Office of Research and Development

Building Knowledgebases and 

Decision Support Tools

Presentation to the FIFRA Scientific Advisory Panel

May 24, 2011

Pat Schmieder

EPA, ORD, NHEERL,

Mid-Continent Ecology Division,

Duluth, MN
Office of Research and Development

Decision Support Systems

A decision support system (DSS) is a computerbased information system that supports 

organizational decision-making activities. DSSs 

include knowledge-based systems and expert 

systems. 
Office of Research and Development

Knowledge-base

A knowledge-base is a special kind of database

for knowledge management, providing the means 

for the computerized collection, organization, and 

retrieval of knowledge. Knowledge-bases are 

more than databases because they are designed 

to help analyze information.
Office of Research and Development

Expert System

An expert system uses a knowledge-base of 

human expertise for problem solving & supporting 

decision making, or to clarify uncertainties where 

normally one or more human experts would need 

to be consulted. Rules developed by experts can 

be codified into logic trees that display the 

decision points in the expert system. 
Office of Research and Development

Benefits of Decision Support Systems 

(DSS)

• Improves personal efficiency

• Speed up the process of decision making

• Increases organizational control/consistency

• Encourages exploration and discovery on the part 

of the decision maker

• Speeds up problem solving in an organization 

• Facilitates interpersonal communication

• Promotes learning or training

• Generates new evidence in support of a decision

• Reveals new approaches to thinking about the 

problem space 

• Helps automate managerial processes
Office of Research and Development

KB/DSS components:

• Inputs: Factors, data and characteristics, 

to analyze

• User Knowledge and Expertise: Inputs 

requiring manual analysis by the user

• Outputs: Transformed/analyzed data from 

which DSS "decisions" are generated

• Decisions: Results generated by the DSS 

based on user criteria
Office of Research and Development

Knowledge-bases, Expert Systems

ECOTOX

ACToR

ToxRefDB

ToxCastDB

DSSTox

ExpoCast

Effectopedia

ER Expert System

MetaPath
ECOTOX

• Is a comprehensive, publicly-available on-line database, which provides EPA 

with a single source of open literature information for ecological effects data 

for aquatic and terrestrial organisms. 

• Includes test results published in the open literature, and from other 

government data sources

from: 35,723 publications; 7 electronic data files (EPA, USGS, OECD, Russia)

• All pertinent information on the species, chemical, test methods, and results 

are abstracted and encoded into the database

9,562 chemicals; 9,731 species; 765,032 individual test results

• Maintained with a high level of quality assurance and extensive 

documentation. Continually improved in accessibility and usefulness and 

regularly updated.

• Publicly available on Internet (www.epa.gov/ecotox)

• Developed and maintained by EPA/ORD/NHEERL/MED

• ECOTOX is internationally recognized as the source for ecotoxicological data

ECOTOX Uses within OPP

• Used to reduce ESA vulnerability

• Complies with an agreement between EPA and the US Fish and Wildlife Service and the 

National Marine Fisheries Service that EPA’s use of ECOTOX complies with the Endangered 

Species Act requirement that Federal agencies use best available information in conducting 

analyses for threatened and endangered species

• Assists scientists in screening open-literature in an efficient/consistent 

manner.

– Serves as the source for searching open literature data by providing an extensive source of 

open literature data. Includes literature available to the public as well as the literature in the 

queue to be coded for the public. 

– Applies the acceptance criteria described in OPP’s guidance for study selection.

– Provides standardized summary of the effects data that pass the acceptance criteria screen.

– Includes bibliographic file for rejected studies and a file for all studies.

• May supplement the standard effects studies required under FIFRA 

regulations (i.e., expanding the number of species tested).

• May reduce the uncertainties associated with the registrant-submitted toxicity 

data.

• Use of ECOTOX ensures consistency and transparency in assessment process. 
ACToR

Aggregated Computational Toxicology Resource

• Collaboration across EPA (ORD, OPP, OPPT, OW, GLNPO, EDSP)

• Compile all publicly available information on environmental chemicals

– One-stop shop – over 600 individual data sources, 500,000 chemicals

– Make previously hard-to-access data transparent (e.g. from OPP)

• Make data available for downloading, data mining

– Available through data.gov

– Entire DB can be downloaded and installed locally

• Make it easy to see data gaps

– Provides resource for EPA testing programs

• Make it widely used

– over 2000 regular users

http://actor.epa.gov
DSSTox

Distributed Structure-Searchable Toxicity Database Network

ToxRefDB

ACToR

ToxCast ExpoCast

Chemical Structure Annotation

Chemical Management

Chemical QC

DSSTox

http://www.epa.gov/ncct/dsstox
ToxRefDB

Capturing OPP Guideline Animal Study Data

STUDY TYPE: Combined chronic toxicity/oncogenicity feeding – Rat OPPTS 870.4300 [§83-5] DP BARCODE: D257223 SUBMISSION CODE: S564270 P.C. CODE: 111901 TOX. CHEM. NO.: 497AB

TEST MATERIAL (PURITY): Imazalil (purity 97.4%) CITATION: Van Deun, K. 1999. Combined oral chronic toxicity/carcinogenicity study with Imazalil in the SPF Wistar rat. Dept. Toxicology, Janssen Research Foundation, 2340 Beerse, Belgium. Laboratory report number, 3817, June 8, 1999. MRID 44858001. Unpublished. EXECUTIVE SUMMARY:

