Good Read-Across Practice 1: State of the Art of Read-Across for - - PowerPoint PPT Presentation

Good Read-Across Practice 1: State of the Art of Read-Across for Toxicity Prediction

Mark Cronin Liverpool John Moores University England

Acknowledgement

What I am Going to Say…

• Background and context
• State of the art of read-across

– Practical issues – Quantification – Supporting read-across – Tools – Guidance – Case Studies – Acceptance

These are my views and others may wish to dissociate themselves from them

Good Read- Across Practice

Category Formation (Grouping) for Read Across

• Read-across uses information from members of a

group of similar compounds, with known activity, to predict activity of unknown(s)

OH OH OH OH

Toxicity

SAR / Read- Across

Toxicity

Interpolation

Some Good Reasons for Using Read-Across

• Its simple, cheap and transparent
• It has regulatory acceptance (if done correctly)
• Provides solutions to problems

Potential Uses of Read-Across

– REACH and other global legislation

• New and existing chemicals
• Prioritisation, C&L, Risk Assessment

– New product risk assessment (e.g. industry) – New product registration – AOP / IATA Framework – Nanomaterials – Pharmaceuticals – development – Pharmaceuticals – impurities – Legal highs / illicit drugs – Others

Example of a Category: Long-Chain Alcohols

Veenstra G et al (2009) Ecotox Environ Saf 72: 1016-1030.

Example of a Category: Terephthalic Acid and Esters

Ball GL et al (2012) Crit Rev Toxicol 42: 28-67.

QUESTION: Can We Fill These Data Gaps?

Ball GL et al (2012) Crit Rev Toxicol 42: 28-67.

Can We Fill These Data Gaps?

Ball GL et al (2012) Crit Rev Toxicol 42: 28-67.

Probably…. If we have….

• High quality “source” data
• Consistency within the data for the category
• We are interpolating
• There is a good reason and justification for

data gap filling

• We can demonstrate similarity

Well Known, and Worrying, Activity Cliffs Exist Which Demonstrate Problem of Identifying Similar Compounds

Teratogen Sedative

Are These Similar Molecules?

Fingerprint Tanimoto maccs 0.77 fp4 0.67 fp2 0.64 fp3 0.50

Similarity is More Than Similarity in Chemical Structure

Strong Skin Sensitiser Non Sensitiser

OH OH OH

Structural Analogues Mechanistic Analogues

Mode of Action Analogues

O O O OH N O

OH

O H OH O H OH O H

Guide to Grouping Chemicals

• Compounds that are metabolised to a

common molecule

• Compounds that are degraded rapidly to

common products

• Metrics of molecular similarity

Other Options for Grouping Chemicals

Like it or Not… The Use of Read-Across is a Reality

Developmental toxicity (1 882 dossiers) Toxicity to reproduction (1 882 dossiers covering phase–in substances 100-1 000 tpa)

Full Report Published 2 June 2014 available at: http://echa.europa.eu/documents/10162/13639/alternatives_test_animals_2014_en.pdf

Growth in Publications

Web of Science literature search using key words “Read- Across” and “Toxic” performed 20 February 2016

Like it or Not… The Use of Read-Across is a Reality

Developmental toxicity (1 882 dossiers) Toxicity to reproduction (1 882 dossiers covering phase–in substances 100-1 000 tpa)

Full Report Published 2 June 2014 available at: http://echa.europa.eu/documents/10162/13639/alternatives_test_animals_2014_en.pdf

However the acceptance of read- across predictions is not fully known

Key Issues with Read-Across

• How can we support a read-across prediction?

– i.e. provide further (biological) evidence that chemicals belong to a group

• When do read-across predictions become

acceptable to replace an animal test?

