Download Extrapolating to time-varying exposure using biology

Extrapolating to time-varying
exposure …
using biology-based modelling
Tjalling Jager
Dept. Theoretical Biology
Problem of extrapolation
Protection goal
Available data
• different exposure time
• different temperature
• different species
• time-varying exposure
• species interactions
• populations
• other stresses
• mixture toxicity
•…
Time-varying exposure
Scientifically interesting
 response of growth, reproduction and
survival?
 reversibility of effects?
 how does this translate to population
impact and recovery?
Specifically relevant for risk assessment
 accidental spills
 plant-protection products
 industrial chemicals; ‘intermittent release’
Fate modelling
pesticide fate modelling
oil-spill modelling
Effects modelling?
 NOEC and ECx cannot complement fate models
• purely descriptive statistics
• only valid for particular test duration and endpoint
• only defined for constant exposure
 Impossible to experimentally test each scenario …
Biology-based modelling
Explicit assumptions about processes
chemicals must be taken up to be toxic
internal
concentration
in time
external
concentration
in time
toxicokinetics
extensively studied
toxicodynamics
less popular …
effects on
life history
in time
Effects on reproduction
Effects on reproduction
Effects on reproduction
Effects on reproduction
Sub-lethal effects
 Understanding growth and reproduction requires
understanding resource allocation
 Dynamic Energy Budget (DEB) theory specifies
allocation rules
• focus of dept. Theoretical Biology
DEBtox
TK model
• one-compartment model
• account for growth
toxicokinetics
external
concentration
Target
• energy-budget parameter
• threshold for effects: NEC
internaltarget
concentration
over time
parameter
Animal model
• simplified DEB model
animal model
survival/growth/repro
Kooijman & Bedaux (1996), Jager et al. (2006)
body length
cumulative offspring
Target: maintenance
time
Jager et al. (2004)
triphenyltin
time
body length
cumulative offspring
Target: costs for growth
time
Alda Álvarez et al. (2006)
pentachlorobenzene
time
DEBtox
 Well-tested for constant exposure
toxicokinetics
 Recognition in regulatory context
• included in ISO/OECD guidance
• workshop at JRC/ECB Ispra
internaltarget
concentration
over time
parameter
 Embedded in (inter)national science
• e.g., participation in EU projects
NoMiracle and ModelKey
 Applicable to time-varying
exposure?
animal model
survival/growth/repro
Time-varying exposure
toxicokinetics
environ. conc.
time
target
parameter
animal model
toxicokinetics
target
parameter
animal model
Assumption
toxicokinetics follows first-order, one-comp. model
environ. conc.
internal conc.
time
time
toxicokinetics
target
parameter
animal model
Assumption
effects on energetic processes are reversible
blank value
environ. conc.
assimilation eff.
internal conc.
NEC
time
time
toxicokinetics
target
parameter
animal model
cumul. reproduction
body length
time
time
blank value
assimilation eff.
time
Experimental validation
Pieters et al. (2006)
•
•
•
•
Daphnia magna and fenvalerate
modified 21-day reproduction test
pulse exposure for 24 hours
two food levels (relative food level is
parameter in DEB)
Pulse exposure
Body length
Cumulative offspring
Fraction surviving
70
1
High food
4
60
0.8
50
3
40
2
0.6
30
‘assimilation’
5
6
mode of action:
20
phys. parameters:
10
tox. parameters:
0
1
0
0.4
0.2
0
Low food
70
4
Insights
3
• tox. parameters
independent of food
50
• chemical effects
fully reversible
40
2
1
60
0.8
0.6
30
0.4
20
1
0.2
10
0
0
5
10
15
20
0
0
5
10
15
20
0
0
5
10
15
20
Population approaches
Effects on individual budgets forms basis of
population response
 Intrinsic rate of increase
• only for exponential growth in constant environment
 Leslie-matrix model
• classes characterised by one state variable (size or age)
 Cohort-based (e.g., escalator-boxcar train)
• cohorts can be specified by many state variables
• dynamically follow food concentration
Cohort based, fenvalerate
High food
10
Limiting food
6
10
4
juveniles
adults
10
5
10
10
4
10
10
10
10
3
2
3
10
2
1
0
5
10
time
15
20
Jager et al., 2007 (RIVM report)
25
10
1
0
0
5
10
15
time
20
25
30
35
Concluding remarks
Time-varying exposure of populations is highly
relevant
• both from scientific and regulatory perspective
DEBtox provides natural modelling framework
• covers both lethal and sub-lethal effects
• no fundamental obstacles for time-variable exposure
Individual budgets as basis for population response
• one of pillars of DEB theory
• cohort-based approaches look promising
Project structure
based on DEBtox, coding MatLab
Model development
Lab experiments
support from BASF AG
food? predation?
migration?
Population framework
reversibility?
multiple pulses?
Data analysis
cohort-based
Population predictions
Extrapolation
Model development
Lab experiments
Data analysis
Population framework
Population predictions
www.bio.vu.nl/thb