Chemical risk assessment:Chemical risk assessment: Historical perspectives and p p

current trends

Jean Jean Lou Lou Dorne, Dorne, ,,EuropeanEuropean Food Food SafetySafety AuthorityAuthority, ,

Unit on contaminants in the Unit on contaminants in the foodfood chainchain

Acknowledgments Acknowledgments

Authors

EFSA, Parma, ItalyDjien Liem , Bernard Bottex, Claudia Heppner

CCD, Center for statistics on AIDS Chiang Mai, ThailandBilly Amzal

Center for Ecology and Hydrology , UKDavid Spurgeon and Claus Svendsen

University of Southampton, Professor Andrew Renwick OBEProfessor Andrew Renwick OBE

Scientific panel on contaminants in the food chain of EFSA

OutlineOutline

• Historical perspectives and principles

• Population variability and risk assessment

• Systematic review, meta-analysis and chemical y yrisk assessment

• Conclusions

3

Historical perspectives and principlesHistorical perspectives and principles

Chemical Risk Assessment

HumanEcological risk Animal HumanEcological risk assessment

Animal

Genotoxiccarcinogens

ThresholdEcological species;Daphnia, fish

Livestock /companion animals

NOECs NOAELs, LOAELs

LOAEL, NOAEL BMDLOAELs NOAEL,BMD

Margin of Exposure

ADITDIEnvironmental standard Margin of

safety

Four pillars of risk assessment

Hazard   identification and Exposure assessmentcharacterisation

Levels in food, feed, water, environmental media, dietaryexposure, food consumption, 

ADME, acute/sub‐chronic/chronic toxicity, human data, genotox, reprotox, mode of action,p , p ,

relevant food groups, time trends

Deterministic vs probabilistic

human data, genotox, reprotox, mode of action, NOECs (ecological)NOELs, LOAELs (animal, human)mathematical modelling (BMD), Health based guidance (TDI…)

X           vsg ( )

Risk characterisationRelate exposure to environmental standards (ecological), 

margin of safety (animal)margin of safety (animal)TDI, derive Margin of Exposure (human)

GenotoxicGenotoxic carcinogenscarcinogens

Margin of Margin of exposureexposureMargin Of exposure (MOE) developed, by the JECFA and EFSA (2005) Point of reference on the dose-response curve* (based on animal and human data) divided by the estimated human intakes. MOE (animal data) >10,000 as of low concern for public health.

BMD/BMDL: Benchmark dose/ limit(*NOAEL: No observed-Adverse-Effect-Level)

http://www.efsa.europa.eu/EFSA/Scientific_Opinion/sc_op_ej282_gentox_en3,0.pdfp

Non Non GenotoxicGenotoxic carcinogenscarcinogens

Chronic exposure daily : ADI: Intentionally added compounds; TDI: Contaminants

A t E A t R f d (ARfD)

ADI/TDI/ARfD (mg/kg/day) =

Acute Exposure : Acute Reference dose (ARfD)

ADI/TDI/ARfD (mg/kg/day) =

NOAEL or BMDL (mg/kg) / ( g g)100*

E t t i t f t *Extra uncertainty factors*

Missing data, uncertainty in the database, subgroups, mixtures

“All things are toxic and there is nothing without poisonous qualities: it is only thewithout poisonous qualities: it is only the dose which makes something a poison”

PARACELSUS (1493-1541)

Pharmaco/Toxicokinetics Pharmaco/Toxicodynamics

What the body does to thechemicalHow the chemical is eliminated

What the chemical does to thebodyHow the chemical exerts itsfrom the body or activated into

a toxic species (ADME )

How the chemical exerts itspharmacological effect/ toxicityTarget receptor/cell/organ

10

EFSA‘s Risk assessment ofcoccidiostats: Cross-contaminationcoccidiostats: Cross contaminationof non-target feedingstuffs: Animalhealth and human health

