@David et al. published a new paper describing AI setting for nitrosamines with CPCA, read across, a tiered TTC-like approach, and so on. I could only read a part of the content now, but I’m curious about how the AI setting will develop in the full paper.
Abstract
The carcinogenic potency categorisation approach (CPCA) has recently been introduced by health authorities. In this model, structural features from recent literature, industry proposals, and analyses performed by health authorities, provide a rapid assessment of the potential acceptable intake (AI) for a nitrosamine impurity. As with other screening regulatory values (such as the ICH M7 Threshold of Toxicological Concern), the CPCA is conservative and can be considered a de minimis risk management framework. In cases where a nitrosamine drug substance-related impurity (NDSRI) is present below the CPCA limit, the framework provides resolution from a toxicological perspective (i.e., no further toxicology studies are required). Where an NDSRI is above the CPCA limit, the framework provides for the initiation of additional activities (i.e., the CPCA is not the only possible limit). Read-across approaches are described in both the CPCA and M7 guidance and can provide a limit with more specific applicability than the general model. The use of available experimental data (in vitro or in vivo), is valuable in order to provide an even more specific limit. The CPCA provides a framework; however, data should permit changing the AI from initial structural assessment, based on increasing data, to ultimately increase precision of the AI.
I am reading it too. Had a short conversation with Joel Bercu during the workshop of Nov 2024. I guess recalibrating the AIs of CPCA Category 1 (some of which are ludicrous) may be a primary focus.
I agree with you, Aloka. His suggestion in CRCG was amazing!! Using the potency of the TGR assay is crucial for improving the AI beyond CPCA.
Dr. Kruhlak from CDER also stated positively in CRCG about improving the CPCA by adding new deactivating features or using physicochemical parameters such as molecular weight. We are currently on the road.
i think that this paper is one of the most important which have been written regarding the acceptance intakes and i believe that will be the base for the second milestone in AIs after the implementation of CPCA.
Thankyou for your kind words! We hope that it will have the impact you predict, and as a result are planning that the paper will be freely available once the proofs have been returned, we’re processing the open access payment now and I’m working through the proofs!
To confirm - the Open Access has gone through, and I’ve just sent back the proofs, so it’s available as a pre-print now and should be available fully-formatted with very minor changes
Happy 2025 to all … Great article and kudos to @David et al.
David, I hope you can help answer few reflecting questions for us:
1. Challenges in Carcinogenic Potency Categorization
The article highlights the conservative nature of the CPCA framework and its reliance on structural features for potency categorization.
Question: In your experience, what are the most significant challenges in applying the CPCA framework to diverse nitrosamine impurities, and how might these challenges be addressed in future iterations of the framework?
2. Role of Experimental Data in Refining AI Limits
The article emphasize the importance of integrating experimental data, such as in vitro or in vivo studies, to refine acceptable intake (AI) limits.
Question: How can the industry better collaborate with regulators to streamline the process of generating and incorporating robust experimental data into CPCA-derived AI limits?
3. Balancing Conservatism and Feasibility
The article mentions that highly conservative AI limits can pose significant challenges for smaller manufacturers and may lead to drug shortages.
Question: What strategies can be implemented to ensure the CPCA framework maintains patient safety while also being practical for manufacturers with limited resources?
4. Global Regulatory Harmonization
Variability in AI limits among regulatory agencies has been noted as a challenge.
Question: How can the CPCA framework serve as a foundation for achieving greater global harmonization in the assessment and control of nitrosamine impurities?
5. Future Directions for CPCA Refinement
The article suggests several potential refinements to the CPCA framework, including a more comprehensive understanding of structural features and their impact on carcinogenic potency.
Question: What additional structural or physicochemical parameters do you believe should be prioritized in future updates to the CPCA framework to improve its predictive power?
I believe it is, yes - we went back and forth between displaying TD50 (e.g. 0.0265 mg/kg/day) and AI (0.0265 ug/day). I will email the editor and hopefully catch them before the issue (Feb 2025) goes to print.
