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CHemical RISk calculators (CHRIS) – Color Additives (v2)

Catalog of Regulatory Science Tools to Help Assess New Medical Devices 

 

This regulatory science tool presents a computer model that enables users to conduct screening level risk assessments to aid in the biocompatibility evaluation of f polymeric medical device components that contain color additives (CAs).

 

Technical Description

The CHemical RISk calculator (CHRIS) – Color Additives (version 2)External Link Disclaimer enables users to conduct screening level risk assessments by providing immediate feedback on whether the presence of a CA would require additional justification or testing, or both to demonstrate acceptable biological risk in the FDA’s premarket review.

The principle of operation relies on first derivation of tolerable intake (TI) values and then the establishment of a model to predict exposure limited only by the diffusive transport of the additive through the polymer matrix. The model is parameterized using a constitutive model for diffusion coefficient (D) as a function of molecular weight (Mw) of the color additive. After segmenting polymer matrices into 8 distinct categories, upper bounds on D(Mw) were determined based on available data for each category. The upper bounds and exposure predictions were validated independently to provide conservative exposure estimates. Because both components (toxicity and exposure) are conservative, a ratio of tolerable intake to exposure in excess of one indicates acceptable risk.

CHRIS – Color Additives (v2) applies a CA-specific toxicological threshold value called a tolerable intake (TI) value for the following CAs: titanium dioxide, carbon black, pigment brown 24, zinc oxide, pigment red 101, solvent violet 13, manganese phthalocyanine, pigment blue 15, phthalocyanine green, ultramarine blue, and pigment yellow 138. These TIs are based on available systemic (including reproductive/developmental, genotoxicity, and carcinogenicity) toxicity data. If   adequate toxicological data for a CA (or associated additives and impurities) is not available, CHRIS – Color Additives (v2) conducts a toxicological risk assessment for systemic biocompatibility endpoints by comparing the exposure estimate of the CA, associated additive, or impurities in the matrix to an appropriate threshold of toxicological concern (TTC). The output of this tool is a conservative margin of safety (MOS = TTC or TI ÷ exposure dose) value for a CA contained within a polymeric medical device component. Based on the MOS value, the calculator determines if further assessment of one or more biocompatibility endpoints is necessary for the specific CA. Because both the TTC and TI approaches are based on systemic toxicity, CHRIS – Color Additives (v2) can address acute systemic toxicity, subacute/subchronic toxicity, genotoxicity, carcinogenicity, and reproductive and developmental toxicity.

The CHRIS – Color Additives (v2)External Link Disclaimer incorporates more accurate (yet still conservative) models, addresses more polymers, and removes the limitation on the solute molecular weights that can be considered when compared to the CHRIS – Color Additives (v1).

Intended Purpose

This calculator provides clinically relevant, yet still conservative, exposure dose estimates using a physics-based transport model for polymeric systems where transport data are available to support the use of the model. The model applies worst-case boundary conditions for release of a CA from the polymer matrix and is based on the following five primary assumptions:

  • The clinical use environment does not cause the polymer matrix to swell or degrade.
  • Manufacturing processes do not impact the stability of the polymer.
  • The CA is homogeneously distributed throughout the polymer.
  • The total amount of the CA is present in dilute concentrations (≤ 2 m/v %).
  • Color additive particles/aggregates present in the polymer are much smaller than the smallest component dimension (≤ 50x).

While these assumptions are typically valid for CAs in biostable polymers, the user must confirm conformance to the underlying assumptions or provide supporting justification to ensure compliance for a given system. Further, this calculator only enables system specific exposure estimates for 53  polymeric systems that are generally biostable (non-swelling and non-degrading). To estimate CA release based on the model, the diffusion coefficient of the CA in the polymer matrix must be specified. For the 53 polymeric systems, a worst-case (upper bound) diffusion coefficient, as a function of molecular weight, has been established based on data from the literature. For polymer matrices that are not included in this list, the tool assigns an ultra-conservative diffusion coefficient that assumes the polymer has the properties of water.

Additional information is available on the Context of Use and Supplemental Publication InformationExternal Link Disclaimer.

Testing

CHRIS – Color Additives (v2) was developed to provide screening level toxicological risk assessments that are protective, not predictive. The rate of release of specific CAs has been measured under laboratory conditions that favor maximum release rates [1], and these measured release rates were compared with the predicted rate from the tool. The testing demonstrated that the tool overestimates the rate of exposure by 100-10000x compared with the rates observed under the worst-case experimental conditions and as such provides a very conservative approach to determining exposure and margins of safety. The new upper bounds on D(Mw) in reference [3] were derived using a similar approach as reference [1] but with more than 5x the amount of experimental diffusion data, which allowed the creation of more accurate yet still conservative bounds that address more polymers and solutes. These new bounds demonstrate a similar level of conservatism as the previous bounds, that is, they overestimate exposure by 100-10000x.

Details provided in:

Note: After the publication of reference [3], additional data were located that justify the inclusion of several additional polymer matrices: poly(methyl acrylate) [10-14], poly(ethyl acrylate) [8], [9], [11], poly(butyl acrylate) [9], [12], [13], poly(ethyl cyanoacrylate) [14], poly(butyl cyanoacrylate) [14], and poly(hexyl cyanoacrylate) [14].

Additionally, the upper bounds on D(Mw) using the 95th percentile of the data were recalculated in place of the statistical procedure in reference [3]. That statistical procedure incorrectly assumes a normal distribution. Using the percentile is a robust, distribution-independent method to ensure the upper bounds are protective.