Feed safety conference 6-7/10/2009 Wageningen

11

Coccidiostats in animal feeds

Ionophoric polyethers Non-ionophoric

O

CH3

HO

O

H3C

O

H3C H3CH3C

CH3

H

Cl

CNCl

Cl

N

N

N

O

O

OO

O

CH3

O

H3C

H3CO

OH

O

O

OH

OHH

H H H

Monensin ALasalocid

S li iSalinomycinNarasin

MaduramycinSemduramycin

DecoquinateDiclazuril

HalofuginoneNicarbazin (DNC/HDP)

R b idi

12

Robenidine

C idi t tCoccidiostatsHazard identification and characterisation

:Toxicological effectsExposure assessment

Occurrence in feed(Cross-contamination of

2% 5% and 10%)

:Toxicological effects

Toxicity in non-target animal

Occurrence/ residues in animal tissues/

Consumption in humansToxicity in laboratory

animalsToxicokinetics

/residues in 2%, 5% and 10%)

-Feed consumption in

non-target animal species

speciesLOAEL/NOAEL

p

LOAEL/NOAELanimal tissues

Uncertaintyfactor 100

Exposure in non-target animal species

TDI

Human exposurep

13

Risk characterisation in animals Risk characterisation in humans

Population variability and risk assessment

14

Use of uncertainty factors (UFs)Use of uncertainty factors (UFs)

SPECIESDIFFERENCES

HUMANVARIABILITY

10 10

KINETICS DYNAMICSKINETICS DYNAMICS

E t l ti f f t t i l tExtrapolation from group of test animals to average human and from average humans to potentially sensitive sub-populationssensitive sub-populations

Uncertainty factorsUncertainty factors

100 - FOLD UNCERTAINTY FACTOR

INTER-SPECIESDIFFERENCES

INTER-INDIVIDUALDIFFERENCES

Chemical specific adjustment factors can replace the

DIFFERENCES

10 - FOLDDIFFERENCES10 - FOLD

pdefault uncertainty factors (IPCS, 2006)Use of PB-TK, PB-

TOXICO-DYNAMIC

TOXICO-KINETIC

TOXICO-DYNAMIC

TOXICO-KINETIC

TK -TD models when data available for chemical of interest

10 0.4

2.510 0.6

4.010 0.5

3 210 0.5

3 24.0 3.2 3.2

Uncertainty Factors:Uncertainty Factors:TTowards owards a more flexible frameworka more flexible framework

Data-derived Data-derived

Toxicokinetics Toxicodynamics

Human variability

orPathway-relatedUncertainty factorsor

orprocess relatedUncertainty factorsoror

general default(3.2)

or

general default(3.2)

Pathway-related UFs for main routes of metabolism in humans –intermediate option between default factor and chemical specific adjustment factors

Dorne and Renwick, 2005 Toxicol Sci 86, 20-26

Major Routes of chemical metabolism Major Routes of chemical metabolism and and excretionexcretion

Phase I enzymesCytochrome P-450 ADH Esterases

Phase II enzymesConjugation reactionsCytochrome P-450, ADH, Esterases Conjugation reactions

Glucuronidation

% of Pharmaceuticals Metabolized by Individual Cytochrome P450’s in man

P4502D6 P4501A2P4502A6

P4502C9

Sulphation

N-acetylation (Polymorphic)P4502A6

P4502C19

P4502E1

Amino acid conjugation

P4503ARenal excretion

TransportersCYP2C9 CYP2C19 CYP2D6* Polymorphic TransportersCYP2C9, CYP2C19, CYP2D6 Polymorphic (Extensive and Poor metabolisers, EMs and PMs). *Caucasian 8% PMs 92% EMs

ToxicokineticToxicokinetic differencesdifferences betweenbetween ExtensiveExtensive andand PoorPoormetabolisersmetabolisers (EMs(EMs andand PMs)PMs) forfor CYPCYP22DD66 phenotypesphenotypes

