Strategies for Rapid Risk Assessment of Color Additives Used in Medical Devices
Many polymeric medical devices contain color additives for differentiation or labeling. Although some additives can be toxic under certain conditions, the risk associated with the use of these additives in medical device applications is not well established, and evaluating their impact on device bio...
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Veröffentlicht in: | Toxicological sciences 2019-11, Vol.172 (1), p.201-212 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Many polymeric medical devices contain color additives for differentiation or labeling. Although some additives can be toxic under certain conditions, the risk associated with the use of these additives in medical device applications is not well established, and evaluating their impact on device biocompatibility can be expensive and time consuming. Therefore, we have developed a framework to conduct screening-level risk assessments to aid in determining whether generating color additive exposure data and further risk evaluation are necessary. We first derive tolerable intake values that are protective for worst-case exposure to 8 commonly used color additives. Next, we establish 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 4 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 estimates. Because both components (toxicity and exposure) are conservative, a ratio of tolerable intake to exposure in excess of one indicates acceptable risk. Application of this approach to typical colored polymeric materials used in medical devices suggests that additional color additive risk evaluation could be eliminated in a large percentage (≈90%) of scenarios. |
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ISSN: | 1096-6080 1096-0929 |
DOI: | 10.1093/toxsci/kfz179 |