Transcript Perspectives on Environmental Assessments of Chemicals Used in Consumer Products Bryan W. Brooks Professor and Director Department of Environmental Science Center for Reservoir and Aquatic Systems.

Perspectives on Environmental
Assessments of Chemicals Used in
Consumer Products
Bryan W. Brooks
Professor and Director
Department of Environmental Science
Center for Reservoir and Aquatic Systems Research
Institute of Biomedical Studies
Assessment of Environmental Effects
Environmental safety studies generally have a two-fold purpose:
1. Determine whether a chemical produces an effect on
a biological system
2. Determine how much of an effect is present
Single species laboratory toxicity tests, microcosms/mesocosms,
and field studies are often used to determine thresholds
at individual, population or community levels
Assessment of Environmental Effects:
Prospective and Retrospective
• New product safety assessments and environmental quality
criteria derivation rely on similar model organisms with survival,
growth and reproduction endpoints
• Effluent water quality evaluated by whole effluent toxicity tests
+
www.cefas.co.uk
algae
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www.cefas.co.uk
Daphnia
fish
What is More Toxic, What is Safer?
Hodge and Sterner 1949
De Wolf et al. 2005
log KOW
“Read-Across” approaches are often explored for
comparative and relative toxicology studies
Acute Toxicity
Uncertainty
described
High
accuracy
Realistic
(predictive)
6
Uncertainty
unknown
5
4.
4
- Cosm/
Chronic SSD
3.
2.
2
Acute
1.
1
Chronic
Low
accuracy
Conservative
(protective)
3
QSAR
1
Simple
(data poor)
2
3
4
5
6
Complex
(data rich)
Ecological Risk Assessment
Prospective and Retrospective
Problem Formulation
Exposure
RISK
Effects
Risk Characterization
Risk Management
Deterministic Approach:
[Exposure] / [Effect] > 1
Weight of Evidence
Uncertainty
Texas Water Resources
www.tpwd.state.tx.us
Texas Water Resources
www.seco.cpa.state.tx.us
Texas Water Resources
Texas Water Resources
Wastewater treatment
Five primary types: activated sludge, oxidation ditch,
trickling filter, lagoon, rotating biological contactor
Uncertainties in ERAs of Consumer Products
1. Ionization and pH
West Texas River
Brazos
Dry climate
Little vegetation
Watershed
HighHigher
surface
water pH
salinity
Higher surface water pH
Generally, higher pH
East Texas
Different geomorph
Wetter climat
Greater vegetat
Lower pH
pH Matters: In Streams, In the Lab
Uncertainties in ERAs of Consumer Products
1. Ionization and pH
Fish Uptake of Diphenhydramine
(pKa = 8.9) from Water to Plasma
Relationship between pH and
DO, Lake Conroe, Texas
9.8
600
9.6
Concentration (mg/kg)
500
9.4
pH
pH 7.7
pH 8.7
9.2
9.0
400
300
200
100
8.8
2
R = 0.782; p < 0.0001
8.6
6
8
10
12
Dissolved Oxygen (mg/L)
Brooks et al 2012
14
16
0
0
20
40
60
80
100
Time (hour)
Du et al. in prep
Uncertainties in ERAs of Consumer Products
100
Survivorship (%)
1. Ionization and pH
80
60
40
pH 6.5
20
pH 7.5
Fluoxetine (pKa = 10.1)
pH 8.5
↑ nonionized, ↑ BCF
0
10
20
30
40
Acute
TImeresults
(h)
log LC50 value
1000
100
y  0.47 x  5.91
r 2  0.97
10
6
Growth
results
7
8
9
pH
1000
log EC10 value
Nakamura et al. (2008)
Sertraline (pKa = 9.4)
0
100
y  0.52 x  6.1
r 2  0.99
10
6
7
8
pH