In a chronic toxicity/oncogenicity study (MRID 44858001), Imazalil (97.4% a.i.) was administered in the diet to groups of 50 male and 50 female Hannover substrain (SPF) Wistar-derived rats at concentrations of 0, 50, 200, 1200, or 2400 ppm (equivalent to 0.0, 2.7, 10.8, 65.8, and 134.8 mg/kg/day for males and 0.0, 3.6, 14.6, 85.2, and 168.8 mg/kg/day for females) for two years. All rats were observed daily for clinical signs of toxicity and morbidity, weighed weekly, and food consumption monitored biweekly. Blood and urine samples were collected after 6, 12, and 18 months of treatment and at study end. Surviving rats were sacrificed after 104 weeks of treatment. All rats were necropsied and the tissues and organs inspected grossly and microscopically for toxicity-related effects and 

the carcinogenic potential of Imazalil. Male and female rats in the 1200 ppm and 2400 ppm groups had slightly increased RBCs and slightly decreased MCVs and MCHs that reached statistical significance at most measurement intervals. The differences, however, were within 6% of controls and the historical control limits for rats of this age, sex, and species. No significant treatment-related effects of biological relevance were found for most clinical chemistry parameters. However, plasma triglyceride and the activities of ALKP, AST, and ALT of male rats in the 2400 ppm group and female rats in the 1200 and 2400 ppm groups were often statistically decreased but remained within historical control limits. The effects were considered related to malnutrition. The effect of treatment on the liver (males and females) and thyroid (males only) were confirmed microscopically, but had distinct sex-related etiologies. The 

incidence of clear cell and basophilic foci was equivocal while eosinophilic foci were significantly increased for male rats in the 2400 ppm group. In female rats of 

the 2400 ppm group, the incidences of clear cell and basophilic foci were significantly decreased but the incidence of eosinophilic foci was unaffected. Also, the 

incidence of hepatocyte fatty vacuolation was increased only in male rats of the 1200 ppm and 2400 ppm groups while the incidence of pigmentation was 

increased only in females of the 200, 1200, and 2400 ppm groups. In addition, the location of hepatocellular hypertrophy was distinctly different. Female rats in 

the 1200 and 2400 ppm groups had significant increases in centriacinar and periacinar hypertrophy while male rats only had centriacinar hypertrophy. Finally, 

the incidence of thyroid follicular cell hyperplasia was increased only in male rats of the 1200 and 2400 ppm groups. The lowest observed adverse effect level (LOAEL) for male and female rats was 1200 ppm (65.8 and 85.2 mg/kg/day, respectively) with a corresponding no observed adverse effect level (NOAEL) of 200 ppm (10.8 mg/kg/day males, 14.6 mg/kg/day females). These are based on the effects found on body weight, weight gain, and the macro- and microscopic effects noted in the liver of all rats and the thyroid of male rats. Male rats had a significant increase in the incidence of hepatocellular adenomas and thyroid follicular neoplasia while no increase was found for female rats. These results indicate a difference in the disposition of Imazalil between the sexes increases hepatic and thyroid neoplasia in male rats, likely through differences 

in metabolic activation of the test material.

STUDY TYPE: Combined chronic toxicity/oncogenicity feeding – Rat OPPTS 870.4300 [§83-5] DP BARCODE: D257223 SUBMISSION CODE: S564270 P.C. CODE: 111901 TOX. CHEM. NO.: 497AB

TEST MATERIAL (PURITY): Imazalil (purity 97.4%) CITATION: Van Deun, K. 1999. Combined oral chronic toxicity/carcinogenicity study with Imazalil in the SPF Wistar rat. Dept. Toxicology, Janssen Research Foundation, 2340 Beerse, Belgium. Laboratory report number, 3817, June 8, 1999. MRID 44858001. Unpublished. EXECUTIVE SUMMARY:

In a chronic toxicity/oncogenicity study (MRID 44858001), Imazalil (97.4% a.i.) was administered in the diet to groups of 50 male and 50 female Hannover substrain (SPF) Wistar-derived rats at concentrations of 0, 50, 200, 1200, or 2400 ppm (equivalent to 0.0, 2.7, 10.8, 65.8, and 134.8 mg/kg/day for males and 0.0, 3.6, 14.6, 85.2, and 168.8 mg/kg/day for females) for two years. All rats were observed daily for clinical signs of toxicity and morbidity, weighed weekly, and food consumption monitored biweekly. Blood and urine samples were collected after 6, 12, and 18 months of treatment and at study end. Surviving rats were sacrificed after 104 weeks of treatment. All rats were necropsied and the tissues and organs inspected grossly and microscopically for toxicity-related effects and 

the carcinogenic potential of Imazalil. Male and female rats in the 1200 ppm and 2400 ppm groups had slightly increased RBCs and slightly decreased MCVs and MCHs that reached statistical significance at most measurement intervals. The differences, however, were within 6% of controls and the historical control limits for rats of this age, sex, and species. No significant treatment-related effects of biological relevance were found for most clinical chemistry parameters. However, plasma triglyceride and the activities of ALKP, AST, and ALT of male rats in the 2400 ppm group and female rats in the 1200 and 2400 ppm groups were often statistically decreased but remained within historical control limits. The effects were considered related to malnutrition. The effect of treatment on the liver (males and females) and thyroid (males only) were confirmed microscopically, but had distinct sex-related etiologies. The 

incidence of clear cell and basophilic foci was equivocal while eosinophilic foci were significantly increased for male rats in the 2400 ppm group. In female rats of 

the 2400 ppm group, the incidences of clear cell and basophilic foci were significantly decreased but the incidence of eosinophilic foci was unaffected. Also, the 

incidence of hepatocyte fatty vacuolation was increased only in male rats of the 1200 ppm and 2400 ppm groups while the incidence of pigmentation was 

increased only in females of the 200, 1200, and 2400 ppm groups. In addition, the location of hepatocellular hypertrophy was distinctly different. Female rats in 

the 1200 and 2400 ppm groups had significant increases in centriacinar and periacinar hypertrophy while male rats only had centriacinar hypertrophy. Finally, 

the incidence of thyroid follicular cell hyperplasia was increased only in male rats of the 1200 and 2400 ppm groups. The lowest observed adverse effect level (LOAEL) for male and female rats was 1200 ppm (65.8 and 85.2 mg/kg/day, respectively) with a corresponding no observed adverse effect level (NOAEL) of 200 ppm (10.8 mg/kg/day males, 14.6 mg/kg/day females). These are based on the effects found on body weight, weight gain, and the macro- and microscopic effects noted in the liver of all rats and the thyroid of male rats. Male rats had a significant increase in the incidence of hepatocellular adenomas and thyroid follicular neoplasia while no increase was found for female rats. These results indicate a difference in the disposition of Imazalil between the sexes increases hepatic and thyroid neoplasia in male rats, likely through differences 

in metabolic activation of the test material.

