Using Quantitative Structure-Activity Relationships (QSAR) to Establish Toxicity/Environmental Scores (TES) Público

Ogden, Jona Marie (2012)

Permanent URL: https://etd.library.emory.edu/concern/etds/tb09j619g?locale=es
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Abstract

Using Quantitative Structure-Activity Relationships (QSAR) to Establish
Toxicity/Environmental Scores (TES)
The Agency for Toxic Substances and Disease Registry (ATSDR) uses
Reportable Quantities (RQs) established by the Environmental Protection
Agency (EPA) in order to prioritize substances subject to Toxicological Profile
development. RQs are calculated using two distinct criteria. The first criteria is
based on the intrinsic physicochemical (ignitability/reactivity) and toxicological
properties (aquatic toxicity, acute mammalian toxicity, chronic toxicity, and
potential carcinogenicity) of each chemical. The second criteria is based on a
chemical's susceptibility to biodegradation, hydrolysis, and photolysis (BHP).
When an RQ is not available, ATSDR uses the same criteria to develop a
Toxicity/Environmental Score (TES). Sufficient original data are not available to
assign a TES to many candidate chemicals. However, Quantitative Structure-
Activity Relationship (QSAR) methods can be used to computationally predict the
physicochemical, toxicological and biodegradability properties needed to
calculate TESs. To evaluate the potential use of QSAR methods to estimate
TESs, the physicochemical, toxicological and biodegradability properties of 102
chemicals were computationally-predicted, and QSAR TESs estimated. QSAR
rat oral LD50, fathead minnow LC50, and BHP models predicted TESs that
correlated strongly (71%, 53%, and 67%, respectively) with original TESs.
QSAR could not predict a dose-response relationship needed to score chronic
toxicity. However, an alternate approach combining developmental toxicity and
chronic LOAELs was used to estimate chronic toxicity values. Using 1 of 4
proposed methods, QSAR-derived TESs were identical to original TESs for 57%
of the chemicals evaluated. 89% of predicted TESs were within 1 tier of original
TESs. Thus, QSAR methods may be used as an alternative approach to fill in
data gaps needed for calculation of TESs. To optimize the use of In Silico
prediction, an integrated approach for the use of multiple QSAR models, tools
and approaches is needed.



Using Quantitative Structure-Activity Relationships (QSAR) to Establish
Toxicity/Environmental Scores (TES)
B.S., Environmental Health Science
The University of Georgia
2009
Thesis Committee Chair: W. Michael Caudle, PhD
A thesis submitted to the Faculty of the
Rollins School of Public Health of Emory University
in partial fulfillment of the requirements for the degree of
Master of Public Health
in Environmental Health
2012

Table of Contents



Table of Contents
INTRODUCTION
..........................................................................................................................
1

METHODS
.....................................................................................................................................
5

DATASET
..................................................................................................................................
5

QSAR PROTOCOL
..................................................................................................................
5

Carcinogenicity
.....................................................................................................................
6

Acute Toxicity
........................................................................................................................
7

Chronic Toxicity
....................................................................................................................
9

Aquatic Toxicity
...................................................................................................................
11

Biodegradability
..................................................................................................................
12

Ignitability/Reactivity
...........................................................................................................
13

RESULTS
....................................................................................................................................
14

ANAYLSIS OF INTRA-CRITERIA AGREEMENT
..............................................................
14

ANALYSIS OF SCORING METHODS
................................................................................
21

DISCUSSION
..............................................................................................................................
23

REFERENCES
...........................................................................................................................
27




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