Ratio of internal dose (clearances) between EMs and PMs forCYP2D6 SubstratesCYP2D6 Substrates

Exponential relationships between ratio EM/PM and % CYP2D6 metabolism.PMs covered by pathway-related UFs for substrates with up to 25% (dose) ofCYP2D6 metabolism in EMs

ToxicokineticToxicokinetic differencesdifferences betweenbetween ExtensiveExtensive andand PoorPoormetabolisersmetabolisers (EMs(EMs andand PMs)PMs) forfor CYPCYP22CC1919phenotypesphenotypes

Ratio of internal dose (clearances) between EMs and PMs for CYP2C19substrates

phenotypesphenotypes

70.0

80.0

90.0substrates

40.0

50.0

60.0

EM/P

M

20.0

30.0Ratio

0.0

10.0

0 20 40 60 80 100

% CYP2C19 in EM

PMs covered by UFs for substrates with up to 20-25% (dose) of CYP2C19 metabolism in EMs.

Predicting human variability in toxicokinetics using Monte Carlo modellingMonte Carlo modelling

21

Latin hypercube sampling: variant of Monte Carlo

Stratified sampling throughout the distribution.

Compounds handled by multiple pathways :

1. predict variability and uncertainty factors for healthy adults andsubgroups.

2. Combine distributions describing pathway –related variabilityg p y yand quantitative metabolism data.

3. Compare simulated and published data

Dealing with subgroups subgroupsDealing with subgroups subgroups

-Ratio of internal dose between healthy adults and subgroups

-Pathway-specific variability (GSD).

-Simulate to get the final distributions

Polymorphic pathways : Combine distribution for EM and PM using frequency ofEM and PMs ( for CYP2D6 7 4% PM in Caucasian)EM and PMs ( for CYP2D6 7.4% PM in Caucasian)

PM

combinedEM PM

EMs

Healthy adults:

Uncertainty factors (99th til )Uncertainty factors (99th centiles)

Published Simulated

3 .43 .5

Published Simulated

2 .7 2 .72 .9

3 .03 .0ant ip yrine

co d e ine

d iazep am2 .32 .3

2 .01 .9

2 .02 .1

1 .8

d iazep am

imip ramine

p a race t amo l

p ro g uanil

p ro p rano lo l

Phenotyped healthy adults:

U t i t f tUncertainty factors (99th centile)

3.62.8

3.62.8

2.11 8

2.11.8

codeine propranolol

1.8

codeine propranolol

CYP2D6 EMs CYP2D6 PMs5.2

1.91.8

4.3 codeine

propranolol

Combined EMs and PMs

ToxiokineticsToxiokinetics of binary mixtures: of binary mixtures: CYP2D6 CYP2D6 inhibitioninhibition

20

25

tile)

EM non competitive

PM non competitive

EM Competitive

15

20to

rs (9

5 th

cen

t

5

10

cert

aint

y Fa

ct

0

5

Un

I i t l d i EMIncrease internal dose in EMs.UF for TK (3.2) would not cover EMs for potent CYP2D6 inhibitors.PMs not affected: alternative pathways of metabolism

EMs at risk if metabolite produced the toxicant but reverse situation withinhibition. PMs at risk if the parent compound is the toxicant.

Dorne and Papadopoulos, 2008

HarmonisationHarmonisation of human and of human and Ecological Ecological risk assessmentrisk assessment

Both use uncertainty factors but differ in what/who they aim to protect:Ecosystem or human populations. y p pHarmonisation focus on Mechanistic descriptors e.g., substance parameters, toxicokinetics, toxicodynamics, mode of actionCase studies looking at interspecies differences (mammals, birds) in kinetics

HumanHumanEcologicalEcological

Dorne, Ragas and Lokke. Toxicology 2006

Mechanistic model for ecological species

PORE BODY SOIL

INSIDE ORGANISMOUTSIDE ORGANISMDETOX TARGET

WATER WALL

M

SOIL

MM

M

M M

MMM

MMM

M

M

M M MM

MM

ML

M

MM

MMM

M

ENVIRONMENTAL AVAILABILITY

TOXICOKINETICS TOXICODYNAMICSSpurgeon et al., 2010- STOTEN

Systematic review, meta-analysis

and chemical risk assessment

29

What is a systematic review (SR) ?