STUDY TYPE: Combined chronic toxicity/oncogenicity feeding – Rat OPPTS 870.4300 [§83-5] DP BARCODE: D257223 SUBMISSION CODE: S564270 P.C. CODE: 111901 TOX. CHEM. NO.: 497AB

TEST MATERIAL (PURITY): Imazalil (purity 97.4%) CITATION: Van Deun, K. 1999. Combined oral chronic toxicity/carcinogenicity study with Imazalil in the SPF Wistar rat. Dept. Toxicology, Janssen Research Foundation, 2340 Beerse, Belgium. Laboratory report number, 3817, June 8, 1999. MRID 44858001. Unpublished. EXECUTIVE SUMMARY:

In a chronic toxicity/oncogenicity study (MRID 44858001), Imazalil (97.4% a.i.) was administered in the diet to groups of 50 male and 50 female Hannover substrain (SPF) Wistar-derived rats at concentrations of 0, 50, 200, 1200, or 2400 ppm (equivalent to 0.0, 2.7, 10.8, 65.8, and 134.8 mg/kg/day for males and 0.0, 3.6, 14.6, 85.2, and 168.8 mg/kg/day for females) for two years. All rats were observed daily for clinical signs of toxicity and morbidity, weighed weekly, and food consumption monitored biweekly. Blood and urine samples were collected after 6, 12, and 18 months of treatment and at study end. Surviving rats were sacrificed after 104 weeks of treatment. All rats were necropsied and the tissues and organs inspected grossly and microscopically for toxicity-related effects and 

the carcinogenic potential of Imazalil. Male and female rats in the 1200 ppm and 2400 ppm groups had slightly increased RBCs and slightly decreased MCVs and MCHs that reached statistical significance at most measurement intervals. The differences, however, were within 6% of controls and the historical control limits for rats of this age, sex, and species. No significant treatment-related effects of biological relevance were found for most clinical chemistry parameters. However, plasma triglyceride and the activities of ALKP, AST, and ALT of male rats in the 2400 ppm group and female rats in the 1200 and 2400 ppm groups were often statistically decreased but remained within historical control limits. The effects were considered related to malnutrition. The effect of treatment on the liver (males and females) and thyroid (males only) were confirmed microscopically, but had distinct sex-related etiologies. The 

incidence of clear cell and basophilic foci was equivocal while eosinophilic foci were significantly increased for male rats in the 2400 ppm group. In female rats of 

the 2400 ppm group, the incidences of clear cell and basophilic foci were significantly decreased but the incidence of eosinophilic foci was unaffected. Also, the 

incidence of hepatocyte fatty vacuolation was increased only in male rats of the 1200 ppm and 2400 ppm groups while the incidence of pigmentation was 

increased only in females of the 200, 1200, and 2400 ppm groups. In addition, the location of hepatocellular hypertrophy was distinctly different. Female rats in 

the 1200 and 2400 ppm groups had significant increases in centriacinar and periacinar hypertrophy while male rats only had centriacinar hypertrophy. Finally, 

the incidence of thyroid follicular cell hyperplasia was increased only in male rats of the 1200 and 2400 ppm groups. The lowest observed adverse effect level (LOAEL) for male and female rats was 1200 ppm (65.8 and 85.2 mg/kg/day, respectively) with a corresponding no observed adverse effect level (NOAEL) of 200 ppm (10.8 mg/kg/day males, 14.6 mg/kg/day females). These are based on the effects found on body weight, weight gain, and the macro- and microscopic effects noted in the liver of all rats and the thyroid of male rats. Male rats had a significant increase in the incidence of hepatocellular adenomas and thyroid follicular neoplasia while no increase was found for female rats. These results indicate a difference in the disposition of Imazalil between the sexes increases hepatic and thyroid neoplasia in male rats, likely through differences 

in metabolic activation of the test material.

STUDY TYPE: Combined chronic toxicity/oncogenicity feeding – Rat OPPTS 870.4300 [§83-5] DP BARCODE: D257223 SUBMISSION CODE: S564270 P.C. CODE: 111901 TOX. CHEM. NO.: 497AB

TEST MATERIAL (PURITY): Imazalil (purity 97.4%) CITATION: Van Deun, K. 1999. Combined oral chronic toxicity/carcinogenicity study with Imazalil in the SPF Wistar rat. Dept. Toxicology, Janssen Research Foundation, 2340 Beerse, Belgium. Laboratory report number, 3817, June 8, 1999. MRID 44858001. Unpublished. EXECUTIVE SUMMARY:

In a chronic toxicity/oncogenicity study (MRID 44858001), Imazalil (97.4% a.i.) was administered in the diet to groups of 50 male and 50 female Hannover substrain (SPF) Wistar-derived rats at concentrations of 0, 50, 200, 1200, or 2400 ppm (equivalent to 0.0, 2.7, 10.8, 65.8, and 134.8 mg/kg/day for males and 0.0, 3.6, 14.6, 85.2, and 168.8 mg/kg/day for females) for two years. All rats were observed daily for clinical signs of toxicity and morbidity, weighed weekly, and food consumption monitored biweekly. Blood and urine samples were collected after 6, 12, and 18 months of treatment and at study end. Surviving rats were sacrificed after 104 weeks of treatment. All rats were necropsied and the tissues and organs inspected grossly and microscopically for toxicity-related effects and 

