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Modeling of Hazard and Organ Manifestation

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Toxicology 21: Scientific Applications

约翰霍普金斯大学

4.6（19 個評分） | 2.1K 名學生已註冊

This course familiarizes students with the novel concepts being used to revamp regulatory toxicology in response to a breakthrough National Research Council Report “Toxicity Testing in the 21st Century: A Vision and a Strategy.” We present the latest developments in the field of toxicology—the shift from animal testing toward human relevant, high content, high-throughput integrative testing strategies. Active programs from EPA, NIH, and the global scientific community illustrate the dynamics of safety sciences.

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4.6（19 個評分）

5 stars
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NK

Dec 27, 2018

A very well-taught course with lots of useful information. I highly recommend it.

OA

Nov 20, 2018

Awesome course! Highly essential information for all toxicologists!

從本節課中

Module 2

This module will discuss how ToxCast and Tox21 technologies can be used in practice. The US EPA Endocrine Disruptor Screening Program will be discussed in detail and we will demonstrate how the ToxCast platform replaced in vivo tiered approaches in EDSP and, thus, acelerate the process of . In the second lesson of this module, the development of in silico models for toxicity testing will be discussed.

Modeling of Hazard and Organ Manifestation11:14

Building a Signature for Vascular Disruption10:31

Testing the Vascular Disruption Signature8:36

Virtual Tissue Model: Vascular Development12:20

Functional Vascular Development Assays16:42

教學方

Lena Smirnova
Research Associate
Thomas Hartung
Professor

腳本

[MUSIC]

Hi and welcome to the lecture on Modeling of Hazard and Organ Manifestation.

I'm Nicole Kleinstreuer, the deputy director for

the National Toxicology Program Interagency Center for

Alternative Toxicology Methods, based in Reasearch Triangle Park, North Carolina.

And today I'll be taking you through a case study of vascular development and

how we model that and understand how certain chemicals might disrupt vascular

development and cause developmental toxicity.

First, the requisite disclaimer.

This research was funded by multiple federal agencies,

none of whose views I am espousing.

These views are exclusively my own.

The learning objectives for this lecture are to understand the concept of

an adverse outcome pathway, the key components that make up an adverse outcome

pathway, and how we can map in vitro, or cell-based,

high-throughput screening assays to those adverse outcome pathways.

We would also like for you to be able to explain ToxPI, or the toxicological

prioritization index, and how it is used to prioritize environmental chemicals.

We want you to be able to define virtual tissues and in silico testing platforms,

and discuss using small model organisms, like zebrafish, and functional assays,

like vascular development assays, to test those predictions.

Our first section will provide background on high-throughput screening,

the ToxCast and Tox21 federal research programs, and

how those are used to predict adverse outcomes.

In 2007, the National Academy of Sciences published

Toxicity Testing in the Twenty-first Century: A Vision and a Strategy.

This document can be accessed via the web link on your screen.

The panel called for a move away from animal testing, to high-throughput and

in vitro, that is cell-based assays,

to understand how chemicals perturb cellular functions.

The committee envisioned that this paradigm shift would help us establish

a linkage between molecular and cellular perturbations, in vitro,

and adverse outcomes in vivo, that is in whole organisms like animals or humans.

Those linkages are referred to as adverse outcome pathways.

High-throughput screening is an advancement in technology that allows for

better, faster, and broader coverage of the chemical landscape.

These types of screening methods and assays allow for faster and

cheaper assessment of biological activity and the use of much fewer animals.

That achieves the three R’s, reduction, refinement, and

replacement of animal testing.

This slide shows an image that represents the high-throughput screening paradigm.

You can see the yellow robot up at the National Center for

Advancing Translational Sciences working tirelessly 24 hours a day

to screen thousands of chemicals against many different cell-based and

biochemical targets.

Those include receptors and protein signalling and cell stress pathways.

We also have assay platforms that provide us with high content screening.

So detailed imaging and visualization of things like cellular

adhesion molecules and how those may be disrupted by chemical exposure.

With all of this data on so many different chemicals, it's quite a challenge to

interpret all of that data and bring it together in a comprehensible fashion.