Limitations

  1. The tool only addresses CAs with a distribution that is macroscopically homogeneous within the matrix.
  2. The tool requires the total amount of the CA to be established in advance, e.g., based on a certificate of analysis.
  3. The tool only addresses individual color additives; therefore, a favorable outcome by the tool does not imply acceptable biological risk for the final finished form of a medical device.
  4. The tool cannot be used to screen the potential risk of polymer medical device components that contact the body by the inhalation route.
  5. Under the information (i) icon button next to Device characteristics, the discussion of ‘Exposure type’ states that, “≤ 24 hours = limited. For limited exposures (≤ 24 hours), please enter the maximum exposure time in hours.” For additional information on device contact classification, it is recommended that users refer to the FDA’s Biocompatibility Guidance for current thinking on how to determine the device’s contact classification or exposure type.
  6. The tool is limited to color additives. For other bulk chemicals, use the CHRIS – Bulk Chemicals (v1)External Link Disclaimer or CHRIS – Bulk Chemicals (v2)External Link Disclaimer.
  7. Some of the color additives listed in this tool are not all listed under 21 CFR 73 Subpart D and 21 CFR 74 Subpart D as color additives appropriate to use in medical devices for additional information on appropriate use of CAs it is recommended that users refer to the device specific guidances, and what is allowed per the CFR.

Supporting Documentation

  1. Saylor, D. M., Chandrasekar, V., Simon, D. D., Turner, P., Markley, L. C., & Hood, A. M. (2019). Strategies for rapid risk assessment of color additives used in medical devices. Toxicological Sciences, 172(1), 201-212. https://doi.org/10.1093/toxsci/kfz179External Link Disclaimer
  2. Saylor, D. M., Chandrasekar, V., Elder, R. M., & Hood, A. M. (2020). Advances in predicting patient exposure to medical device leachables. Medical Devices & Sensors, 3(1), e10063. https://doi.org/10.1002/mds3.10063External Link Disclaimer
  3. Elder, R. M., Saylor, D. M. (2023). Robust estimates of solute diffusivity in polymers for predicting patient exposure to medical device leachables. Journal of Polymer Science, available online. https://doi.org/10.1002/pol.20230219External Link Disclaimer
  4. H. Fujita, A. Kishimoto, K. Matsumoto, Concentration and temperature dependence of diffusion coefficients for systems polymethyl acrylate and n-alkyl acetates. Transactions of the Faraday Society, 56, 424-437 (1960). https://doi.org/10.1039/TF9605600424External Link Disclaimer
  5. Kishimoto, E. Maekawa, H. Fujita, Diffusion Coefficients for Amorphous Polymer and Water Systems. Bulletin of the Chemical Society of Japan, 33, 988-992 (1960). https://doi.org/10.1246/bcsj.33.988External Link Disclaimer
  6. W. H. Burgess, H. B. Hopfenberg, V. T. Stannett, Transport of noble gases in poly(methyl acrylate). Journal of Macromolecular Science, Part B 5, 23-40 (1971). https://doi.org/10.1080/00222347108212519External Link Disclaimer
  7. J. S. Chiou, J. W. Barlow, D. R. Paul, Sorption and transport of gases in miscible poly(methyl acrylate)/poly(epichlorohydrin) blends. Journal of Applied Polymer Science, 30, 1173-1186 (1985). https://doi.org/10.1002/app.1985.070300322External Link Disclaimer
  8. Z. Mogri, D. R. Paul, Gas sorption and transport in poly(alkyl (meth)acrylate)s. II. Sorption and diffusion properties. Polymer, 42, 7781-7789 (2001). https://doi.org/10.1016/S0032-3861(01)00260-9External Link Disclaimer
  9. S. Maji, O. Urakawa, K. Adachi, Relationship between segmental dynamics and tracer diffusion of low mass compounds in polyacrylates. Polymer, 48, 1343-1351 (2007). https://doi.org/10.1016/j.polymer.2006.12.039External Link Disclaimer
  10. D. W. Janes, J. S. Kim, C. J. Durning, Interval Sorption of Alkyl Acetates and Benzenes in Poly(methyl acrylate). Industrial & Engineering Chemistry Research 52, 8765-8773 (2013). https://doi.org/10.1021/ie300536cExternal Link Disclaimer
  11. Kishimoto, Y. Enda, Diffusion of benzene in polyacrylates. Journal of Polymer Science Part A: General Papers, 1, 1799-1811 (1963). https://doi.org/10.1002/pol.1963.100010530External Link Disclaimer
  12. J. Li, K. D. Sullivan, E. B. Brown, M. Anthamatten, Thermally activated diffusion in reversibly associating polymers. Soft Matter, 6, 235-238 (2010). https://doi.org/10.1039/B909662K
  13. G. S. Sheridan, C. M. Evans, Understanding the Roles of Mesh Size, Tg, and Segmental Dynamics on Probe Diffusion in Dense Polymer Networks. Macromolecules, 54, 11198-11208 (2021). https://doi.org/10.1021/acs.macromol.1c01767External Link Disclaimer
  14. W. R. Vezin, A. T. Florence, Diffusion of Small Molecules in Amorphous Polymers. Journal of Pharmacy and Pharmacology, 29, 44P-44P (1977). https://doi.org/10.1111/j.2042-7158.1977.tb11512.xExternal Link Disclaimer

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