the carcinogenic potential of Imazalil. Male and female rats in the 1200 ppm and 2400 ppm groups had slightly increased RBCs and slightly decreased MCVs and MCHs that reached statistical significance at most measurement intervals. The differences, however, were within 6% of controls and the historical control limits for rats of this age, sex, and species. No significant treatment-related effects of biological relevance were found for most clinical chemistry parameters. However, plasma triglyceride and the activities of ALKP, AST, and ALT of male rats in the 2400 ppm group and female rats in the 1200 and 2400 ppm groups were often statistically decreased but remained within historical control limits. The effects were considered related to malnutrition. The effect of treatment on the liver (males and females) and thyroid (males only) were confirmed microscopically, but had distinct sex-related etiologies. The 

incidence of clear cell and basophilic foci was equivocal while eosinophilic foci were significantly increased for male rats in the 2400 ppm group. In female rats of 

the 2400 ppm group, the incidences of clear cell and basophilic foci were significantly decreased but the incidence of eosinophilic foci was unaffected. Also, the 

incidence of hepatocyte fatty vacuolation was increased only in male rats of the 1200 ppm and 2400 ppm groups while the incidence of pigmentation was 

increased only in females of the 200, 1200, and 2400 ppm groups. In addition, the location of hepatocellular hypertrophy was distinctly different. Female rats in 

the 1200 and 2400 ppm groups had significant increases in centriacinar and periacinar hypertrophy while male rats only had centriacinar hypertrophy. Finally, 

the incidence of thyroid follicular cell hyperplasia was increased only in male rats of the 1200 and 2400 ppm groups. The lowest observed adverse effect level (LOAEL) for male and female rats was 1200 ppm (65.8 and 85.2 mg/kg/day, respectively) with a corresponding no observed adverse effect level (NOAEL) of 200 ppm (10.8 mg/kg/day males, 14.6 mg/kg/day females). These are based on the effects found on body weight, weight gain, and the macro- and microscopic effects noted in the liver of all rats and the thyroid of male rats. Male rats had a significant increase in the incidence of hepatocellular adenomas and thyroid follicular neoplasia while no increase was found for female rats. These results indicate a difference in the disposition of Imazalil between the sexes increases hepatic and thyroid neoplasia in male rats, likely through differences 

in metabolic activation of the test material.

DER

Input

Pesticide Active Ingredients

Non-Pesticide 

Chemicals

Output Structure

SOURCE

DATA

DATABASE

APPLICATION ToxCast Retro

Status: 572 chemicals, 3184 studies 

http://actor.epa.gov/toxrefdb/faces/Home.jsp
ToxCastDB

High Throughput Screening (HTS) Data

• ToxCastDB provides access to all ToxCast data

• Screening 1,000 chemicals in over 500 rapid tests (highthroughput screening assays

• Users can search and download data for all ToxCast 

chemicals, assays, genes, pathways and endpoints

• Database allows for statistical associations and biologically 

driven data mining

• Provide links to available animal data through ToxRefDB

http://actor.epa.gov/actor/faces/ToxCastDB/Home.jsp
Data from NERL studies

1) American Health Home Survey

2) HUD Child Care Center Survey (“CCC” )

3) CTEPP – NC 4) CTEPP – OH

Browse data capability

> By study name, chemical list, media list

Descriptive statistics capability

> Detection frequency = # of samples above MDL/total # of samples

> N, max, MDL (if result concentration is < MDL, then result = 2/3 * MDL)

> Units

> Mean, standard deviation, geometric mean, geometric standard 

deviation (GSD), 25th and 75th percentile

- Only show these if detection frequency is >= 25 %

ExpoCastDB

Exposure data sets

http://actor.epa.gov/actor/faces/ExpoCastDB/Home.jsp
ACToR

Aggregated Computational Toxicology Resource

http://actor.epa.gov
A knowledgebase that defines AOPs in multiple dimensions

Life stage

Taxonomy

Gender

Time to effect

Level of biological organization

Adverse Outcome Assessment 

Endpoint

Molecular Initiating 

Events
DEFINING AN ADVERSE OUTCOME PATHWAY

Chemical Adverse 

Outcome

MIE 1

MIE 2

MIE n

Effect 1

Effect 2

Effect m

Effect 1

Effect 2

Effect k1

Effect 1

Effect 2

Effect k2

Effect 1

Effect 2

Effect kn

...

Adverse Outcome Assessment 

Endpoint

Molecular Initiating 

Events

BREAKING DOWN THE COMPLEXITY
Functionalities

Visual editor

Search Engine

History tracking module

Suggestion engine and filters 

Chemical database connectivity 

Reference repository

Advanced pathway visualization / analysis tools:

Show pathways in different relevant pathway projections

Sorting and filtering data. 

Vulnerability slider
Facilitates hazard assessment

-catalog of AOPs explaining linkages of biological effects at different levels of observation

-library of molecular initiating events (MIEs) for important adverse outcome pathways. 

-extend QSAR methods by integrating existing models of hundreds of in vitro endpoints with 

relevant assessment endpoints and outcomes 

-extend the OECD Toolbox with chemical profilers for identifying chemicals with similar receptor 

binding profiles (MIEs)—”what other chemicals in the inventory might bind to this receptor” 

-extend the AOPs to all metabolites derived from QSAR-driven simulators for specific 

organ/tissue metabolism

Facilitates forming chemical categories

-organizes expert data and knowledge of AOPs and facilitates the grouping of chemicals into 

categories based on: 

-QSAR allows extrapolating adverse effects determined for one chemical to similar 

chemicals if the chemicals have the same mechanism through the same pathway (AOP)

-OECD category approach groups chemicals that have similar metabolism and hazardous 

effect profiles 
Office of Research and Development

Expert System

An expert system uses a knowledge-base of 

human expertise for problem solving & supporting 

decision making, or to clarify uncertainties where 

normally one or more human experts would need 

to be consulted. Rules developed by experts can 

be codified into logic trees that display the 

decision points in the expert system. 
Office of Research and Development

Expert System Development

1) the creation of a knowledge base which uses 

some knowledge representation structure to 

capture the knowledge of the Subject Matter 

Expert (SME); 

2) a process of gathering that knowledge from the 

SME and codifying it according to the structure, 

which is called knowledge engineering; 

3) once the system is developed, it is placed in the 

same real world problem solving situation as the 

human SME, i.e., to aid decision making. 
In vitro Assay

focus area

ER-mediated Reproductive Impairment AOP

QSAR 

focus 

area

Inerts; 

Antimicrobial

Chemicals

Receptor

Binding

ER Binding

Liver Cell

Protein 

Expression

Vitellogenin 

(egg protein 

transported to 

ovary)

Liver 

Altered 

proteins (Vtg)

Sex 

reversal;

Altered 

behavior;

Repro.