• SRs are reviews that attempt to…id tif ll l t t di fitti d fi d it i– identify all relevant studies fitting predefined criteria

– systematically summarize the validity and findings of the studies

– synthesize or integrate the findings

• ...using techniques aimed at minimizing biasg q g

• Governed by principles ofSystematic reviews

y p p– methodological rigour– transparency

Meta analyses– reproducibility

Meta-analyses

30

Questions suited to SR

Type of question Examples of what the question seeks to assess

Effect of a deliberate intervention

- Nutritional properties of an additive in a food or feed

- Efficacy of a vaccine in preventing a diseaseEffect of exposure to a potential risk factor

- Mutagenic effect of a chemical on cells used in mutagenicity tests

A t f Ch i t i ki ti t f tiAssessment of a dose-dependent fate of a substance or dose response

- Changes in toxicokinetic parameters as a function of the dose of a chemical in animals or humans

- Changes in physiological parameters or bi k f ti f th d fdose-response

relationshipbiomarkers as a function of the dose of a chemical in animals or humans (toxicodynamics)

Environmental fate - Changes in the environmental distribution, d d i l hi ff f bdegradation, leaching, or run-off of a substance into surrounding areas as a function of its concentration

Population exposure control outcome (PECO) and steps of risk assessment

• Adult humans (16 or older) P• Chemical in food

PE

• Exposed group, non-exposed group

T i it / id i l f i diti i t d ith d

C

O • Toxicity/epidemiology of a given condition associated with dose; cancer, target organ damage

O

Hazard identification/characterisation• Hazard identification/characterisationTK: fate of chemical in populationTD: toxicity; genotox non-genotox, dose response

32

• Exposure assessment : in some cases SR from literature• Risk characterisation: SR not relevant

SR and hazard identification

Specific questions Question type, open/closed question, key-elements

Answer question using the SR method or SR h? T f id i d?elements search? Type of evidence required?

Does chemical X havegenotoxiceffects/cancer in rat

Narrow, CLOSED question, same question typeas above. Key-elements: chemical X=exposure,human liver=population, genotoxic effect/cancer

Potentially SR. Cohort studies in humans. If notavailable, case control studies. If not aggregateddata (clinical reports) may be considered. If not, dataeffects/cancer in rat

liver?human liver population, genotoxic effect/cancerinduction [=outcome] and comparator [=non-exposure])

data (clinical reports) may be considered. If not, datafor structurally-related compounds.

33Must be determined if SR worthwhile

SR and hazard characterisation

Specific questions Question type, open/closed question, key-elements

Answer question using the SR method or SR search? Type of evidence required?

Dose-response relationshipbetween chemical X and livertoxicity in the rat?

Narrow, CLOSED question, Dose-response type. Key elements:population=rat, measurement 1(quantitative)=dose of chemical X,

Potentially SR . Randomised control in vivo studies in rat using multiple doses over time following GLPs (OECD guidelines). If not available, randomised

outcome=liver toxicityg ) ,control in vivo studies. When none of the above are available, randomised control in vivo studies on structurally-related compounds may be considered.

Dose-response relationshipbetween chemical X and livertoxicity in humans?

Same as above. Key elements:population=humans, measurement 1(quantitative)=dose of chemical X,outcome=liver toxicity

Potentially SR .Ideally, randomisedcontrol trials in humans using multipledoses over time. If not available,aggregated data, clinical reports, narrowdose studies. When none of the above

il bl d t f t t ll l t dare available, data for structurally-relatedcompounds may be considered.