Valenti et al. 2009. ET&C
9
Uncertainties in ERAs of Consumer Products
2. Nutrient stoichiometry and concentrations affect toxicity
N & P range in standard Lemna media:
N (mg L-1) P (mg L-1) Molar N:P
Medium
A
Hoagland
280
155
4
Hutner B
127
93
3
Steinberg C
84
46
8
20X-AAP D
84
3.7
50
E
SIS
14
2.4
13
A
ASTM, B Brain & Solomon, C Mkandawire and
Dudel, D EPA, E OECD
N and P conditions variable, dissimilar from surface waters
Uncertainties in ERAs of Consumer Products
2. Nutrient influences on triclosan toxicity
Fulton et al. 2009. ET&C
Uncertainties in ERAs of Consumer Products
2. Nutrient influences on triclosan toxicity
Day 7
Fulton et al. 2009. ET&C
Day 14
Uncertainties in ERAs of Consumer Products
3. Chirality
Enantiomers can significantly differ in:
• Biodegradation
• Selectivity for receptors, transporters, and/or enzymes
• Type of effect(s)
• Potency
• Rate of metabolism & structure of metabolites
• Rate of uptake and excretion
Introduces Uncertainty in…
EXPOSURE & TOXICITY
Comparative Toxicology and Chirality
Feeding rate EC10
R-fluoxetine 16.1µg/L
S-fluoxetine 3.7 µg/L
S-fluoxetine
R-fluoxetine
5-HT
NPY
Feeding
Growth
Stanley et al 2007 Chemosphere
Growth EC10
R-fluoxetine 132.9 µg/L
S-fluoxetine 14.1 µg/L
Comparative Toxicology and Chirality
Enantiomer-Specific Metabolism Differs from Racemate
0.0
log Concentration (umol/L)
-0.2
Intrinsic Clearance Rates
(mL/hr/mg)
-0.4
-0.6
-0.8
Rac-Propranolol
R-Propranolol
S-Propranolol
-1.0
-1.2
-1.4
2.89
0.66
1.91
rac-Propranolol
S-Propranolol
R-Propranolol
-1.6
0
10
20
30
40
50
60
70
Time (min)
Rainbow trouth model: S9 substrate depletion kinetics
Connors et al. In prep.
Proposed Chiral ERA Decision Tree
Stanley and Brooks. 2009. IEAM
Model Organism and MOA Matters
Uncertainties in ERAs of Consumer Products
4. Mode of Action
Multigenerational Daphnia magna
Responses to 17α-ethinylestradiol
Mean Ecdysone (pg organism-1)
40
F0
F1
30
20
10
0
0
62.5
125
0.8
250
500 1000
[EE2] (g L-1)
F0
F1
50
Normalized Mean Vitellin
(µg organism-1)
Intrinsic Rate of Population Growth
1.0
0.6
0.4
0.2
F0
F1
40
*
30
20
10
0.0
0
62.5
125
250
[EE2] (g L-1)
500 1000
0
0
62.5
125
250
[EE2] (g L-1)
Clubbs & Brooks 2007. EES
500 1000
But High Potency in Fish….
The 17α-ethinylestradiol Example
Kidd et al. 2007. PNAS USA
“Intelligent” Toxicology
Bradbury, Feijtel, van Leeuwen. 2004. ES&T
“Intelligent” Ecotoxicology?
Ankley et al. 2010 ET&C
Some General Research Questions
1. How can hazard be estimated for compounds
with limited exposure data?
2. How does one select a model for a specific
endpoint or chemical class when multiple
models exist?
3. Which chemicals may required future studies
of acute and chronic hazards?
More Efficient Risk Assessment?
Bradbury, Feijtel, van Leeuwen. 2004. ES&T
Thresholds of Toxicological Concern
• Historically applied to food additives
• Oral route only; applications to other routes
of exposure may require additional effort
• 1.5 g/person/day considered safe
• Some exceptions (e.g., genotoxic carcinogens)
• Several previous approaches to TTC
• Broad spectrum
• Structurally based
Kroes et al. 2005. Toxicological Sciences
Aquatic Exposure Thresholds of No Concern?
“….no evidence suggests that an ETNCaq,MOA1–3 of 0.1 μg/L is an unacceptable
value.”