MOLECULAR

Target

CELLULAR

Response 

TISSUE/ORGAN INDIVIDUAL

Skewed 

Sex Ratios;

Yr Class

POPULATION

Greater Toxicological Understanding Greater Risk Relevance
1) the creation of a knowledge base which uses 

some knowledge representation structure to 

capture the knowledge of the Subject Matter 

Expert (SME); 

Log Kow = 3.05 Log Kow = 3.39 Log Kow = 4.06 Log Kow = 5.12

NH2

Log Kow = 0.90

NH2

H3C

Log Kow = 1.96

NH2

H3C

Log Kow = 2.40

H3C NH2

Log Kow = 1.39

NH2

H3C H3C

NH2 NH2

H3C H3C

NH2

ER Knowledge base 

C0

C1 C2 C3 C4 C5 C6 C8
2) a process of gathering that knowledge from the 

SME and codifying it according to the structure, 

which is called knowledge engineering;

Contains a Charge

#2

R ...

1

O

OH

R

1

S

O

O

OH R

1

P

CH2

OH

OH

R

1 N+

R

2

R

4

R

3

Contains sulfonic acid, 

carboxylic acid, 

phosphoric acid or 

quaternary 

ammonium functional 

group.

Has

AND

Contains

3 Oxygen Atoms AND

Does NOT Contain

N, P, F, Cl, Br or I Atoms 

Alkylaromatic Sulfonic Acids

Has

Sulfonic Acid Dyes AND Number of Cycles >= 3

#2.1

#2.2

Structure has c1(S(=O)(=O)O)ccccc1 AND structure has O; number of fragments=3 AND NOT structure has 

Rx:N,P,F,Cl,Br,I

Rx

Structure has c1(S(=O)(=O)O)ccccc1 AND N_Cycles >=3

Decision Tree Node Current Formal Rules (Refined with each inventory)
26

Contains 

a Cycle

Yes

Log KOW <1.3

“Special 

Rule”

Applies

Site “A”

Contains Phenol

Fragment 

Log Kow Range

4-Alkylanilines ( 1.4 - 5.1)

4-Alkoxy Anilines ( 2.6 - 3.7)

Phthalates ( 2.5 - 6.8)

Phenones-(branched) ( 2.7 - 4.8)

4-Alkyl cyclohexanols ( 2.4 - 3.8)

4-Alkyl cyclohexanones ( 2.4 - 3.8) *

2-; 4-; or 2,4,6-Benzoates 

(substitution-dependent Log Kows)

Possible Low Affinity

Site A-Type, Site B-Type

Site “B”

Contains “Specified”

Fragment

Log Kow Range

Alkylphenols (1.5 - 8.0)

Alkoxy phenols (2.3 - 4.3)

Parabens (1.9 - 5.4)

Salicylates (2.5 - 5.1)

Belongs to 

known Active

Sub-class

RBA > 0.00001%

Yes

No

VI

Unknown 

Binding Potential

No

Yes

Yes

No

Yes

Belongs to 

known Active

Sub-class

Belong to untested class

Unknown Binding Potential

Mixed Phenols

No

VII

No

Belongs to 

known Inactive 

Sub-class

Log Kow Range 

4-n-Alkylfluorobenzenes ( 2.3 - 4.9)

Alkylphenol (2,6-subst) ( 4.2)

Benzamides ( 1.7 - 2.1) 

Borate Esters (-0.5 - 1.0)

Benzoates (non-ring subst) ( 3.6 - 4.2)

Bis-anilines ( 1.6 - 6.2)

Hydrofurans (alcohol & ketone) ( 0.0 - 1.2)

Imidazolidines (-0.9 - 0.6) 

Isothiazolines ( 0.6 - 2.5)

Mono-cyclic Hydrocarbons ( 2.7 - 4.6)

Oxazoles (<0.3)

Phenones (n-alkyl) ( 1.6 - 4.1)

Pyrrolidiones (-0.4 - 3.3)

Sorbitans ( 3.2 - 5.9) 

Triazines (-0.4 - 3.4)

Yes

DDT-Like 

Tamoxifen-Like

Multicyclic hydrocarbons

Alkylchlorobenzenes

Thiophosphate Esters

Yes

No

No

Yes

RBA > 0.00001%

RBA < 0.00001%

I

RBA < 0.00001%

Yes

No

V

III

Contains

a Charge

No

Yes

II

Exact match to Mixed Phenols 

Training Set Structure and 

measured RBA

RBA > 0.00001%

RBA < 0.00001%

No

Yes

Unknown 

Binding Potential

Mixed Organics

No

Exact match to Mixed Organics 

Training Set Structure and 

measured RBA

RBA > 0.00001%

RBA < 0.00001%

No

Yes

Unknown 

Binding Potential

Exact match to Group 

Training Set Structure 

and measured RBA

RBA > 0.00001%

RBA < 0.00001%

No

Yes

Alkylaromatic Sulfonic Acids 

Log Kow (-0.6 - 5.7)

Sulfonic Acid Dyes 

Log Kow (-0.4 - 6.0)

4-Alkylbenzthiols 

Log Kow ( 2.9 - 4.2)

Miscellaneous Functional

Groups w/ Charge

Contains a phenolic

OH, and additional

OH and/or =0

IV

Meets specific distance 

criteria for: 

Sites “A-B”;

Sites “A-C”;