Previous ADI/TDI been derivedfor chemical X?

Narrow, OPEN question This Q is answerable doing a broadliterature search and anarrative description of the results.

34Must be determined if SR worthwhile

SR and exposure assessment and Risk characterisation

Specific questions Question type, open/closed question, key-elements

Answer question using the SR method or SR search? Type of evidence required?yp q

Exposure assessmentHow much ofchemical X occurs inthe different food

Narrow, CLOSED question, Occurence type.Key-elements: quantity of interest=quantity ofchemical x population= food commodity

Occurence data would be required and a SRwould not be necessary. In case not available, thisQ is potentially answerable using the SR methodthe different food

commodities?chemical x, population= food commodity Q is potentially answerable using the SR method.

In case, aggregated data on the concentration ofchemical X could be used

How much of thefood commodity is

Narrow, CLOSED question, quantity ofinterest=quantity of food commodity

Food consumption data over time would berequired and a SR would not be necessary. Iny

consumed byhumans?

q y yconsumed, population=humans

q ycase not available, this Q is potentially answerableusing the SR method. In case, aggregated dataon food consumption could be used.

Risk characterisation

What is the riskassociated withhuman exposure tochemical X?

Complex, OPEN question Answerable doing a broad literature search and anarrative description of the results

35Must be determined if SR worthwhile

SR and Meta-analysis of human data :cadmiumhuman data :cadmium

CADMIUM

Urinary cadmium

reflects thisdose

CADMIUMin food

Accumulatesover years

reflects thisaccumulation

biomarker

kidney Kidneydamages:β2-

effectbiomarker

• SR studies linking internal dose (urinary β2-microglobulin

SR studies linking internal dose (urinary cadmium) to (early) biomarkers of bone/renal effects

• Extensive literature search (19661966 OctoberOctober• Extensive literature search (19661966--October October 20082008) (2 persons in parallel / cross checking)

• Geometric means and SD recorded

36

• 5000 abstracts > 200 relevant papers > 63 included

Final databaseRenal

BiomarkerTotal β2-

MGα1-MG

NAG (total)

NAG a

NAG b

RBP Protein-Uria

(total)(total)

N studies 54 35 16 27 1 2 10 11Continous

data

Bone Total BMD Calcium bALP PTHBoneBiomarker

Total BMD Calcium serum

bALP PTH

N studies 9 5 5 5 4

165 entries

30,000 individualsN studies

Continous data9 5 5 5 4 individuals

37=> 1 to 10 « entries » by study

Hill dose-effect model

Log b2GM

ude Shape

Parameter( )

amplit (η)

background

dLog UCd

ed50

38Effect=bkground + amplitude*(dη / (dη + ed50

η) )

Effect (B2MG) vs dose (U-Cd) data

1000000

100000

/g c

rea)

1 colour = 1 studyDiameters=GSD

1000

10000

lobu

lin (u

g/

10

100

B2-

Mic

rogl

0.1 1 101

10

Urinary Cadmium (ug/g crea)

39

Urinary Cadmium (ug/g crea)

Points considered in the analysis

• Account for group sample sizesAccount for and quantify inter study variability• Account for and quantify inter-study variability

• Account for and quantify the population variability«surrounding » the dose effect curve => allows for«surrounding » the dose effect curve => allows for BMD evaluation for any cutoff

effect Prevalence Correspondingeffect Prevalence Correspondingto the cut off

Cut off

40dosed1 d2 d3 d4

Overall fit

106

104

105

ug/g

cre

a)

103

104

rogl

obul

in (u

102

B2-

Mic

r

10-1 100 101 102101

Urinary Cadmium (ug/g crea)

41

Model fit with adjustment for ethnicity

106

4

105

g/g

crea

) asiancaucasianjapanese

103

104

glob

ulin

(ug

102

10

B2-

Mic

rog

10-1 100 101 102101

Urinary Cadmium (ug/g crea)

