Enhancing biological equivalen ts by biologically effective dose using a generic pbtk model the case of bpa and dehp
1. SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
ENHANCING BIOMONITORING EQUIVALENTs BY
BIOLOGICALLY EFFECTIVE DOSE USING A GENERIC
PBTK MODEL - THE CASES OF BPA AND DEHP
BPA - Glu &
BPA – Sulf
formation
GI tract – portal vein GI tract – portal vein
BPA - Glu &
BPA – Sulf
formation
GI tract – portal vein GI tract – portal vein
Liver Liver
Liver Liver
Heart Heart
Heart Heart
Brain Brain
Brain Brain
Muscles Muscles
Muscles Muscles
Skin Skin
Skin Skin
Kidneys Kidneys
Kidneys Kidneys
Adipose Adipose
Adipose Adipose
Bones Bones
D.A. Sarigiannis
Bones Bones
Breast Breast
Gonads Gonads
Placenta
Uterus - gonads Uterus - gonads Placenta
S.P. Karakitsios
Lungs Lungs
Arterial blood Lungs Venous blood Arterial blood Lungs Venous blood Arterial blood Venous blood Arterial blood Venous blood
A. Gotti
1AristotleUniversity of Thessaloniki, Department of Chemical Engineering, Environmental
Engineering Laboratory, Thessaloniki, 54124, Greece;
2Centre for Research and Technology Hellas (CE.R.T.H.), Thessaloniki, 57001,Greece
2. Rationale
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
This study attempts to refine the Risk Characterization Ratio (RCR) calculation comparing
Biomonitoring Equivalents (BEs) with tissue-specific Biologically Effective Dose (BED) of the
chemicals in question. This is expected to improve significantly the efficacy of risk assessment.
Social Benefit
Increasing benefit →
Increasing cost →
Social cost
Optimal
cost-benefit
Acceptable risk
Exposure reduction →
3. Rationale
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
The overall methodology is demonstrated for Bisphenol-A (BPA) and
di(2-ethylhexyl)phthalate (DEHP), both known to be Endocrine Disruptors (EDs).
4. Methodological concept – current status
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
Estimate sum of metabolites using excretion
Human dose fraction data; divide by avg. daily creatinine BE
(e.g. RfC, TDI) excretion or urinary volume - UFH
Simple PK
considerations
UFAH
Animal dose
UFA
Animal POD
UFAH
Human Equiv. Estimate sum of metabolites using excretion
fraction data; divide by avg. daily creatinine BEPOD
POD excretion or urinary volume
Simple PK
considerations
UFH
BE
5. Methodological concept – current status
for BPA and DEHP
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
Threshold value systemic reference
NOAEL 5 mg µg/kg_bw/day →
BPA UF = 10 intra-species and 10 for inter-individual differences → EFSA, 2006
TDI 5 µg/kg bw/day
NOAEL 44 mg µg/kg_bw/day →
UF = 10 intra-species and 10 for inter-individual differences, 10 Health Canada, 1998
for potential teratogenicity) → TDI 5 µg/kg bw/day
NOAEL 5 mg µg/kg_bw/day →
UF = 10 intra-species, 10 (for adults) 20 (kids above 3 months) -
DEHP ECB, 2008
25 (neonates up to 3 months) inter-individual differences) →
TDI 50-20 µg/kg bw/day
NOAEL 5 mg µg/kg_bw/day →
UF = 10 intra-species, 10 inter-individual differences) → EFSA, 2005
TDI 50 µg/kg bw/day
6. Methodological concept [a] –
Uncertain about MOA and PD similarities
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
Estimate sum of metabolites using excretion
Human dose fraction data; divide by avg. daily creatinine BE
(e.g. RfC, TDI) excretion or urinary volume - UFH
Simple PK
considerations
UFAH
Animal dose
Human PBTK
UFA
Human PBTK
Human Human dose
Animal POD UFAH Reverse dosimetry (capturing bioavailability
BED differences)
UFAH
Human PBTK
Human Equiv. Estimate sum of metabolites using excretion
UFH
fraction data; divide by avg. daily creatinine BEPOD
POD excretion or urinary volume
Simple PK
considerations
UFH
BE BE
7. Methodological concept [b] –
confident about MOA and PD similarities
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
Estimate sum of metabolites using excretion
Human dose fraction data; divide by avg. daily creatinine BE
(e.g. RfC, TDI) excretion or urinary volume - UFH
Simple PK
considerations
UFAH
Human PBTK
Animal BED to Human BED (equal (?) Human Human dose
Animal dose UFA Animal BED with respect to the mode of action)
Reverse dosimetry (capturing bioavailability
BED differences)
UFA
Animal PBTK
Animal POD
Human PBTK
UFAH
UFH
Human Equiv. Estimate sum of metabolites using excretion
fraction data; divide by avg. daily creatinine BEPOD
POD excretion or urinary volume
Simple PK
considerations
UFH
BE BE
8. Generic human/rodents
lifelong PBTK model
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
BPA - Glu &
BPA – Sulf
formation
GI tract – portal vein GI tract – portal vein
Breast feeding link
ADME processes
Liver Liver
Heart Heart
dC_ breast C_ breast
