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Estimating percutaneous absorption using microlevel-activity time series (MLATS).

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Estimating percutaneous absorption using microlevel-activity time series (MLATS).
作者:	Ferguson, Alesia Coralie.
面頁冊數:	413 p.
附註:	Adviser: James O. Leckie.
附註:	Source: Dissertation Abstracts International, Volume: 64-05, Section: B, page: 2336.
Contained By:	Dissertation Abstracts International64-05B.
標題:	Engineering, Environmental.
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3090585
ISBN:	0496383078

Estimating percutaneous absorption using microlevel-activity time series (MLATS).
Ferguson, Alesia Coralie.

Estimating percutaneous absorption using microlevel-activity time series (MLATS). [electronic resource] - 413 p.

Adviser: James O. Leckie.

Thesis (Ph.D.)--Stanford University, 2003.

Accurately assessing the health risk posed by toxic chemicals that come into contact with the human skin requires understanding the complex nature of the exposed boundary (i.e., skin), and the many interactions that can occur. For that reason, the risk assessment field requires acceptable mathematical models to estimate percutaneous absorption. The primary objectives of this dissertation are (1) the development of a physiologically based, pharmacokinetic (PBPK) model (called the DoseModel) to calculate the skin absorption of chemicals; (2) coupling of this model to a previously developed physical-stochastic exposure model (called the Dermal Exposure Reduction Model or DERM). The coupled model is unique in its use of micro-level activity time series data (MLATS) that describe in details the contact events leading to the mass loading of a chemical on the skin surface. Therefore the third primary objective of this dissertation was the collection of MLATS for children (aged 1--12) and, the associated development of videotaping and video-translation methodologies for quality assurance on MLATS.

ISBN: 0496383078Subjects--Topical Terms:

212478
Engineering, Environmental.

Estimating percutaneous absorption using microlevel-activity time series (MLATS).
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520 # $a Accurately assessing the health risk posed by toxic chemicals that come into contact with the human skin requires understanding the complex nature of the exposed boundary (i.e., skin), and the many interactions that can occur. For that reason, the risk assessment field requires acceptable mathematical models to estimate percutaneous absorption. The primary objectives of this dissertation are (1) the development of a physiologically based, pharmacokinetic (PBPK) model (called the DoseModel) to calculate the skin absorption of chemicals; (2) coupling of this model to a previously developed physical-stochastic exposure model (called the Dermal Exposure Reduction Model or DERM). The coupled model is unique in its use of micro-level activity time series data (MLATS) that describe in details the contact events leading to the mass loading of a chemical on the skin surface. Therefore the third primary objective of this dissertation was the collection of MLATS for children (aged 1--12) and, the associated development of videotaping and video-translation methodologies for quality assurance on MLATS.
520 # $a The main component of the DoseModel, is a finite volume, time-varying, numerical model, that (1) estimates the uptake of chemical mass into two-layers of the human skin, and (2) is suitable for multiple chemical exposure events described by MLATS. The DoseModel, also incorporates other simpler, previously developed, analytical models for chemical uptake into the skin (from liquid and soil vehicles, and for infinite and finite chemical sources). The DoseModel is available in the S-Plus programming platform with a user-friendly interface for managing the routine calculations, and for generating quantitative and graphical output. Simulations of the coupled model have been performed, using the MLATS data from 20 children (aged 1--6), to demonstrate model utility, and performance Results reveal that dermal uptake is highly dependent on the vehicle volume and type, as well as the chemical exposure amount and contact profile of chemical mass loading on the skin surface. Simulations also address previous overly conservative assumptions of the existing DERM model.
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