42

Urinary Cadmium (ug/g crea)

Assuming additive effect on the log scale

Bayesian model for metaBayesian model for meta--analysis of analysis of toxicokinetictoxicokinetic datadata

Σstudy Μdrug Σdrug σΜdrug σΣdrug Pr(PM) Population cÜ|ÉÜáΣstudy Μdrug Σdrug σΜdrug σΣdrug Pr(PM) Population cÜ|ÉÜá

μ μd

study drug drug drug drug ( )

PM

parameterscÜ|ÉÜá

Population modelsμ μd

study drug drug drug drug ( )

PM

parameterscÜ|ÉÜá

Population modelsμstudy μdrugσdrug

)( k

modelstudy k

drug j

PM Population models• study mean: lognormal• compound mean: lognormal• compound specific inter

μstudy μdrugσdrug

)( k

modelstudy k

drug j

PM Population models• study mean: lognormal• compound mean: lognormal• compound specific inter

μsubjσsubj

)1(~1

,~)log(

)(2)(2)(

2

)(

)(2)(

)(

)(

log−

−

⎟⎟⎠

⎞⎜⎜⎝

⎛∑

jkjkjk

jk

jkjk

ijk

jk

nn

S

nN

nY

i

χσ

σμ

subject i

• compound-specific inter-subject var: gamma• PM subgroup mean:Mixture of lognormals

μsubjσsubj

)1(~1

,~)log(

)(2)(2)(

2

)(

)(2)(

)(

)(

log−

−

⎟⎟⎠

⎞⎜⎜⎝

⎛∑

jkjkjk

jk

jkjk

ijk

jk

nn

S

nN

nY

i

χσ

σμ

subject i

• compound-specific inter-subject var: gamma• PM subgroup mean:Mixture of lognormals

Data: Σlog(Yi)/n ; S2/(n-1) ; n ; (subgroups id)

Mixture of lognormals

Data: Σlog(Yi)/n ; S2/(n-1) ; n ; (subgroups id)

Mixture of lognormals

g( ) ; ( ) ; ; ( g p )g( ) ; ( ) ; ; ( g p )

Dorne and Amzal, 2008, Toxicology Letters, Eurotox 2008

44

In a nutshell… In a nutshell… CHEMICAL

Toxicological effectsExposure assessment

TICA

L ST

RY Occurrence data Food

Genotoxic Non-genotoxic

ANAL

YTCH

EMIS (Concentration in

food)

Food consumption

Toxicokinetics / Toxicodynamics

Chronic Acute

ANTI

TATI

VEOD

ELLI

NG Benchmark dose/ NOAELProbabilistic or deterministic

approach

QUA

MO

Health-based guidance value

pp

MOE ADI / TDI ARfD

45RISK ASSESSMENT Dorne et al (2009) TrAc: 28,6 , 695

CONCLUSIONSCONCLUSIONSCONCLUSIONSCONCLUSIONS

T d• Towards more :

– Quantitative risk assessmentQuantitative risk assessment– Integration of population variability

• Harmonisation of ecological and human risk assessmentsusing mechanistic descriptors

46• Model-based approaches currently used in regulatory bodies throughout the world

EFSA websites

General EFSA Website :

http://www.efsa.europa.eu

CONTAM activities: http://www.efsa.europa.eu/EFSA/ScientificPanels/efsa localhttp://www.efsa.europa.eu/EFSA/ScientificPanels/efsa_local

e-1178620753812_CONTAM.htm

Si i EFSA' E t d t bSign up in EFSA's Expert database

http://www.efsa.europa.eu/EFSA/National_Focal_Points/Scientific_Cooperation_projects/efsa_locale-

1178620753812 t d t b ht1178620753812_expert_database.htm

Disclaimer

47The opinions and views reflected in this presentation are the authors’ only anddo not necessarily reflect the views of the European Food Safety Authority

MUCHAS GRACIASMUCHAS GRACIAS

49