V PS _ cell _ breast fu C_ int_ breast Lexcr
dCij Brain Brain
dt K _ breast
Vi Qi (CAj CVij ) Metabij E limij Absorpij Pr Bindingij
dt C_ breast
Muscles Muscles
Lexcr Q_ milk P_ milk / blood
K _ breast
Skin Skin
Kow Fl_ tissue Fw_ tissue
The blood/tissue partition coefficients are Kidneys Kidneys P_ milk / blood
Kow Fl_ blood Fw_ blood
contaminant specific and are estimated by the Adipose Adipose
tissue lipids content and the octanol/water partition
coefficient of the contaminant by the following
Bones Bones
formula
Breast Breast
Uterus - gonads
Placenta
Uterus - gonads Placenta
Mother –Fetus interaction
K ow Fltissue Fwtissue
Ptissue / blood Arterial blood Lungs Arterial blood Lungs Venous blood
K ow Flblood Fwblood Quterus_M Cuterus _ M
Futerus _ M Cart _ M K d _ uter _ pla C placenta Cuterus _ M
BPA - Glu &
BPA – Sulf
formation
t Puterus
GI tract – portal vein GI tract – portal vein
Qplacenta C placenta
K d _ uter _ pla C placenta Cuterus _ M Fplacenta_B Cart _ B
Organ volumes (V) and blood flows (Q) were taken Liver Liver
t Pplacenta
from the ICRP (2002) report and the obtained data K d _ pla _ amniot C placenta Camniot
Pplacenta
K m _ placenta C placenta
Pamniot
were fitted to time (T) in order to exclude
Heart Heart
continuous time depended non lineal polynomial Brain Brain
Qamniot
K d _ pla _ amniot C placenta Camniot
Pplacenta
Ke _ gut _ B Cgut _ B
formulas in the form of: Muscles Muscles
t Pamniot
V a Tb c Td e Skin Skin
K e _ bile _ B Cliver _ B K a _ amniot _ B Camniot
Kidneys Kidneys
The permeability parameters PS were scaled
Adipose Adipose
according to the formula: Bones Bones
0.75
Gonads Gonads
Sarigiannis DA, Karakitsios SP. A dynamic physiology based
Vtissue _ child pharmacokinetic model for assessing lifelong internal dose.
PStissue _ child PStissue _ adult
Vtissue _ adult Arterial blood
Lungs
Arterial blood
Lungs
Venous blood
AIChE 2012, Pittsburgh, PA, 2012.
9. BPA human/rat
toxicokinetic differences
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
3.0 Actual BED is higher in mice due
Single oral dose of to enterohepatic recirculation
50μg/kg_bw ↓
2.5 Toxicokinetic factor for animal to
Human human extrapolation not quite
Free plasma BPA (μg/L)
necessary if PBTK model is used
2.0 Rat ↓
What about human inter-individual
1.5 variability?
1.0
0.5
0.0
1 5 9 13 17 21 25 29 33 37 41 45 49
Time (h)
10. BPA human inter-individual variability
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
- Wider inter-individual variability regarding
glucuronidation capacity (significantly lower clearance Adult EFSA TDI dose
for neonates/infants) (50 μg/kg-bw/d) BED
- Very strong plasma protein binding
- First-pass metabolism decisive for clearance – wide
bioavailability differences are expected from routes
beyond oral (up to six times higher internal dose
concentrations for inhalation compared to oral)
- BPA-GLU de-conjugates to BPA in the stomach,
increasing the actual dose during breast feeding,
thus, the sum of BPA and BPA-GLU needs to be taken
into account as BPA dose during breast feeding
- BPA-GLU de-conjugates to BPA in the placenta, 0.144 0.152 0.160 0.167 0.175 0.183
increasing the actual dose during pregnancy Free plasma BPA (μg/L)
11. BPA daily exposure and RCR
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
14
1.20 Fetus
Premature infants
12
Bottle fed neonates
1.00
Breastfed neonates
10 Children
Exposure (μg/kg_bw/d)
0.80 Adults
8
0.60
6 RCR
0.40
4
2 0.20
0 0.00
Fetus Premature Bottle fed Breastfed Children Adults
infants neonates neonates EFSA BED-BE [a] BED-BE [b]
Daily intake under typical RCR under different
exposure scenarios methodological schemes
12. DEHP human/rat toxicokinetic differences
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
0.9 Single oral dose of 250
50μg/kg_bw Human DEHP
0.8 Rat DEHP
Human MEHP 200
0.7
Rat MEHP
0.6
MEHP plasma (μg/L)
DEHP plasma (μg/L)
Actual BED is higher in rat (especially MEHP) due 150
0.5 to enterohepatic recirculation and slower renal
elimination of MEHP-Glu
0.4 ↓
Toxicokinetic factor for animal to human 100
0.3 extrapolation not quite necessary if PBTK model
is used
0.2 50
0.1
0.0 0
1 5 9 13 17 21 25 29 33 37 41 45 49
Time (h)
13. DEHP daily exposure and RCR
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
1.4 Adults 0.04 Adults
Kids Children
1.2 0.03
Uptake (μg/kg_bw/d)
1.0 0.03
0.8 0.02
RCR
0.6 0.02
0.4 0.01
0.2 0.01
0.00
0.0 EFSA BED-BE [a] BED-BE [b]
Inhalation Oral Skin
Daily intake under typical RCR under different
exposure scenarios methodological schemes
14. Conclusions
SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
• Incorporating toxicokinetic considerations in animal to human extrapolation
