Biology-based approaches for mixture ecotoxicology Tjalling Jager.
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Process-based toxicity analysisin risk assessment
Tjalling Jager
Bas Kooijman
Dept. Theoretical Biology
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Contents
Dynamic Energy Budget (DEB) theory Current procedures in (eco)tox Introduction to DEBtox Advanced examples The DEB laboratory
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Why DEB theory?
How do individuals acquire and allocate their resources?
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Relation DEB and toxicants
??
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Relation DEB and toxicants
??
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Relation DEB and toxicants
??
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Dynamic Energy Budgets
food faeces
reserves
structure
maturity maint.somatic maint.
assimilation
1-
maturityoffspring
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DEB pillars
Quantitative theory; “first principles”– time, energy and mass balance
Life-cycle of the individual– links levels of organisation: molecule ecosystems
Comparison of species– body-size scaling relationships; e.g. metabolic rate
Fundamental to biology; many practical applications– (bio)production,(eco)toxicity, climate change …
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Chemical-related projects at TB
Dutch government (RWS and RIVM)– biaccumulation metals in mussels; biomonitoring– toxicokinetics dioxin in humans
Dutch Technology Foundation STW– DEBdeg (bio)degradation of (toxic) compounds– DEBtum tumour induction/growth, analysis tox data– DEBtox indpop (reprod. modes in nematodes)
EU Projects– ModelKey effects on ecosystems and food chains– NoMiracle mixture toxicity
More info: http://www.bio.vu.nl/thb/research/project/
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Current procedures in (eco)tox
EC50EC50
Re
sp
on
se
log concentration
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“RISK”“RISK”
Risk assessment
EXPOSUREEXPOSURE EFFECTSEFFECTS
air
water
sediment
naturalsoil
agricult.soil
industr.soil
emission advection diffusion degradation
Available data Assessment factor
Three LC50s 1000
One NOEC 100
Two NOECs 50
Three NOECs 10
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Integrated modelfor system
Integrated modelfor system
Process parametersat env. conditions
Process parametersat env. conditions
PECPEC
Lab. experimentsLab. experiments
Exposure assessment
air
water
sediment
naturalsoil
agricult.soil
industr.soil
emission advection diffusion degradation
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Contr.
Standard approaches
NOEC
Res
po
nse
log concentration
LOEC
*
1. Statistical testing
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What’s wrong with NOEC?
No statistically significant effect is not no effect Effect at NOEC regularly 10-34%, up to >50% Inefficient use of data
– only last time point, only lowest doses– for non-parametric tests also values discarded
NOECNOECR
es
po
ns
e
log concentration
Contr.Contr.
LOEC
*LOECLOEC
*OECD Braunschweig meeting 1996:NOEC is inappropriate and should be phased out!
OECD Braunschweig meeting 1996:NOEC is inappropriate and should be phased out!
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Standard approaches
EC50
Res
po
nse
log concentration
1. Statistical testing2. Curve fitting
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What’s wrong with ECx?
No estimation of process parameters– not possible to extrapolate to env. conditions
Inefficient use of data (last time point only) ECx depends on exposure time
EC50EC50
Re
sp
on
se
log concentration
Regression model is purely empirical
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Effects change in time
0 0.1 0.2 0.3 0.4 0.5 0.6 0.70
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
concentration
fra
cti
on
su
rviv
ing
48 hours
24 hours
Nonylphenol, survival
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Why does LC50 decrease?
Toxicokinetics– effects are related to internal concentrations
time
inte
rna
l c
on
ce
ntr
ati
on
chemical A
chemical B
chemical C
– kinetics depend on chemical
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Why does LC50 decrease?