State of the Art of Read-Across and Good Read-Across Practice

Practical Issues with Undertaking Read-Across

Similarity is a Simple and Fundamental Concept Difficult and Subjective

Well recognised approaches Much guidance Consideration of endpoint to identify best approach

Assuring Category Membership

Confirmation and Evidence Required

Proof is essential for regulatory acceptance Identification and reduction of uncertainties Support from New Methods Data / Biological Similarity

Good Read-Across Practice

Practical Issues with Undertaking Read-Across

Defining Uncertainty

Can be Described R-A Arguments, Data, TK etc

Some uncertainty, context dependent, must be considered acceptable Criteria for defining uncertainty proposed but not necessarily accepted Further effort required

Good Read-Across Practice

Practical Issues with Undertaking Read-Across

Biological Data

Various Resources Assessing and Assigning Quality

Increasing data availability e.g. eChemPortal, ECHA DB etc New methods data e.g. HTS, Tox21 Biological profiling will support read-across

Good Read-Across Practice

Specific Use Case Scenarios

Confirming the Presence of Toxicity

Many Case Studies

Good examples for e.g. reactive toxicity Some areas more effort e.g. receptor mediated toxicity

No / Low Toxicity

Difficult to Confirm No Toxicity

Few robust categories, map onto OECD / HPVC? Similarity in toxicokinetics may need to be proven Effort needed in using biological similarity

Good Read-Across Practice

Other Area: Nanomaterials, Mixtures, UVCBs

Supporting Mechanistically-Based Read-Across

AOPs

Clear Linkages to Category Formation Supports Hypothesis

• f Toxicity

Molecular Initiating Events form the basis of grouping Data from assays for key events may confirm category membership Data from key events may be quantitative May form the basis of ITS / IATA, case studies required

Good Read-Across Practice

Quantification of Read-Across

How to Quantify R-A

Qualitative R-A is the current norm Some examples

Appreciation of (PB)PK modelling will be required Effort needed on how to incorporate new methods data More understanding, e.g. through case studies, is needed

Toxicokinetics

Very important, little addressed Few data

Requires more data and understanding May support quantification, similarity assessment

Good Read-Across Practice

Chemoinformatics: Tools for Grouping, Databases, Predictions of Toxicity, Metabolism etc

Tools and Databases – Not An Exhaustive List

Tool Grouping Tox Data ADME Mechanism Free Tox/Track

Yes Partial Yes Some Yes

DrugMatrix

Yes Few Some Yes Few No Yes Yes

• Many bespoke tools for grouping and read-across
• May need further guidance / illustrated case studies

Tools and Databases – Not An Exhaustive List

Tool Grouping Tox Data ADME Mechanism Free Tox/Track

Yes Partial Yes Some Yes

DrugMatrix

Yes Few Some Yes Few No Yes Yes

• Many data sources support read-across
• Always opportunities for further data sharing

Tools and Databases – Not An Exhaustive List

Tool Grouping Tox Data ADME Mechanism Free Tox/Track

Yes Partial Yes Some Yes

DrugMatrix

Yes Few Some Yes Few No Yes Yes

• (Quantitative) metabolite and PK property prediction requires

development and better integration into read-across

Tools and Databases – Not An Exhaustive List

Tool Grouping Tox Data ADME Mechanism Free Tox/Track

Yes Partial Yes Some Yes

DrugMatrix

Yes Few Some Yes Few No Yes Yes

• A mechanistic basis to read-across is desirable
• AOPs may support read-across in a number of ways

Several Other Initiatives

Current Guidance

• Many sources
• Need for consistent approach to reporting and assessing

read-across

• Adoption of ECHA’s Read-Across Assessment Framework

(RAAF) and ensure effectiveness

Four repeat dose RA case studies Ten safety assessments using RA

Several Other Initiatives

Case Studies

• Many examples
• Need for more to address

issues such as RAAF, uncertainty, reporting, biological profiling etc

Acceptance of Read-Across

• Variable
• Addressed in next talk

(Some) Key Points

• Getting the documentation right
• Read-across argument
• Acceptable level of uncertainty

Conclusions

• Practical issues affecting read-across have

been identified, if not resolved

• Useful tools and databases
• Much guidance and opinion
• Less certainty about certainty…
• Acceptance variable

Acknowledgements

• The European Community’s Seventh Framework

Program (FP7/2007-2013) COSMOS Project under grant agreement n° 266835 and Cosmetics Europe

• The CAAT GRAP Drafting Groups
• Co-workers in Liverpool, EU, USA