ICH M7 Impact on DMF Review Process. David Green Quality Assessment Lead (acting) CDER/OPQ/ONDP/DLCAPI November 4, 2015

Transcription

1 ICH M7 Impact on DMF Review Process David Green Quality Assessment Lead (acting) CDER/OPQ/ODP/DLCAPI ovember 4,

2 Key steps the DMF reviewer will follow to implement M7 in their Review Process Reviewer will calculate the Threshold of Toxicological Concern (TTC) for API based on the Maximum Daily Dose (MDD) of the reference ADA and the Daily Intake per Duration of Treatment. Reviewer will look at the firm s synthesis and determine if there are any chemical compounds that contain structural alerts. If structural alerts are identified, the reviewer will follow the DMF Structural Alert Process to determine the appropriate response to the firm. 2

3 Example TTC calculation: Table generated in every DMF review that lists the ICH Q3A thresholds based on the MDD of the referenced ADA. The TTC is calculated by the reviewer and added to the table for reference. 1.5 µg/day Daily Intake is used for a drug product that has lifetime Duration of Use per M7. TTC is calculated by dividing Daily Intake/ MDD: 1. 5 µg g = µg/g or ppm If Duration of Use is not clearly defined or in question, OGD Clinical will be consulted to make appropriate determination. 3

4 M7 TTC Guidelines based on Duration of Action

5 Example Synthesis from Literature: (For illustration purpose only) C H + Cl O Cl C O Cl + C O H Cl H H Cl C (CH 2)4 C (CH 2)4 HCl - H O COOEt + C H O COR O COOEt Reviewer will identify structural alerts in the firm s synthesis. For consistency across all reviewers, the structural alerts will be defined per Müller Paper. Org. Process Res. Dev. 2012, 16,

6 Structural Alerts per Müller Paper (L. Müller et al. Regulatory Toxicology and Pharmacology 44 (2006) )

7 Example Synthesis from Literature: (For illustration purpose only) Cl C H C + O Cl Cl + O Cl C O H H H C (CH 2)4 C (CH 2)4 HCl - H O COOEt + C Cl H O COR O COOEt O r g. P rocess Res. D ev. 2012, 16,

8 M7 Classification

9 DMF Structural Alert Process 9

10 OGD Clinical will be consulted per current SOP. 10

11 The Computational Toxicology Group will be consulted per current SOP. 11

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13 DMF (Q)SAR Structural List (Internal Database) Folder ame -If DMF is in an ADA, ADA # given Highlighted Structure File ame (Hyperlinked) Ctrl + Click to go directly to file The list contains every structure submitted for (Q)SAR analysis from the DMF staff. The list does not give the (Q)SAR analysis results. The reviewer goes to the linked report for the expert conclusions. As of October 16, 2015 the list consists of 136 drug substances with 532 chemical structures. 13

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16 Suggested Deficiency Language: Impurity XYZ contains a structural alert for genotoxicity. Please include a process control for Impurity XYZ to ensure this impurity is below the TTC in the drug substance. Alternatively, in vitro / in vivo methods as described in ICH M7 to determine mutagenicity experimentally can be used. If upstream control is established at higher than the acceptable limit or where control is achieved through process capability, spike/purge studies at greater than the proposed limit and/or sufficient batch data from drug substance manufactured from intermediate containing the proposed levels of the impurity should be supplied to support this proposal. Batch size used for spike/purge studies, analytical methods and validation reports should be provided where necessary. 16

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18 CCRIS Database Chemical Carcinogenesis Research Information System (CCRIS) is a publicly accessible database maintained by ational Cancer Institute (CI). Organized by chemical record, this databank contains carcinogenicity, tumor promotion, tumor inhibition, and mutagenicity test results derived from the scanning of primary journals, current awareness tools, CI technical reports, review articles, and International Agency for Research on Cancer monographs published since Test results have been reviewed by experts in carcinogenesis. Please note, to access the CCRIS database through ChemIDplus and not through the TOXET database. 18

19 CCRIS Database Search Search by name Search by structure (good for complex molecules) 19

20 CCRIS Database Search Searched for Benzene using the name search. This is the result page Click on the CCRIS database link 20

21 CCRIS Database Search Another window will open with the CCRIS database results All that matters is if study data is available. We do not read or interpret any of the studies. If data is available a deficiency is triggered. 21

22 CCRIS Database Search If you preform a search and you get this screen or you get a screen that does not list the CCRIS database then you have a negative CCRIS search. egative search result 22

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24 Suggested Deficiency Language: We note that published literature indicates that impurity, XYZ, is potentially genotoxic. Please include a process control for XYZ to ensure this impurity is below the TTC in the drug substance. Alternatively, in vitro / in vivo methods as described in ICH M7 to determine mutagenicity experimentally can be used. If upstream control is established at higher than the acceptable limit or where control is achieved through process capability, spike/purge studies at greater than the proposed limit and/or sufficient batch data from drug substance manufactured from intermediate containing the proposed levels of the impurity should be supplied to support this proposal. Batch size used for spike/purge studies, analytical methods and validation reports should be provided (if they are available) where necessary. 24

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27 In Summary The DMF reviewers will implement ICH M7 in the DMF review process by: Calculate the Threshold of Toxicological Concern (TTC) and added to the Impurity Threshold Table. Look at the API synthesis and determine if there are chemical compounds that contain structural alerts. If structural alerts are identified, follow the DMF Structural Alert Process to determine the appropriate response to the firm. 27

28 Our Goal: Future Process Flow 28

29 Acknowledgements: David Skanchy, PhD. Barbara Scott, M.S. Steve Miller, Ph.D. aomi L. Kruhlak, Ph.D. Brian Connell, Ph.D. Lidiya Stavitskaya, Ph.D. Mark Powley, Ph.D. Thank You! 29