Literature DB >> 28948381

Conservative Exposure Predictions for Rapid Risk Assessment of Phase-Separated Additives in Medical Device Polymers.

Vaishnavi Chandrasekar1, Dustin W Janes2, David M Saylor3, Alan Hood2, Akhil Bajaj4, Timothy V Duncan5, Jiwen Zheng2, Irada S Isayeva2, Christopher Forrey2, Brendan J Casey2.   

Abstract

A novel approach for rapid risk assessment of targeted leachables in medical device polymers is proposed and validated. Risk evaluation involves understanding the potential of these additives to migrate out of the polymer, and comparing their exposure to a toxicological threshold value. In this study, we propose that a simple diffusive transport model can be used to provide conservative exposure estimates for phase separated color additives in device polymers. This model has been illustrated using a representative phthalocyanine color additive (manganese phthalocyanine, MnPC) and polymer (PEBAX 2533) system. Sorption experiments of MnPC into PEBAX were conducted in order to experimentally determine the diffusion coefficient, D = (1.6 ± 0.5) × 10-11 cm2/s, and matrix solubility limit, C s = 0.089 wt.%, and model predicted exposure values were validated by extraction experiments. Exposure values for the color additive were compared to a toxicological threshold for a sample risk assessment. Results from this study indicate that a diffusion model-based approach to predict exposure has considerable potential for use as a rapid, screening-level tool to assess the risk of color additives and other small molecule additives in medical device polymers.

Entities:  

Keywords:  Color additive; Diffusion; Medical device; PEBAX; Risk assessment

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Year:  2017        PMID: 28948381     DOI: 10.1007/s10439-017-1931-4

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  1 in total

1.  The Ubiquitous Issue of Cross-Mass Transfer: Applications to Single-Use Systems.

Authors:  Phuong-Mai Nguyen; Samuel Dorey; Olivier Vitrac
Journal:  Molecules       Date:  2019-09-24       Impact factor: 4.411

  1 in total

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