Sites “A-B-C”

Contains some 

attenuating feature,

steric or other

High Affinity 

“A-B”;“A-C” or “A-B-C” 

RBA > 0.1%

RBA < 0.00001%

Low Affinity 

“A-B”,“A-C” or “A-B-C”

0.00001% < RBA < 0.1%

Strength of 

attenuation factors 

Yes

No

Strong

Weak

Start Here:

Chemical List

393

Food Use Inerts

3) once the system is developed, it is placed in the 

same real world problem solving situation as the 

human SME, e.g., to aid decision making. 
Office of Research and Development

Metabolism Pathways Knowledgebase

MetaPath

• Collaborative OPP & ORD Project

• National Health and Environmental Effects Research Laboratory 

(NHEERL), Mid-Continent Ecology Division (MED), Duluth, MN

• National Exposure Research Laboratory (NERL), Ecosystems 

Research Division (ERD), Athens, GA 

• Cooperative Agreement with Laboratory of Mathematical Chemistry, 

Bourgas University

• Database & Data Evaluation Tools 

• Common Assessment Tool Box

• International Partnerships (Global Acceptance)

• Stakeholder Engagement
Office of Research and Development

Metabolism Data Use in

Risk Assessment

• Pesticides risk assessment must not only 

consider the active ingredient but also 

pesticide residues.

• Exposure to and potential toxicity of the 

parent compound and any major 

metabolites or degradates is assessed. 
Building a scientific knowledgebase to use existing 

metabolism information in real 

time & in real situations

Heavy Reliance 

On Animal Studies

Less Reliance on

Animals

Generate information

For All possible Outcomes

The Paradigm Shift

Tailor data generation

& obtain right information

For chemical of interest

Empirical approach

Increasing Effectiveness & Efficiency

Mechanism Based Approach
Office of Research and Development

MetaPath

• Knowledgebase that stores information on 

pesticide metabolism and residues in food 

organisms

• Lab animals, livestock, plants, and 

environmental transformation products

• Allows for visualization of parent chemicals & 

metabolites displayed as a pathway or map

• Enables efficient and systematic comparisons 

of metabolites across chemicals, species, and 

environmental media to identify metabolites of 

potential risk concern 
Office of Research and Development

Key Benefits of MetaPath

• Provides structure-based searching and 

identification of structurally similar or unique 

metabolites

• Identifies common metabolites as residues 

in plants, and livestock. 

• Provides a platform for global joint 

reviews/work share efforts

• Systematic compilation of metabolism 

information will facilitate development of a 

metabolism simulator
Office of Research and Development

MetaPath 

a metabolism pathways database and data evaluation tools

DER Composer

a software template for efficient data entry to facilitate: 

- creation of draft Data Evaluation Records (DER) 

for risk assessor evaluations of OPP metabolism studies 

- auto-population submitted data into MetaPath

- enhanced quality control through electronic datahandling

Metabolism Simulator

uses observed metabolite occurrence data from MetaPath 

and knowledge of biotransformation reaction types

to simulate metabolism pathways 

Computational Tools for 

Metabolism Research and Risk Assessment
MetaPath Metabolic Simulators 2013

Building a Scientific Database to Use

Metabolism information in Real Time

Developing & Testing a Predictive

Model that is based on MetaPath

Livestock & 

Plant Residues

Environmental

Degradates

Lab animal

(mostly rat)

Faster more consistent document preparation

Easy information retrieval & searching

>Are there similar metabolites

from different parent AIs?

>Are there sex & species differences?

Reduce Animal Testing: Read Across

Predict

A B

C X?

Are there likely AI metabolites

not found in submitted data? 

Assess metabolism for data poor 

chemicals

> Are there toxic metab/

degradates from 

antimicrobials or 

inert ingredients? 

Building a scientific knowledgebase 

to assess existing 

metabolism/degradate information 

in real time & in real situations
Office of Research and Development

MetaPath

Two components: 

• Database 

- pathways

- metadata 

• Data evaluation tools

Definitions:

map = pathway = tree

experimental matrices = urine, bile, feces, plasma
The main MetaPath display screen

Display of Metabolism 

Pathway (map):

parent chemical + 

metabolites

List of pesticides in the 

database:

Search by Common name, 

ChemName, CAS, Agency 

Code, etc

Clickable ‘Tabs’ to view supporting information, e.g., Results tables of summary 

metabolite quantities as compiled from Registrant studies and reported in DER/DARs. 
Bioassay information associated with the study for a given chemical/map is displayed as 

RESULTS tables to facilitate user interpretation, and can be selected for export and printing.
Pharmacokinetic data associated with the study for a given chemical/map
Analyzing Treatment Group Effects

Maps in the 

database are the 

combined 

pathways across 

all treatment 

groups (as 

reported in the 

study)

(e.g., M +, F; low 

+ high dose; all 

matrices, etc) 

User selects 

treatment group 

of interest; unique 

color shown with 

each treatment. 

For example, this 

metabolite was 

observed only in 

urine of male rats 

at low dose.

Highlight Treatment Group: 

Indicates which metabolites were observed 

under what experimental condition
Map Comparisons – One selected map is compared to another (e.g., Species comparisons), 

or to all others within a database. 

Example: Metabolites common to both maps are shown in green boxes. 

All 3 metabolites found in chickens exposed to tebuconazole (right screen) are found in rats (left screen), 

however, additional metabolites are found in the rat. 
Leverage Existing Knowledge

Search & Group Chemicals by

Shared Features

Chemical structure

Physical chemical properties

(Q)SAR models

In vitro or HTP data

In vivo data

Apply data from a group of tested chemicals for a 

particular property or effect to a similar untested 

chemical for that endpoint

Inherent Properties of the 

Chemical & Chemical Class
Searches: Setting up a Query (Q)

The database can be searched by building Queries (Q) 

Looking for a specific chemical structure, sub-structure, species, 

type of dose administration, etc. 

