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Group 1B: Suitable Top Concentration for Tests with Mammalian Cells -MLA Workgroup-. 5 TH INTERNATIONAL WORKSHOP ON GENOTOXICITY TESTING Basle, August 17-19, 2009. Martha Moore Chair Masa Honma Co-chair Julie Clements Rapporteur Takumi Awogi George Douglas Aoi Kimura Wolfgang Muster

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group 1b suitable top concentration for tests with mammalian cells mla workgroup

Group 1B: Suitable Top Concentration for Tests with Mammalian Cells-MLA Workgroup-

5TH INTERNATIONAL WORKSHOP

ON GENOTOXICITY TESTING

Basle, August 17-19, 2009

workgroup members
Martha Moore Chair

Masa Honma Co-chair

Julie Clements Rapporteur

Takumi Awogi

George Douglas

Aoi Kimura

Wolfgang Muster

Mike O’Donovan

Rita Schoeny

Freddie van Goethem

Bhaskar Gollapudi*

Shinobu Wakuri*

* Unable to attend

Affiliations of panel:

4 regulatory, 4 pharma, 2 CRO

One representative of the chemical industry in audience

Workgroup members
agenda items for discussion
Agenda items for discussion
  • Listing the various regulatory decisions/uses for MLA data
  • Appropriate Gold Standard to which MLA data should be compared
  • Re-evaluation of NTP MLA data using the current IWGT recommendations
  • Recommended top concentration for non pharmaceuticals
  • Proposals and conclusions
regulatory decisions utilising mla data
Regulatory decisions utilising MLA data
  • Pre clinical safety evaluation for potential carcinogens
  • Identification of mutagens (mutation is the endpoint of concern)
  • Support for hazard identification (weight of the evidence to address question - is chemical a mutagen or carcinogen?)
  • Use for hazard assessment/Mode of Action and Risk Assessment
  • Classification and Labelling
discussion of gold standard to which mla data should be compared
Discussion of “Gold standard” – to which MLA data should be compared
  • In vitro gene mutation assays need to be evaluated against repeat dose in vivo mutation assays
  • Using mutation as a surrogate for cancer does not , and would not be expected to, give a perfect correlation with carcinogenicity
  • Gold Standard is not readily available
observations
Observations
  • Acceptance criteria and data interpretation (Neg/Pos) for the assay well established
  • In some circumstances it is important to understand the mechanism/mode of action for mutation induction within the MLA itself – follow up studies
observations 2
Observations 2
  • Pharmaceuticals often have high molecular weights
  • The average molecular weight of the chemicals that go through testing in the chem/agchem world is approximately 250
observations 3
Observations 3

Straw poll

  • Participants, both workgroup and audience, were asked to indicate their support for the ICH proposal for pharmaceuticals to lower top concentration from 10mM to 1mM
    • Workgroup 7 For, 3 Against
    • Audience 9 For, 3 Against
ntp mla data re analysis

NTP MLA Data Re-analysis

Bhaskar Gollapudi, Melissa Schisler, & Martha Moore

(NOTE: Not workgroup analysis)

re analysis approach
Re-analysis Approach
  • So far, analyzed 244 chemicals using data from NTP publications
  • IWGT criteria, decision rules, and expert judgment used to classify chemical assay responses into
    • Positive
    • Equivocal
    • Inconclusive
    • Negative
      • Lack of colony sizing data precluded negative classification (with one exception – water!)
  • Data were examined for
    • Background CE (65-120) and MF (35-140)
    • MF of positive control (IMF >300 at RTG>10%)
    • Dose selection (at least one dose between 10-20% RTG)
    • Data consistency
preliminary data unaudited
Preliminary Data (unaudited)

REANALYSIS CALL

NTP CALL

take home messages
Take Home Messages
  • Careful reanalysis of NTP MLA data using current standards is in progress.
  • A significant proportion of NTP experiments are not valid by current standards
    • Low background MF
    • Low induced MF in positive controls
  • NTP Positive calls were often based on MF data below 10% RTG.
  • Strict adherence to IWGT acceptance criteria would have resulted in substantially more tests as Inconclusive calls
  • Approximately 50% of the positive calls in the NTP data may need re-testing.
  • Use of NTP calls in deriving correlations (e.g., to carcinogenicity) may lead to inaccurate conclusions.
iwgt mla workgroup conclusions
IWGT MLA Workgroup Conclusions
  • Consensus that top concentration for testing (10 mM) needs to be re-considered and further evaluated
  • Several proposals put forward
  • Each one discussed and voted upon
    • Number of workgroup members ready to support proposal based on available information
    • Number of workgroup members felt proposal had merit and should be further developed, investigated and evaluated
proposal number 1
Proposal Number 1
  • Top concentration 1000 µg/ml or 10 mM whichever is lower (BG proposal)
    • Number of workgroup members ready to endorse this now – 0
    • Number of workgroup members who consider it is a viable proposition warranting further evaluation - 6
proposal number 2
Proposal Number 2
  • Lower top concentration for non pharmaceuticals to 1 mM
    • Number of workgroup members ready to endorse this now – 6
    • Number of workgroup members who consider it is a viable proposition warranting further evaluation - 3
proposal number 3
Proposal Number 3
  • Lower top concentration for non pharmaceuticals to 2 mM
    • Number of workgroup members ready to endorse this now – 1
    • Number of workgroup members who consider it is a viable proposition warranting further evaluation - 6
proposal number 4 for complex mixtures
Proposal Number 4 for Complex Mixtures
  • For complex mixtures, top concentration proposed to be 5000 µg/ml (or as high as considered appropriate in each case)
    • Number of workgroup members ready to endorse this now – 4
    • Number of workgroup members who consider it is a viable proposition warranting further evaluation - 3
issues needing further discussion
Issues needing further discussion
  • Agree on data required and Gold Standard for evaluation
  • Agree what level of concordance is required
  • Formulate strategy to obtain data
  • Make data driven decision