That's why we need systems modeling, to bring in data from the literature,

data from high-throughput screening, and date mining, and our understanding of

biological pathways in a way that will allow us to make predictions about

entire systems and how chemicals may disrupt them and cause adverse outcomes.

To this end, the US Environmental Protection Agency,

in partnership with the Food and Drug Administration, the National Institute for

Environmental Health Sciences and the National Toxicology Program and

the National Center for Advancing Translational Science,

another NIH institute, have partnered together to form the Tox21 consortium.

Within the Tox21 consortium is the Toxicity Forecaster,

or ToxCast research program.

This program has profiled to date over 2,000 chemicals

across over 700 in vitro assays.

The first phase focused on predominantly food used pesticides,

around 300 chemicals that were very data-rich.

They had over 30 years of traditional animal studies.

Those studies are valued at over $2 billion.

So those provide some nice anchoring end points,

where we can compare the bio-activity that these chemicals cause in vitro,

in the cell-based or biochemical assays, and compare those

to the in vivo toxicity endpoints that we saw in the animal studies.

Phase-II expanded the chemical landscape to an additional

776 chemicals from a wide range of sources.

These were industrial and consumer products,

things like cosmetics ingredients, food additives, and failed pharmaceuticals.

This chemical library was used to extend and apply the first generation

predictive models of toxicity that were built off the Phase-I data set.

Currently, Phase-III of ToxCast testing is under way,

that expands the chemical library to an additional 1,000 chemicals.

Tox21 tests far more chemicals in a smaller range of assays.

As you can see on this slide, the coverage of chemical space

is quite wide with the TOX21 program but the chemicals are not

being tested in quite as many endpoint, only around 50 or so.

Those map particularly to cell stress related pathways,

versus ToxCast which has a much larger coverage of the target space and

a fewer number of chemicals.

The coverage of the assay space that's represented in the ToxCast

chemical testing research program is shown here.

There are a number of different assay providers.

These come from the most cutting edge scientific

platforms available both in the commercial and the academic space.

And they cover a wide range of biological responses,

including things like cell proliferation, cell death, functional

cellular assays that investigate things like mitochondrial function or

a protein expression or receptor activity, receptor binding.

They cover a variety of target families and

span a range of assay designs, readout types, and formats.

The majority of the assays in ToxCast are human targets, but

there are several other species represented.

And there's quite a wide variety of tissue sources and

detection technologies that are being used.

On the animal side, we have the Toxicological Reference Database, or

the ToxRefDB.

ToxRefDB holds in vivo endpoint data from animal toxicology studies.

These come from data evaluation records, from the EPA,

long term animal studies from the National Toxicology Program, some contributions

from the open literature that have been very heavily evaluated for

a high enough standard of quality to be included with the federal studies.

From this animal studies we can derive LELs,

or lowest effect levels, for endpoints of concern.

There are currently over 1,000 chemicals with over 5,500 studies in the ToxRefDB.

And at this slide, you can see a breakdown of the different endpoints,

from chronic cancer studies in various species to

developmental prenatal toxicity studies, multi-generational

reproductive toxicity studies, subacute, and subchronic studies.

So how do we link the bio-activity profiles that the chemicals

exhibit in vitro, in the cell-based or cell free assays,

with the toxicity endpoints that they may cause in vivo in the animal studies?

From a very basic perspective, we can divide those chemicals for

particular animal toxicity into those that caused that toxicity and

had a lowest effect level, or LEL,

to those that were non-toxic and did not have an LEL.

And then we can use computational methods to look for

in vitro effects that are associated with that toxicity endpoint

in the animal based on that group of chemicals that have an LEL.

And look for in vitro effects, or lack of effect,

that are associated with chemicals that did not cause that toxicity endpoint and

look for statistical significance and build models off of that data.

Here are a list of ToxCast predictive models.

These can be loosely divided into two categories.

Models that are built based on particular endpoints, like liver tumors or

Inhibiting development in a prenatal guideline study,

versus models that built off of modes of action.

So bringing to bear our knowledge of the biology to build models for

predicting disruption of certain biological pathways.

Things like disrupting the endocrine system or,

in this case, disruption of vascular development.

That is the case study that I will be focusing on today in this lecture.

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