Toxicokinetics– effects are related to internal concentrations– kinetics depend on chemical– and species …
time
inte
rna
l c
on
ce
ntr
ati
on
chemical A
chemical B
chemical C
small fish
large fish
Daphnia
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Sub-lethal EC10 in time
survival
body length
cumul. reproduction
body length
cumul. reproduction
0 5 10 15 200
0.5
1
1.5
2
2.5
carbendazim
time (days)0 2 4 6 8 10 12 14 16
0
20
40
60
80
100
120
140
pentachlorobenzene
time (days)
does not necessarily decrease in time …
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Consequences
Procedures are inefficient Test protocols yield more data than are used
NOEC and LCx/ECx are not representative Change in time, depending on species, body size,
chemical and endpoint
Standard exposure time leads to systematic error in comparing effects
– between chemicals (comparative RA, QSARs …?)– between species (SSDs … ?)
OECD Braunschweig meeting 1996:Exposure time should be incorporated in data analysis
OECD Braunschweig meeting 1996:Exposure time should be incorporated in data analysis
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Introduction to DEBtox
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DEBtox
– Windows software, version 1.0 in 1996, version 2.0.1 in 2004
– Included in draft ISO/OECD guidance on statistical analysis of ecotox data
OECD Braunschweig meeting 1996:Exposure time should be incorporated in data analysisMechanistic models should be favoured if they fit the data
OECD Braunschweig meeting 1996:Exposure time should be incorporated in data analysisMechanistic models should be favoured if they fit the data
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Why process-based?
Understand toxic effects– biology of organism and toxic mechanisms
Match experimental set-up– e.g. degradation, pulse exposure
Predictions for exposure situation– e.g. populations, food level, varying exposure
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DEBtox basics
Effect depends on internal concentration– one-compartment model
time
inte
rnal
co
nce
ntr
atio
n
timetime
inte
rnal
co
nce
ntr
atio
nin
tern
al c
on
cen
trat
ion
toxicokinetics
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targetparameter
toxicokinetics
DEBtox basics
internal concentration
DE
B p
aram
eter
NEC
blank value
internal concentration
DE
B p
aram
eter
NEC
blank value
Chemical affects a parameter in DEB– e.g. maintenance rate
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targetparameter
toxicokinetics
DEBtox basics
Change in target parameter affects endpoint– survival, reproduction, growth
food faeces
reserves
assimilation
food faeces
reserves
assimilation
structure
somatic maintenance
structure
somatic maintenance
maturityoffspring
maturity maintenance
1-
maturityoffspring
maturity maintenance
1-
DEB model
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Modes of Action
food faeces
reserves
structure maturityoffspring
maturity maint.somatic maint.
assimilation
1-
assimilation
maintenance costs
growth costs
reproduction costs
hazard to embryo
hazard (lethal effects)
tumour
tumour induction endocrine disruption
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Windows version
User-friendly software, freely downloadable
Only for standard tests– acute survival– Daphnia reproduction– fish growth– algal population growth
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Example: survival dieldrin
0.0 3.2 5.6 10 18 32 56 100
0 20 20 20 20 20 20 20 20
1 20 20 20 20 18 18 17 5
2 20 20 19 17 15 9 6 0
3 20 20 19 15 9 2 1 0
4 20 20 19 14 4 1 0 0
5 20 20 18 12 4 0 0 0
6 20 19 18 9 3 0 0 0
7 20 18 18 8 2 0 0 0
tim
e (d
)
concentration (µg/L)
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Example: survival dieldrin
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Example: survival dieldrin
