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GARD : An in vitro platform for toxicological assay development

Gradin, Robin LU (2020)
Abstract
Life in modern society is intricately intertwined with the results of continuous technological advances. This
has given rise to daily routines where people are frequently exposed to a wide variety of chemicals.
Though many of the chemicals do not generally induce adverse health effects upon normal exposure,
several of them has the potential to negatively impact health. Indeed, in order to create products that are
safe for the general population, potential hazards must be considered and characterized. However, many
of the potential adverse health effects are challenging to assess due to the complexity of their underlying
mechanisms.
Therefore, hazard assessment has traditionally been based on animal models, since... (More)
Life in modern society is intricately intertwined with the results of continuous technological advances. This
has given rise to daily routines where people are frequently exposed to a wide variety of chemicals.
Though many of the chemicals do not generally induce adverse health effects upon normal exposure,
several of them has the potential to negatively impact health. Indeed, in order to create products that are
safe for the general population, potential hazards must be considered and characterized. However, many
of the potential adverse health effects are challenging to assess due to the complexity of their underlying
mechanisms.
Therefore, hazard assessment has traditionally been based on animal models, since the available
knowledge has failed to reduce the complexity to a state that allows the creation of simpler yet effective
alternative assays. However, animal models are problematic for several reasons, which makes the
development of accurate non-animal alternatives for hazard assessment a sought-after endpoint.
The GARD platform has been developed towards this end, and it permits the development of effective nonanimal
assays, even for mechanistically complex endpoints. The method exploits the technological
advances enabling transcriptomic analysis, following controlled exposure experiments, with machine
learning techniques to identify predictive biomarkers and to define high-performing classification models.
This thesis presents the GARD platform and its technological constituents and highlights how it can be
used to create assays aimed towards mechanistically complex endpoints, while simultaneously generating
new information that can aid the understanding of said endpoints. Further, two of the developed GARD
assays, GARDskin and GARDpotency, are described in more detail. Both assays have been developed
toward the hazard endpoint of skin sensitization and provide cutting edge performances in hazard
identification and hazard characterization, and represent viable alternatives for eventually eliminating the
need for animal testing. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Ass. Prof. Öberg, Mattias, Karolinska Institute, Solna.
organization
publishing date
type
Thesis
publication status
published
subject
keywords
In vitro assay, predictive modelling, skin sensitization, Toxicology
pages
123 pages
publisher
Department of Immunotechnology, Lund University
defense location
Lecture hall Hörsalen, Medicon Villagre, Scheelevägen 2, Faculty of Engineering LTH, Lund University, Lund
defense date
2020-11-27 09:00:00
ISBN
978-91-7895-650-0
978-91-7895-651-7
language
English
LU publication?
yes
id
8df96d61-f1e9-4e61-b851-931dffd9a7ae
date added to LUP
2020-11-01 17:05:03
date last changed
2024-02-13 10:52:29
@phdthesis{8df96d61-f1e9-4e61-b851-931dffd9a7ae,
  abstract     = {{Life in modern society is intricately intertwined with the results of continuous technological advances. This<br/>has given rise to daily routines where people are frequently exposed to a wide variety of chemicals.<br/>Though many of the chemicals do not generally induce adverse health effects upon normal exposure,<br/>several of them has the potential to negatively impact health. Indeed, in order to create products that are<br/>safe for the general population, potential hazards must be considered and characterized. However, many<br/>of the potential adverse health effects are challenging to assess due to the complexity of their underlying<br/>mechanisms.<br/>Therefore, hazard assessment has traditionally been based on animal models, since the available<br/>knowledge has failed to reduce the complexity to a state that allows the creation of simpler yet effective<br/>alternative assays. However, animal models are problematic for several reasons, which makes the<br/>development of accurate non-animal alternatives for hazard assessment a sought-after endpoint.<br/>The GARD platform has been developed towards this end, and it permits the development of effective nonanimal<br/>assays, even for mechanistically complex endpoints. The method exploits the technological<br/>advances enabling transcriptomic analysis, following controlled exposure experiments, with machine<br/>learning techniques to identify predictive biomarkers and to define high-performing classification models.<br/>This thesis presents the GARD platform and its technological constituents and highlights how it can be<br/>used to create assays aimed towards mechanistically complex endpoints, while simultaneously generating<br/>new information that can aid the understanding of said endpoints. Further, two of the developed GARD<br/>assays, GARDskin and GARDpotency, are described in more detail. Both assays have been developed<br/>toward the hazard endpoint of skin sensitization and provide cutting edge performances in hazard<br/>identification and hazard characterization, and represent viable alternatives for eventually eliminating the<br/>need for animal testing.}},
  author       = {{Gradin, Robin}},
  isbn         = {{978-91-7895-650-0}},
  keywords     = {{In vitro assay; predictive modelling; skin sensitization; Toxicology}},
  language     = {{eng}},
  month        = {{11}},
  publisher    = {{Department of Immunotechnology, Lund University}},
  school       = {{Lund University}},
  title        = {{GARD : An in vitro platform for toxicological assay development}},
  url          = {{https://lup.lub.lu.se/search/files/86037423/Robin_Gradin_web.pdf}},
  year         = {{2020}},
}