Integration of non-testing tools: a weight of evidence...

SETAC - October 24, 2008

Integration of non-testing tools:

a weight of evidence approach

Dinant Kroese

TNO Quality of Life

Zeist, The Netherlands


Generation of information under REACH

Gathering all existing data

Data sharing

Animal studies only as a last resort


Tonnage Human Health

1 – 10 tpa

Annex VII

• In vitro skin and eye irritation

• Skin sensitization

• In vitro mutagenicity

• Acute toxicity (one route)

10 – 100 tpa

Annex VIII

• In vivo skin and eye irritation

• Further in vitro mutagenicity

• Acute toxicity (2nd route)

• Sub acute toxicity (28d)

• Reproductive toxicity screen

100 – 1000 tpa

Annex IX

• Further mutagenicity tests

• Sub-chronic toxicity (90d)

• Reproductive toxicity tests

>1000 tpa

Annex X

• Further mutagenicity tests

• Further reproductive toxicity

tests

• Carcinogenicity may

• Chronic toxicity may

Required Information under REACHAnnexes VII - X


REACH

Estimated number of substances

20,000substances

Annex VIII

≥ 10 tpa

Annex VII

≥ 1 tpa

Annex IX

≥ 100 tpa

Annex X

≥ 1000 tpa4,600

substances

2,900substances

2,600substances


Scenario for animal use under REACH

2030

Anim

al use

Pre-registration

Dec 2008

Registration Annex X

+ CMR (cat 1+2) > 1 tonne/y

+ very toxic (R50/53) > 100 tonnes/y

Dec 2010

Registration Annex IX

June 2013

Registration Annex VII & VIII

June 2018

2008 2010 2020


Different types of information

In vitro

(Q)SAR

Grouping & read across

Exposure

Human data Non-Testing information


Combine information in Integrated Testing Strategies (ITS)

In vitro


(Q)SAR

Existing testing

information

Human data

Gathered information ..

via ITS



Additional Testing Needed?

using WoE

cf Required information:Annexes VI-XI ?

In vitro


(Q)SAR

Existing testing

information

Human data

Perform the test!



Additional Testing Needed?

using WoE

cf Required information:Annexes VI-XI ?

In vitro


(Q)SAR

Existing testing

information

Human data

Perform the test!

Waiving cf Annex XI:

Technical or Exposure arguments

?


…taking into account:

Quality descriptors

Relevance of data

Acceptability in the field

Fit for purpose

Cost effectiveness

Pragmatism

Deadlines

Weight of Evidence

Making decisions on information in ITS ….


REACH objectives

C&L, RC

When is information sufficient?

OK ???

Non-GLP / Non-OECD

Available information

+ =

+

+


Evaluating information

• allows for transparency and objectivity

• assesses value of individual test & non-test information

• combines values of test & non-test information, expert judgement,

historical context

• reflects hierarchy of the testing strategy

• quantifies uncertainty

• resolves conflicting results….

a formal approach needed!

……that:


Evaluating information

• allows for transparency and objectivity

• assesses value of individual test & non-test information

• combines values of test & non-test information, expert judgement,

historical context

• reflects hierarchy of the testing strategy

• quantifies uncertainty

• resolves conflicting results….

a formal approach needed!

……that:


e.g. use of (Q)SARs

Human health effect

Human exposure to substance A

Animal model


e.g. use of (Q)SARs

Mechanism A

Mechanism B

Mechanism C

Animal model

‘Same’ effect


e.g. use of (Q)SARs

Mechanism A

Mechanism B

Mechanism C

Animal model

‘Same’ effect

(Q)SAR model, critical:

1. Understanding of toxicity mechanisms

biological domain

2. Specifying of applicability domains

chemical domain

Statistical model


e.g. use of (Q)SARs

Animal model Statistical model

Uncertainty is defined by

variability sensitivityspecificity


Evaluating information in ITS

ITS can be modeled as Decision Networks through

Influence Diagrams

Influence Diagrams are graphical networks with 3 types of

nodes, that model:

1. Chance events, e.g. probability of a chemical having a

certain property

2. Decisions, such as exposure-based waiving, decisions to

do more testing

3. Utilities: costs, animal use, value of information

using ‘Decision Analysis’


Influence Diagram:

Does a compound have a certain toxicity?

Result Model A

Decide on running one or more non-testing models from toolbox

Costs, value, animal use

Result Model B Result Model C

Result Model I

Decide on running one or more testing models from toolbox

Result Model II

Mechanisms, Domain, Specificity, Sensitivity …

Result Model III

Sufficient certainty to make decision?

?

Dependence…

Predictivity…


Is there a WoE approach?

Not yet available….


Landscaping document: conclusions

Webtool: position & functionalities

Route to webtool: concept deliverable

Takes time to achieve common understanding and agreement!

…

interaction between:toxicologist, chemists, statisticians, hygienists, toolbuilders…..

‘own’ language and concepts etc ….


The OSIRIS webtool

To help registrant/user to comply with REACH

SETAC - October 24, 2008EU Working Group on QSARs - OSIRIS

OSIRIS webtool features

Implements the ITS developed within RIP/OSIRIS

Compatibility of data formats from external sources

Is secure and keeps user privacy

ITS processes are persistent

ITS is easily changed

Is easy to use


Position of OSIRIS webtool


General concept of OSIRIS tool

WP 4.2 Tool

sorts to type of info

adds weight to type of info

or

identifies datagap

or

asks expert input

makes an assessment

compares with ‘golden standard’

information, and concludes on:

C & L

RA

concludes on additional

information needed

consults ITS and library of options

ITS library of

options

webtool

Input

Output

Predefined questionaire?


General concept of OSIRIS tool

WP 4.2 Tool

sorts to type of info

adds weight to type of info

or

identifies datagap

or

asks expert input

makes an assessment

compares with ‘golden standard’

information, and concludes on:

C & L

RA

concludes on additional

information needed

consults ITS and library of options

ITS library of

options

webtool

Input Generate new test data

Predefined questionaire?


‘pilot webtool’

SETAC - October 24, 2008EU Working Group on QSARs - OSIRIS

OSIRIS webtool features – input & output

Input

Only public databases are used

Accepts testing data introduced by the end user

Testing data introduced by a specific user are not used in the

process of another user

Allows to include expert judgment in selected phases

Output

A report describing the whole process

It indicates what (testing) data is required to satisfy information

requirements

Can be tuned to minimize costs or animal use


Concluding remarks

• WoE: yet no prototype……..

• Assesses and ‘adding’ weight to information is being worked on

• Positioning webtool in very dynamic field needs attention

• Very first webtool pilot on mutagenicity; only testing sofar

• A long way to go… there is an urgent need


Acknowledgements

Istituto Di Ricerche Farmacologiche ‘Mario Negri’

University of Rovira I Vergilli

Procter & Gamble

Fraunhofer Institut, University of Berlin, UFZ, DIALOGIK

Joint Research Centre

SIMPPLE

NICBP

RIVM, University of Wageningen, TNO

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Integration of non-testing tools: a weight of evidence...

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