NEC 5.2 (2.7-6.9) µg/LKilling rate 0.038 L/(µg d)Elim. rate 0.79 d-1
Blank haz. 0.0084 d-1
NEC 5.2 (2.7-6.9) µg/LKilling rate 0.038 L/(µg d)Elim. rate 0.79 d-1
Blank haz. 0.0084 d-1
0 d
1 d
2 d
3 d
4 d5 d6 d
7 d
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Example: survival nonylphenol
0 h 24 h 48 h
0.004 20 20 20
0.032 20 20 20
0.056 20 20 20
0.100 20 20 20
0.180 20 20 16
0.320 20 13 2
0.560 20 2 0
time
con
cen
trat
ion
(m
g/L
)
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Example: survival nonylphenol
24 hrs
48 hrs
0 hrs
NEC 0.14 (0.094-0.17) mg/LKilling rate 0.66 L/(mg h)Elim. rate 0.057 h-1
NEC 0.14 (0.094-0.17) mg/LKilling rate 0.66 L/(mg h)Elim. rate 0.057 h-1
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Example: survival nonylphenol
LC0
LC50
NEC
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Example: repro cadmium
Mode of action costs for repro
NEC 3.3e-9 (0-0.017) mMTolerance 4.7e-9 mMMax. repro 14 offspring/dElim. rate 2.6e-9 d-1
Mode of action costs for repro
NEC 3.3e-9 (0-0.017) mMTolerance 4.7e-9 mMMax. repro 14 offspring/dElim. rate 2.6e-9 d-1
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Example: repro cadmium
EC0 EC50
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Advantages DEBtox
Make efficient use of all data points– more accurate parameter estimates– reduce number of test animals …
More information obtained– ECx at any time point can be calculated– mode of action; crucial for population response
Characterisation of effects– time-independent NEC may replace NOEC and ECx
For the standard software
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Advanced examples
0 2 4 6 8 10 12 14 160
0.2
0.4
0.6
0.8
1
0 2 4 6 8 10 12 14 160
0.2
0.4
0.6
0.8
1
0 5 10 150
20
40
60
80
100
120
0 5 10 150
20
40
60
80
100
120 0 5 10 150.5
1
1.5
2
2.5
3
3.5
4
0 5 10 150.5
1
1.5
2
2.5
3
3.5
4
survival reproduction
body size
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DEBtox extensions
Simultaneous fits on more data sets– endpoints, chemicals, species …
Fit deviating experimental data– degradation, pulse exposure …
Extrapolations– time, food level, temperature, (species) …
At this moment only available as MatLab scripts
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Simultaneous fitsSurvival and body residues for cadmium (Heugens et al.)
0 10 20 30 40 500
5
10
15
20
25
30
time (hours)
inte
rna
lco
nc
en
tra
tio
n(m
g/k
g d
wt)
0 10 20 30 40 500
5
10
15
20
25
30
time (hours)
inte
rna
lco
nc
en
tra
tio
n(m
g/k
g d
wt)
0 20 40 60 80 1000
0.2
0.4
0.6
0.8
1
time (hours)
fra
cti
on
su
rviv
ing
0 20 40 60 80 1000
0.2
0.4
0.6
0.8
1
time (hours)
fra
cti
on
su
rviv
ing
0-0.56 mg/L
0.82 mg/L
1.1 mg/L
1.7 mg/L
2.2 mg/L
NEC on internal basis: 259 mg/kg dwt (202-321)NEC on internal basis: 259 mg/kg dwt (202-321)
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ExtrapolationFrom continuous exposure to a 20-hour pulse
0 20 40 60 80 1000
0.2
0.4
0.6
0.8
1
time (hours)
frac
tio
n s
urv
ivin
g
0 mg/L
3 mg/L
4 mg/L
5 mg/L
10 mg/L
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0
0.2
0.4
0.6
0.8
1
0
0.2
0.4
0.6
0.8
1
0 5 10 150
0.2
0.4
0.6
0.8
1
0 5 10 150
0.2
0.4
0.6
0.8
1
0 5 10 150 5 10 15 0 5 10 150 5 10 15
Azinophos-methyl
Malathion
Methidathion
Phentoate Phosmet
time (days)
frac
tio
n s
urv
ivin
g
simultaneous fitsSurvival for 5 OP esters (data De Bruijn & Hermens)
Same NEC, elim. rate, killing rate, receptor repair rateDifferent affinity for receptor
Same NEC, elim. rate, killing rate, receptor repair rateDifferent affinity for receptor
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simultaneous fits
0 2 4 6 8 10 12 14 160
0.2
0.4
0.6
0.8
1
survival
0 5 10 150
20
40
60
80
100
120
reproduction
0 5 10 150.5
1
1.5
2
2.5
3
3.5
4
0 5 10 150.5
1
1.5
2
2.5
3
3.5
4
body size
Mode of actiondecrease assimilation
Mode of actiondecrease assimilation
Reproduction test with cadmium (data Heugens et al.)