Simple (one parameter_Q1)

or 

complex (multiple parameter_Q1 to Qx) 

searches using "AND", "OR", "NOT“ 

logic

Example: find all chemicals in the 

database with: 

Q1_Species = rat 

Q2_Administered Dose = oral 

Q3_Metabolite = 1,2,4-triazole 

RESULTS – next slide
SEARCH RESULTS

Within the entire database, 3 metabolites 

were found matching search criteria, 

triazole metabolite found in rats dosed by 

oral gavage. 

Info is provided to trace back to the parent 

chemical and the entire metabolic 

pathway. 
Excel Output from MetaPath
Office of Research and Development

Developed around Pharmacokinetic & Metabolism, and 

Nature of the Residue harmonized guidelines:

1) OPPTS 870.7485 (85-1) Rat Metabolism

2) OPPTS 860.1300 Nature of Residues in Animals

• Data entered in DER Composers can output as: 

– *.xml file for direct data import into MetaPath

– *.doc file draft Data Evaluation Record to record OPP 

decisions 

• Efficient standardized data entry 

• Facilitates electronic data submission and e-population of 

new data into MetaPath into the future

DER Composer: 

System for Auto-population of MetaPath
screen shots from ‘DER Composer’ software

‘General Info’ 

screen 

corresponding to 

first page of an 

OPP rat 

metabolism Data 

Evaluation 

Record (DER); 

currently used 

for entry of 

archived DERs, 

but could be used 

to build new 

DER.

Note the OPP and 

OECD 

guideline 

numbers 
‘Materials and 

Methods’ tab, 

Part A: 

Materials.

Chemical 

structure can be 

drawn with 

internal 

structure 

drawing 

package, or from 

imported 

SMILES string. 
‘Materials and 

Methods’ tab, 

Part B: Study 

Design and 

methods.

This information 

is captured in 

table format 

similar to what is 

found in the 

DER. 

Text boxes are 

included for addition 

of explanatory 

information as 

typically found in 

DERs.

Analytical 

method details 

can be captured 

as text, or more 

systematically in 

a Table. 
Tables are built for 

Pharmacokinetic and 

Metabolite 

Characterization 

data.
Text boxes are 

included for addition 

of explanatory 

information as 

typically found in 

DERs.
Appendix Table 1:

Systematic capture of treatment group 

parameters for:

-Autopopulation of DER Table 1

-Specifying metabolite differences 

due to treatments, gender, matrix 

(Highlight Treatment Grp feature in 

MetaPath)

Appendix Table 2:

Chemical structures of parents and 

metabolites entered as SMILES strings;

Connectivity between parent and each 

metabolite (i.e., the metabolism pathway).
DER Composer data entry screen DER *.doc file 
MetaPath – ‘General Info’
Appendix Table 1:

Systematic capture of treatment group 

parameters for:

- autopopulation of DER Table 1

- Specifies treatments, i.e., M,F; dose level & 

duration; excretion route, etc., as ‘Highlight 

Treatment Group’ feature in MetaPath

Appendix Table 2:

-Chemical structures of parents and 

metabolites entered as SMILES strings;

-Connectivity between parent and each 

metabolite (i.e., the metabolism pathway) is 

specified here

DER Composer - Appendix Table 1 & Table 2
Tables are built for 

Pharmacokinetic and 

Metabolite 

Characterization data.

Pre-populated with row & column headers 

as defined in Appendices; this info is used in 

MetaPath to associate which metabolites 

were found under which experimental 

conditions; e.g., if a cell in this table reports 

a number for a metabolite, then the 

metabolite will be shown as detected in that 

treatment (dose level; gender group) in 

MetaPath if selected in “Highlight Treatment 

Group”

DER Composer - ‘Results’ – Metabolite Characterization 
MetaPath - Highlight Treatment Group Feature
Office of Research and Development

Benefits of DER Composers

• improve efficiency in data summary and 

submission

• maximize electronic data transfer to minimize 

data errors

• facilitate QA of data

• autopopulate Agency knowledge-bases to 

improve PRIA workflow; 

- getting data in the hands of the risk assessor more 

efficiently

- spend less time compiling data and more time 

assessing
Office of Research and Development

DER Composers

• OECD Working Group on Pesticides/MetaPath 

Users Group working with OECD Secretariat 

towards use of rat, livestock Data Summary 

Builders (DER Composers) for data capture and 

population of MetaPath

• Using the same approach, EPA would develop 

DER Composers to facilitate electronic capture 

of registrant-submitted toxicity data

• DER Composers for EDSP T1S data submission
Assessment Team 

(Lead Toxicologist 

and Risk Assessors) 

review the 

Toxicology Profile 

using summary 

information in draft 

DER and refer to 

Study File as 

appropriate 

ROCKS Hazard Assessors pre-meet 

before full committee meeting to 

discuss team proposal and 

consider metabolites of potential 

hazard concern (using MetaPath

and/or other (Q)SAR tools for 

predictions) summarized in draft 

DER

MetaPath/DER Composer use in OPP workflow

Registrant produces Residues Of Concern Knowledgebase Subcommittee (ROCKS)

draft DER (doc file) and 

XML for a ‘new’ 

chemical using 

‘DER Composer’

(rat metabolism, 

livestock residues, plant 

residues, environmental 

degradates)

MetaPath tools

used to assess 

common metabolites 

for Proposed

Residue Definitions 

for inclusion in 

Risk Assessment 

and Tolerance 

Expression recorded 

in 

draft DER

‘new’ chemical xml

(after QA) is added to 

MetaPath database

ROCKS Committee Reviews the 

team’s proposal and renders an 

Expert opinion/ 

recommendation(s);

draft DER updated and decision 

finalized and reported in 

final DER

MetaPath

draft DER
Office of Research and Development

• A new sulfonyl urea “Pesticide B” is 

being assessed. MetaPath could be 

used to ask: 

• What other sulfonyl urea pesticides have 

we previously assessed? 

• What types of metabolic transformations 

are likely to occur?