allows multiple options for minimizing uncertainty and unnecessary conservatism,
based on whether uncertainty and knowledge gaps are related mostly to MOA or
toxicokinetics
• Identification of inter-individual differences in bioavailability related to
- inter-individual variability of enzyme related genotypes
- windows of developmental susceptibility (e.g. pregnancy and infancy) due to
immature detoxification processes
- route of administration
might be more important than inter-species differences
• Refinement of RCR should rely not only on the accurate identification of
toxicological thresholds, but also on the relevance of exposure scenarios in terms
of age groups and administration route.
• This way, unnecessary conservatism (e.g oral exposure scenarios for adults
exposed to levels marginally above TDI) is avoided and exposure scenarios
posing risks are identified (e.g. premature infants hosted to intensive care units
exposed to BPA at levels below TDI)
15. SOT’s 52nd Annual Meeting San Antonio, Texas March 10th –14th 2013
Thank you for your kind attention
www.enve-lab.eu
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Notas do Editor
In this figure, it is graphically illustrated the methodological concept of the INTERA approach, following the source to dose continuum.Keeping in line to the source to dose assessment, we initiate by identifying the potential indoor sources of contamination, taking into account also outdoor contributions such as traffic. From emissions, we move to environmental media concentrations, thus meaning the concentrations in the indoor air from all type of sources. After estimating the concentrations, we need to calculate human exposure from all type of possible exposure pathways and routes. Thus, besides exposure from inhaling indoor air, exposure due to non-dietary oral exposure as well as dermal exposure will be taken into account.Following, we estimate internal dose. Internal dose is the actual exposure metric, and it might be referring either to the parent compound entering human body or to the product of metabolisms. Additional advantage from the implementation of internal dose arises from the possibility of use of biomarker data. Although INTERA project is focused on exposure, exposure data or internal dose data might be further used for assessing possible health risks or the margin of safety for the indoor locations under study. All the above methodological elements described above, are currently implemented within a computational platform, which is composed by individual models. In addition, the overall modelling platform derives dynamic source to dose calculations, meaning that we can track the temporal variability of the several intermediate outcomes.At this point, we need to address that the overall assessment does not always start from emissions, but the starting point might be indoor concentration or even inhalation exposure.
In this figure, it is graphically illustrated the methodological concept of the INTERA approach, following the source to dose continuum.Keeping in line to the source to dose assessment, we initiate by identifying the potential indoor sources of contamination, taking into account also outdoor contributions such as traffic. From emissions, we move to environmental media concentrations, thus meaning the concentrations in the indoor air from all type of sources. After estimating the concentrations, we need to calculate human exposure from all type of possible exposure pathways and routes. Thus, besides exposure from inhaling indoor air, exposure due to non-dietary oral exposure as well as dermal exposure will be taken into account.Following, we estimate internal dose. Internal dose is the actual exposure metric, and it might be referring either to the parent compound entering human body or to the product of metabolisms. Additional advantage from the implementation of internal dose arises from the possibility of use of biomarker data. Although INTERA project is focused on exposure, exposure data or internal dose data might be further used for assessing possible health risks or the margin of safety for the indoor locations under study. All the above methodological elements described above, are currently implemented within a computational platform, which is composed by individual models. In addition, the overall modelling platform derives dynamic source to dose calculations, meaning that we can track the temporal variability of the several intermediate outcomes.At this point, we need to address that the overall assessment does not always start from emissions, but the starting point might be indoor concentration or even inhalation exposure.