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Extrapolations
0 0.05 0.1 0.15 0.20
0.1
0.2
0.3
0.4
concentration
po
pu
lati
on
gro
wth
rat
e (1
/day
)
90% food
80% food
0 2 4 6 8 10 12 14 160
0.2
0.4
0.6
0.8
1
0 2 4 6 8 10 12 14 160
0.2
0.4
0.6
0.8
1
0 5 10 150
20
40
60
80
100
120
0 5 10 150
20
40
60
80
100
120
0 5 10 150.5
1
1.5
2
2.5
3
3.5
4
0 5 10 150.5
1
1.5
2
2.5
3
3.5
4
survival reproduction
body size
To populations and limiting food
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Simultaneous fits
0
1
2
3
4
0
1
2
3
4
0 5 10 15 200
1
2
3
4
0 5 10 15 200
1
2
3
4
0
10
20
30
40
50
60
70
0
10
20
30
40
50
60
70
0 5 10 15 200
10
20
30
40
50
60
70
0 5 10 15 200
10
20
30
40
50
60
700
0.2
0.4
0.6
0.8
1
0
0.2
0.4
0.6
0.8
1
0 5 10 15 200
0.2
0.4
0.6
0.8
1
0 5 10 15 200
0.2
0.4
0.6
0.8
1
Body length Cumulative offspring Fraction surviving
Hig
h f
oo
dL
ow
fo
od
Fenvalerate pulse at two food levels (data Pieters et al.)
Mode of action: assimilationNEC survival: 0.42 µg/LNEC growth/repro: 0.051 µg/L
Insights• intrinsic sensitivity independent of food• chemical effects fully reversible
Mode of action: assimilationNEC survival: 0.42 µg/LNEC growth/repro: 0.051 µg/L
Insights• intrinsic sensitivity independent of food• chemical effects fully reversible
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Opportunities 1:Relevant endpoint
concentration
po
pu
lati
on
gro
wth
rat
e
PEC
impact
• ecologically relevant• time independent• integrate endpoints• comparable between chemicals
NEC
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impact
PEC
Opportunities 1:Relevant endpoint
concentration
po
pu
lati
on
gro
wth
rat
e
PEC
impact
• ecologically relevant• time independent• integrate endpoints• comparable between chemicals
NEC
![Page 49: Process-based toxicity analysis in risk assessment Tjalling Jager Bas Kooijman Dept. Theoretical Biology.](https://reader036.fdocuments.net/reader036/viewer/2022062305/56649d4a5503460f94a26bcb/html5/thumbnails/49.jpg)
Opportunities 2:Match exposure scenario
timeex
po
sure
time
surv
ival
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Opportunities 3:Reduce testing needs?
Use all of the data points– more data points per parameter– less animals needed
Less need to discard ‘poor’ data– disappearance of test compound– change in body weight of test organism– combine low-quality data sets
Less need for new tests– better extrapolations from lab data– opportunities for QSAR development …
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Relations for alkyl benzenes
Daphnia pulex, elimination
1 mm juveniles
3 mm adults
Fathead minnows, NEC
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The DEB laboratory
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Electronic DEB laboratory
DEBtox– Windows version 2.0.1.– routine applications
DEBtool– open source (Octave, MatLab)– full range of DEB research (fundamental+applied) – also advanced DEBtox applications
Freely downloadable fromhttp://www.bio.vu.nl/thb/deb/deblab/
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Finally …
– exposure assessment is well ahead of effects assessment
– effects assessment will benefit from a process-based approach
• more scientific extrapolation• testing needs may be reduced
– but … requires major shift in thinking• basic methods are already available• toxicity data are already reported in time
In our opinion …
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More information
These slides are available at: http://www.bio.vu.nl/thb/users/bas/lectures/
Further reading (paper submitted): http://www.bio.vu.nl/thb/research/bib/
JageHeug2005.html
Further literature: http://www.bio.vu.nl/thb/research/bib