De Wolf et al. 2005. ETC
Probabilistic Hazard Assessment
A Chemical Toxicity Distribution
99.99
Criterion concentration or
predicted environmental
concentration (PEC)
Percent rank
99.9
Probability of
finding a
compound ≤
the criterion
concentration
value or PEC
99
90
70
50
30
10
Chemical toxicity distribution (CTD)
5th centile
1st centile
0.1
0.01
0.1
1
10
100
1000
10000
Concentration (log scale)
Toxicological benchmark
concentration (TBC)
Predicting Toxicity for a Broad Group
99.99
99.9
99
Fam
Percent Rank
90
70
50
30
Ib
fish ( ) r2 = 0.96
Ery
Ery
Pr Cl
Flu
Ib
Wa
Cl
EE Pr
Flu
10
Fam
EE
rat ( ) r2 = 0.92
1
Wa
0.1
0.01
0.001
10-3
10-2
10-1
100
101
102
103
104
105
Acute Toxicity
(Rat LD50 mg/kg) (Fish LC50 mg/L)
- Only 5% of drugs predicted to be toxic to fish below
0.84 mg/L and rodents below 33.5 mg/kg
Berninger and Brooks. 2010. Toxicol Lett
Predicting Toxicity for a Narrower Group
- Only 5% of surfactants predicted to be acutely toxic
to Daphnia magna below 0.354 mg/L
Williams, Berninger and Brooks. 2011. ETC
Predicting Toxicity for a Specific Class
Parabens: Antimicrobial Agents
- Only 5% of parabens predicted to
adversely affect fish survival and
growth below 0.74 μg/L and 0.37
μg/L, respectively
Dobbins et al. 2009. ETC
Predicting Toxicity for a Specific Class
Paraben Acute Toxicity MOA: Narcosis?
2.2
Methylparaben
(log P = 1.87)
Fathead Minnow
Daphnia magna
2.0
log mean LC50 (mg L-1)
1.8
R2 = 0.99
1.6
1.4
R2 = 0.88
1.2
1.0
Benzylparaben
(log P = 3.64)
0.8
0.6
0.4
1.6
1.8
2.0
2.2
2.4
2.6
log P
Dobbins et al. 2009. ETC
2.8
3.0
3.2
3.4
3.6
Predicting Toxicity for a Specific MOA
Acute Toxicity of Acetylcholinesterase Inhibitors
- Only 5% of AChEIs predicted to be acutely toxic to Daphnia
magna and Pimephales promelas below 0.188 μg/L and 65.07
μg/L, respectively
Williams, Berninger and Brooks. 2011. ETC
Using Probabilistic Hazard Approaches to
Prioritize Chemical Safety Studies:
Application to REACH
Williams, Berninger and Brooks. 2011. ETC
Current Challenge: Lack of Safety Data
• Lack of safety information for many
chemicals
• Current approach is retrospective
• Can we take prospective approaches?
Principles of Green Chemistry
9. Use catalysts
Warner, J.; Anastas, P. Green Chemistry: Theory and Practice, 1993.
Green Chemistry Principle #4
Chemical products should be designed to
preserve efficacy of function while reducing
toxicity and other environmental hazards.
Chemistry &
Engineering
Toxicology &
Biochemistry
Ecology &
Env. Science
Warner, J.; Anastas, P. Green Chemistry: Theory and Practice, 1993.
Sustainable Molecular Design Guidelines?
Design Guidelines for Reduced Aquatic Toxicity:
Standardized Responses
• 70-80% of the compounds that have low acute aquatic
toxicity have a defined range of values for octanol-water
partition coefficient, logPo/w, and ΔE (LUMO-HOMO
energy).
• Compounds with logPo/w values < 2 and ΔE > 9 eV are
significantly more likely to have low acute aquatic
toxicity
• These design guidelines closely extend to standardized
aquatic chronic/subchronic effects.
Voutchkova et al 2011, 2012 Green Chem
What if we employed sustainable molecular
design for commodity chemicals?
1) What might be the likelihood of encountering industrial
chemicals exceeding established US EPA toxicological
categories of concern?
2) What could be the likelihood of exceeding these
toxicological categories if chemical design guidelines
were followed in the future?
Design Guidelines for Reduced Acute
Aquatic Toxicity
Fathead minnow
P. promelas
LC50, 96-h assay
Japanese medaka
O. latipes
LC50, 96-h assay
Daphnia magna
671 chemicals
285 chemicals
363 chemicals
EC50, 48-h assay
Green algae
P. subcapitata
EC50, 72-h
4 categories based on EPA toxicological categories
LC50/EC50:
0–1
mg/L
LC50/EC50:
1 – 100
mg/L
LC50/EC50:
100 – 500
mg/L
Voutchkova 2011 Green Chem.; Russom 1997 ETC; Japan Ministry of Environment
LC50/EC50:
> 500 mg/L
300 chemicals
What might be the likelihood of encountering
industrial chemicals exceeding established US
EPA toxicological categories?