In this figure, it is graphically illustrated the methodological concept of the INTERA approach, following the source to dose continuum.Keeping in line to the source to dose assessment, we initiate by identifying the potential indoor sources of contamination, taking into account also outdoor contributions such as traffic. From emissions, we move to environmental media concentrations, thus meaning the concentrations in the indoor air from all type of sources. After estimating the concentrations, we need to calculate human exposure from all type of possible exposure pathways and routes. Thus, besides exposure from inhaling indoor air, exposure due to non-dietary oral exposure as well as dermal exposure will be taken into account.Following, we estimate internal dose. Internal dose is the actual exposure metric, and it might be referring either to the parent compound entering human body or to the product of metabolisms. Additional advantage from the implementation of internal dose arises from the possibility of use of biomarker data. Although INTERA project is focused on exposure, exposure data or internal dose data might be further used for assessing possible health risks or the margin of safety for the indoor locations under study. All the above methodological elements described above, are currently implemented within a computational platform, which is composed by individual models. In addition, the overall modelling platform derives dynamic source to dose calculations, meaning that we can track the temporal variability of the several intermediate outcomes.At this point, we need to address that the overall assessment does not always start from emissions, but the starting point might be indoor concentration or even inhalation exposure.
In this figure, it is graphically illustrated the methodological concept of the INTERA approach, following the source to dose continuum.Keeping in line to the source to dose assessment, we initiate by identifying the potential indoor sources of contamination, taking into account also outdoor contributions such as traffic. From emissions, we move to environmental media concentrations, thus meaning the concentrations in the indoor air from all type of sources. After estimating the concentrations, we need to calculate human exposure from all type of possible exposure pathways and routes. Thus, besides exposure from inhaling indoor air, exposure due to non-dietary oral exposure as well as dermal exposure will be taken into account.Following, we estimate internal dose. Internal dose is the actual exposure metric, and it might be referring either to the parent compound entering human body or to the product of metabolisms. Additional advantage from the implementation of internal dose arises from the possibility of use of biomarker data. Although INTERA project is focused on exposure, exposure data or internal dose data might be further used for assessing possible health risks or the margin of safety for the indoor locations under study. All the above methodological elements described above, are currently implemented within a computational platform, which is composed by individual models. In addition, the overall modelling platform derives dynamic source to dose calculations, meaning that we can track the temporal variability of the several intermediate outcomes.At this point, we need to address that the overall assessment does not always start from emissions, but the starting point might be indoor concentration or even inhalation exposure.
In this figure, it is graphically illustrated the methodological concept of the INTERA approach, following the source to dose continuum.Keeping in line to the source to dose assessment, we initiate by identifying the potential indoor sources of contamination, taking into account also outdoor contributions such as traffic. From emissions, we move to environmental media concentrations, thus meaning the concentrations in the indoor air from all type of sources. After estimating the concentrations, we need to calculate human exposure from all type of possible exposure pathways and routes. Thus, besides exposure from inhaling indoor air, exposure due to non-dietary oral exposure as well as dermal exposure will be taken into account.Following, we estimate internal dose. Internal dose is the actual exposure metric, and it might be referring either to the parent compound entering human body or to the product of metabolisms. Additional advantage from the implementation of internal dose arises from the possibility of use of biomarker data. Although INTERA project is focused on exposure, exposure data or internal dose data might be further used for assessing possible health risks or the margin of safety for the indoor locations under study. All the above methodological elements described above, are currently implemented within a computational platform, which is composed by individual models. In addition, the overall modelling platform derives dynamic source to dose calculations, meaning that we can track the temporal variability of the several intermediate outcomes.At this point, we need to address that the overall assessment does not always start from emissions, but the starting point might be indoor concentration or even inhalation exposure.
In this figure, it is graphically illustrated the methodological concept of the INTERA approach, following the source to dose continuum.Keeping in line to the source to dose assessment, we initiate by identifying the potential indoor sources of contamination, taking into account also outdoor contributions such as traffic. From emissions, we move to environmental media concentrations, thus meaning the concentrations in the indoor air from all type of sources. After estimating the concentrations, we need to calculate human exposure from all type of possible exposure pathways and routes. Thus, besides exposure from inhaling indoor air, exposure due to non-dietary oral exposure as well as dermal exposure will be taken into account.Following, we estimate internal dose. Internal dose is the actual exposure metric, and it might be referring either to the parent compound entering human body or to the product of metabolisms. Additional advantage from the implementation of internal dose arises from the possibility of use of biomarker data. Although INTERA project is focused on exposure, exposure data or internal dose data might be further used for assessing possible health risks or the margin of safety for the indoor locations under study. All the above methodological elements described above, are currently implemented within a computational platform, which is composed by individual models. In addition, the overall modelling platform derives dynamic source to dose calculations, meaning that we can track the temporal variability of the several intermediate outcomes.At this point, we need to address that the overall assessment does not always start from emissions, but the starting point might be indoor concentration or even inhalation exposure.