthetic fragrance & flavours
• Peppermint oil – natural: high carbon footprint – up to 50 kg CO2 equivper kg oil…
• Synthetic-derived fragrance ingredients: range from around 4 kg CO2/kg - 40 kg CO2/kg
NATURALS = LOW CARBON FOOTPRINT !
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SAFETY CHALLENGES
• Naturals are complex mixtures of many chemicals, each with many potential effects, most of which are unknown
• Safety challenges are the same as those for any material• Comprehensive characterisation and risk assessment approaches• History of safe use approach
chemical complexity
chemical understanding
NATURALS
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Partnering To realise full potential of naturals in a Safe and Sustainable manner
Transparency & Clear Communication on:
• Facts
• Risks
• How to manage them
Unambiguous Identification to avoid
• Adverse events
• False challenges
Specifically
• Risk & Impact Assessment Methodologies
• History of Use Data & Information
NATURALS – SAFETY – SEAC’S ROLE
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Applied to Assessment of novel foods e.g. Noni Juice
Result:
Acceptable at observed intake (30 ml)*
* EU Scientific Committee for Food (2002)
History of Use
Approval decision
Evidence for
concern
Degree of similarity Exposure Biological effects
(efficacy)
Mechanism of action
Evidence of adverse
effects in Man
Toxicological data
Contra-indications
Population
No. of people exposed
Frequency of use
Intake
Duration of exposure
Origin of ingredient
Specification of
ingredient
Preparation/processing
Decision
Criteria cluster
Criterion to
be assessed
Value Tree for Safe History of Use
MCDA model
Bioavailability
… to area of acceptable HoSU
From approval decision criteria to model … Are complex and may contain
hazardous materials
Long-term human experience may be relevant measure experience
Level of safety regarded as “acceptable”
Naturals:
HISTORY OF SAFE USE MODEL
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KEY CRITERIA IN DEFINING HISTORY OF SAFE USE
History of Use
Origin of ingredient
• Similarity of spec
• Prep and processing similarity
• Similarity of population to be exposed especially products aimed at babies/children (comparator should have similar history of exposure)
• No of people exposed
• Pattern of use/frequency of application
• Bioavailability/Skin penetration
Evidence of Concern
Toxicology data
• High Concern: Reproductive or developmentaltoxicity, mutagenicity, neurotoxicity or anyorgan toxicity, data showing skin sensitization(type IV allergy), type I allergy, skincarcinogenicity, phototoxicity effects
• Chemical components of concern, known skin sensitisers, photoallergens, protein
• Biological effects/mechanism of action
• Evidence of adverse effects in man(Information from literature review or existingclinical data)
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R&D - SEAC
HISTORY OF SAFE USE (HOSU)
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FINGERPRINTING
Knowns & unknowns – we don’t need to identify every component
• Unique signals for as many components as possible
• Holistic view
• Respectful of Ayurveda philosophy
‘A unique visual pattern representing the presence of known and/or unknown characteristic chemical components’
Definition:
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ANALYTICAL DATA
R&D - SEACR&D - SEAC
COMPARATOR
PURIFIED EXTRACT
Mo
lecu
le 4
Mo
lecu
le 2
Mo
lecu
le 5
Mole
cule
7
Mo
lecu
le 8
Mo
lecu
le 2
Mo
lecu
le 4
Mo
lecu
le 3
Mole
cule
5
Mo
lecu
le 6
Mo
lecu
le 7
Mo
lecu
le 8
Mo
lecu
le 1
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BUT WHAT IF
?Traditional methods Desired material
- There is no HoU for the comparator of the desired material- Or route of exposure differs compared to traditional HoU (Oral exposure but no
dermal)- For HoSU risk assessments which indicate high risk
We are good at demonstrating similarity but what if we can’t?
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HOW CAN SYSTEMS BIOLOGY HELP SAFETY ASSESSMENT?
Understanding holistic and interdependent biological effects
• Identify pathways of concern
• Determine mechanism of action
• Lead further research priority areas
Naturals - When History of Safe Use is not relevant?
• Data analysis and uncertainty assessment is a challenge
We see systems biology tools and creative ways to integrate data as key tounderstanding the mechanistic effects of our ingredients and products
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MULTIDISCIPLINARY RESEARCH: INVESTMENT IN PREDICTIVE BIOLOGY
• Non-animal approaches to assuring safety rely on a new network of scientific disciplines
• Exposure science• Computational/mathematical modelling • Informatics• Complex 3D cell/tissue culture/imaging• Molecular and high content biology• Transcriptomics and proteomics• Mechanistic chemistry
• New challenges around standards, quality and governance
Reynolds et al (2014), Biochemist, 36, 19-25
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1. DATA GENERATION
• Start with what we know
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FOCUSSED TRANSCRIPTOMICS
L1000
• L1000 Expression Profiling measures 978 validated landmark genes identified through connectivity mapping
• Comparison with public L1000 data from the LINCS Program
BioSpyder
• Custom content panels available dependant upon the problem posed
• Included in the FDA ToxCast programme
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2. ANALYSIS OF MULTIPLE DATA TYPES
Microarray Differential Expression
RNAseqDifferential Expression
Whole genome methylation
Analysis
Utilise Genestack platform to manage data provenance and governance across internal & public data sets.
Functional group (pathway/Gene set) & Gene Level BMD identification for NOTEL
Differential expression
Pathway & Functional Analysis
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3. INTEGRATED READ ACROSS
Lamb et al. Nature Chemical Biology 2, 663 - 664 (2006)Cronin et al. RCS Chemical Toxicity prediction: Category formation
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READ-ACROSS
• Biological signatures for read-across
Readout Parameters (Biomarkers)
E-selectin
TNF-
IL-8
PGE2
IL-8MCP-1
MCP-1, IL-8, E-sel. decreaseLeukocyte recruitment
Many, e.g. Jilma et al., 2000
PGE2 decreasePain, swelling
Sebaldt et al., 1990
Collagen I & III
Collagen I, III decreaseSkin atrophy
Autio et al., 1994
MMP-1
PAI-1
SAA
PAI-1, SAA increaseCV complications
Sartori et al., 1999Fyfe et al., 1997
PAI-1
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• Utilise algorithms such as Reverse Causal Reasoning to understand mechanistic causes of gene expression changes.
• Links prior knowledge of causal associations eg. Activiation of protein A results in upregulation of Gene B,C & E. Utilise directed networks.
4. MODE OF ACTION DETERMINATION AND APPLICATION
MoA or AOP
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SYSTEMS BIOLOGY APPROACHES TO IDENTIFY PATHWAYS AND GAIN CONFIDENCE IN ABSENCE OF OFF-TARGET EFFECTS
Transcriptomics & metabolomics
High Content Screening
Informatics
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NEXT GENERATION RISK ASSESSMENT (NGRA)
• Using new tools and approaches to build a risk assessment to enable decisions to be made
• An exposure-led risk assessment solution to biological pathway-indicated hazard concerns
Exposure led Mechanistic Hypothesis driven
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PATHWAY CHARACTERISATION(TARGETS)
EXAMPLES:3D and organotypic cell modelsMolecular dynamic simulations
Integrated in vitro systems
IN SILICO-FIRST
EXAMPLES:Molecular initiating event (MIE) in
silico predictions & 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 panelsReceptor binding assaysSPME 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
TIERED APPROACH
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Unilever Information: Internal Use
FOR MORE INFORMATION ON SEAC’S RESEARCH VISIT WWW.TT21C.ORG