All chemicals
Percent Rank
99.9
99.8
99
98
95
90
80
70
14.5
55.1
14.4
16
50
30
20
10
5
2
1
0.5
0.2
0.1
10-5 10-4 10-3 10-2 10-1 100
All
dE
log P
Both
101
102
103
104
P. promelas 96 hr. LC50 mg/L
All chemicals (n=570)
105
106
High: 0-1 mg/L
Moderate 1-100 mg/L
Low 100-500 mg/L
None >500 mg/L
What could be the likelihood of exceeding these
toxicological categories if chemical design
guidelines were followed in the future?
All chemicals
Percent Rank
99.9
99.8
99
98
95
90
80
70
14.5
55.1
14.4
16
50
30
20
10
5
2
1
0.5
0.2
0.1
10-5 10-4 10-3 10-2 10-1 100
All
dE
log P
Both
101
102
103
104
P. promelas 96 hr. LC50 mg/L
Chemicals with dE above 9 eV (n=408)
105
106
High: 0-1 mg/L
Moderate 1-100 mg/L
Low 100-500 mg/L
None >500 mg/L
What could be the likelihood of exceeding these
toxicological categories if chemical design
guidelines were followed in the future?
All chemicals
Percent Rank
99.9
99.8
99
98
95
90
80
70
14.5
55.1
14.4
16
50
30
20
10
5
2
1
0.5
0.2
0.1
10-5 10-4 10-3 10-2 10-1 100
All
dE
log P
Both
101
102
103
104
P. promelas 96 hr. LC50 mg/L
Chemicals with logP below 2 (n=299)
105
106
High: 0-1 mg/L
Moderate 1-100 mg/L
Low 100-500 mg/L
None >500 mg/L
What could be the likelihood of exceeding these
toxicological categories if chemical design
guidelines were followed in the future?
All chemicals
Percent Rank
99.9
99.8
99
98
95
90
80
70
14.5
55.1
14.4
16
Following guidelines
50
30
20
10
5
2
1
0.5
0.2
0.1
10-5 10-4 10-3 10-2 10-1 100
42.7
All
dE
log P
Both
101
102
103
104
P. promelas 96 hr. LC50 mg/L
Chemicals with both dE above 9 and
logP below 2 (n=233)
105
23.4
106
3.3 %
30.6
High: 0-1 mg/L
Moderate 1-100 mg/L
Low 100-500 mg/L
None >500 mg/L
Extends to other models…
99
98
95
90
80
70
99.9
99.8
P. promelas
Percent Rank
Percent Rank
99.9
99.8
50
30
20
10
5
2
1
0.5
0.2
0.1
10-5 10-4 10-3 10-2 10-1 100
All
log P
dE
Both
101
102
103
104
105
106
99
98
95
90
80
70
O. latipes
50
30
20
10
5
2
1
0.5
0.2
0.1
10-5
10-4
10-3
10-2
D. magna
Percent Rank
Percent Rank
99.9
99.8
50
30
20
10
5
2
1
0.5
0.2
0.1
10-5
10-4
10-3
10-2
10-1
100
EC50 mg/L
100
101
102
103
104
101
102
103
104
LC50 mg/L
LC50 mg/L
99.9
99.8
99
98
95
90
80
70
10-1
101
102
103
104
99
98
95
90
80
70
P. subcapitata
50
30
20
10
5
2
1
0.5
0.2
0.1
10-5
10-4
10-3
10-2
10-1
100
EC50 mg/L
Projected Reduction in Chemicals Falling in
High Toxicity Category?
• Acute
– 11.2-20.7% reduction in chemicals classified as
“high” acute toxicity
– Guidelines are more successful at reducing
toxicity in Daphnia than fish species (4.5-9.5%)
Ongoing Research
– Exploring additional guidelines to understand
chemicals remaining in “high” toxicity category
– Working to identify sustainable molecular
design guidelines for specific MOAs, or other
model organisms and responses
– Further examine utility of these guidelines
may be possible as additional toxicity data
becomes available (e.g., REACH)
Some Parting Thoughts….
- Define toxicological endpoints, models well
- Ionization, Chirality, Nutrients = Uncertainty
- A priori understanding of MOA; AOPs
- Sustainable molecular design = prospective
- Probabilistic hazard assessment can support
prioritization, sustainable design and
read-across approaches
Thank You