• What are likely residues of concern? 

MetaPath Example
O S

O

CH3

S

O

O

NH

O

NH

N

O

CH3

H3C O

N

N

N

Ran search in MetaPath for structural analogs to Parent.

Cl

S

O

O

NH

O

NH

N

O

CH3

H3C O

N

N

N

Pesticide B Structural sub-fragment for search

RESULTS: Found Rat Metabolism maps within database for four sulfonyl ureas.

O S O

CH3

S

O

O

NH

O

NH

N

O

CH3

H3C O

N

N

N

Pesticide W

S

O

O

N

-

Na

+

O

NH

N

O

CH3

H3C O

N

O

F

F

F

N

Pesticide X

O

S

O

O

NH

O

NH

N

O

CH3

H3C O

N

NH

S

CH3

O

O

H3C O

Pesticide Y

Cl

S

O

O

NH

O

NH

N

O

CH3

H3C O

N

Pesticide Z
S

NH2

O

O O

F F

F

N

1.1.

H3C O

HO

O

CH3

N

NH

O

NH

S

O

O

O

F

F

F

N

N

1.

O

CH3

HO

H3C O

N

N O

F F

F

N

NH2

O

N

1.2.

O

CH3

OH O

HO

OH OH

O

O

CH3

N

N O

F

F

F

N

NH2

O

N

 EXJ 

1.2.1.

O

CH3

OH O

HO

OH OH

O

O

CH3

N

NH

O

NH

S

O

O

O

F F

F

N

N

 EXJ 

1.3.

O

CH3

OH O

HO

OH OH

O

O

CH3

N

N O

F

F

F

N

NH2

O

N

 EXJ 

1.3.1.

S

O

O

NNa+

O

NH

N

O

CH3

H3C O

N

O

F

F

F

N

Parent

S

O

O

NH

O

NH

NH

NH

O

HO

O

F F

F

N

 EXJ 

2.1.

S

O

O

NH

O

NH

NH

NH2

O

F F

F

N

2.1.1.

S

O

O

NH

O

NH

N

OH

H3C O

N

O

F

F

F

N

2.

N

N

OH

H3C O

N

NH2

O

O

F

F

F

N

2.2.

NH

N

OH

H3C O

O N

F

F

F

N

2.2.1.

S

NH2

O

O O

F F

F

N

3.

Map for Pesticide X shows primary 

metabolic pathway of:

ring hydroxylation, O-dealkylation, and 

cleavage to the sulfonamide
Map for pesticide W also shows:

ring hydroxylation, O-dealkylation, and 

cleavage to sulfonamide, potentially 

resulting in same residues of concern. 

O S O

CH3

S

O

O

NH

O

NH

N

OH

H3C O

N

N

N

1.

O S O

CH3

S

O

O

NH

O

NH

N

O

CH3

H3C O

N

N

N

Parent

O

CH3

OH

O

CH3

N

NH

O

NH

S

O

O

S

O

O

CH3

N N

N

2.

O S O

CH3

S H2N

O

O

N

N

2.1.

O S O

CH3

S H2N

O

O

N

N

3.
KB/DSS components - MetaPath:

• Inputs: Factors, data and characteristics, to analyze:

MetaPath - metabolic maps and associated metadata tables specified in 

the Data Evaluation Records as the study information important to the 

evaluations (automated e-data entry via DER Composers)

• User Knowledge and Expertise: Inputs requiring manual analysis by 

the user:

MetaPath - User defines substructures for searching, map comparisons 

to make, etc

• Outputs: Transformed/analyzed data from which DSS "decisions" are 

generated: 

MetaPath – lists all AI containing substructure of concern; common 

metabolites across hundreds of maps in the KB are identified using the 

software; residues of concern identified within the maps of the AIs listed; 

etc

• Decisions: Results generated by the DSS based on user criteria: 

MetaPath - User identifies residues of concern for current pesticide 

assessment (as a result of map comparisons; treatment group 

comparisons; substructure searches; subsequent analysis 

metabolites/degradates in MetaPath outputs in QSAR toolbox, expert 

systems, etc)
Benefits of Decision Support Systems

• Improves personal efficiency (desktop data availability)

• Speed up the process of decision making (automated loading of 

new information into OPP proprietary database for comparison of 

new map information with legacy data)

• Increases organizational control (consistency)

• Encourages exploration and discovery on the part of the decision 

maker (allows new analyses/comparisons)

• Speeds up problem solving in an organization 

• Facilitates interpersonal communication (within OPP; with 

international partners in global joint reviews)

• Promotes learning or training (allows new analyses/comparisons)

• Generates new evidence in support of a decision (comparisons 

between chemicals; species - gender; dose-levels etc)

• Reveals new approaches to thinking about the problem space 

• Helps automate managerial processes (standardize data 

gathering; analysis; reporting)
Collaborations

• Working toward a common international 

platform for storing & evaluating information 

– International MetaPath User Group established 

under OECD (Working Group on Pesticides)

– Collaborators:

• Health Canada, Pesticide Management Regulatory 

Authority

• European Food Safety Authority and European member 

countries

• Australia’s Pesticides & Veterinary Medicines Authority 

and Office of Chemical Safety & Environmental Health

• OECD Secretariat 
Office of Research and Development

Partnership between EPA/OPP and EPA/ORD/ NHEERL & NERL, and PMRA Health Canada:

NHEERL, MED - Duluth, MN: P. Schmieder, R. Kolanczyk

NERL, ERD - Athens, GA: J. Jones

Cooperative Agreement with: O. Mekenyan, Laboratory of Mathematical Chemistry (LMC) , 

Bourgas University, Bourgas, Bulgaria, 

OPP - Residues Of Concern Knowledge-bases Sub-committee (ROCKS): M. Manibusan, C. 

Olinger, R. Kent 

OPP, Environmental Fate and Effects Division (EFED): Fate Tech Team 

PMRA, Health Canada: L. Croteau, M. Gerrits

MetaPath Partners: