process-based toxicity analysis in risk assessment tjalling jager bas kooijman dept. theoretical...

Process-based toxicity analysisin risk assessment

Tjalling Jager

Bas Kooijman

Dept. Theoretical Biology

Contents

Dynamic Energy Budget (DEB) theory Current procedures in (eco)tox Introduction to DEBtox Advanced examples The DEB laboratory

Why DEB theory?

How do individuals acquire and allocate their resources?

Relation DEB and toxicants

??

Relation DEB and toxicants

??

Relation DEB and toxicants

??

Dynamic Energy Budgets

food faeces

reserves

structure

maturity maint.somatic maint.

assimilation

1-

maturityoffspring

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 …

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/

Current procedures in (eco)tox

EC50EC50

Re

sp

on

se

log concentration

“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

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

Contr.

Standard approaches

NOEC

Res

po

nse

log concentration

LOEC

*

1. Statistical testing

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!

Standard approaches

EC50

Res

po

nse

log concentration

1. Statistical testing2. Curve fitting

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

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

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

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

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 …

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

Introduction to DEBtox

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

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

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

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

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

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

Windows version

User-friendly software, freely downloadable

Only for standard tests– acute survival– Daphnia reproduction– fish growth– algal population growth

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)

Example: survival dieldrin

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

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

)

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

Example: survival nonylphenol

LC0

LC50

NEC

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

Example: repro cadmium

EC0 EC50

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

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

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

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)

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

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

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.)

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

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

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

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

Opportunities 2:Match exposure scenario

timeex

po

sure

time

surv

ival

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 …

Relations for alkyl benzenes

Daphnia pulex, elimination

1 mm juveniles

3 mm adults

Fathead minnows, NEC

The DEB laboratory

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/

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 …

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