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.

The rate of diffusion of small molecules within polymer matrices is important in an enormous scope of practical scenarios. However, it is challenging to perform direct measurements of each system of interest under realistic conditions. Free volume theories have proven capable of predicting diffusion coefficients in polymers but often require large amounts of physical constants as input. Therefore, we adapted a version of the Vrentas–Duda free volume theory of diffusion such that the necessary parameters may be obtained from a limited set of diffusion data collected at the temperature of interest using commercially available and automated sorption equipment. This approach correlates the size and shape of molecules to their trace diffusion coefficient, D, such that D of very large, solid diffusants can be predicted based on properties measured for condensable vapor diffusants. Our analysis was based on the volume-averaged transport properties of polyaromatic color additives within segmentally arranged poly­(ether-block-amide) (PEBAX) block copolymer matrices. At very high polyamide content the considerable plasticization effects due to absorbed water can be accommodated by increasing the available hole free volume as a function of water content. Alternatively, if the release rate of additives is measured for very high polyether content and degree of swelling, the release rate in the unswollen elastomer may be anticipated using the tortuosity model of Mackie and Meares. Agreement of these physical models to new experimental data provides a scientific basis for accurately predicting the in vivo leaching of aromatic additives from medical device polymers using accelerated and/or simplified in vitro methodologies.

Microwave-assisted extraction (MAE) of phenolic antioxidants from the pomace of Red Delicious and Jonathan apple varieties was optimized using response surface methodology. Optimization parameters included solvent type, microwave power, solvent volume to sample ratio and extraction time. Optimum conditions were based on the total polyphenol content (TPC) of extracts. Antioxidant activities of optimized extracts were also measured by inhibition percentage (IP) of the DPPH (2,2-diphenyl-1-picrylhydrazyl) free radical. High-performance liquid chromatography was used to identify and quantify some of the major phenolics extracted. Red Delicious pomace had the highest TPC (15.8 mg GAE/g) obtained under the optimum extraction conditions of 735 W power and 149 s extraction time with 10.3 mL of ethanol per gram dry sample. The DPPH IP of this extract was 77.1%. Phloridzin, caffeic acid, chlorogenic acid and quercetrin were some of the major polyphenols identified in the extracts. MAE was found to be an effective method of extracting antioxidant compounds from apple pomace. PRACTICAL APPLICATIONSExtraction of phenolics from apple pomace using microwave-assisted extraction (MAE) has significant potential compared with traditional extraction methods, as it significantly reduces extraction time and solvent consumption while generating higher extraction yields. The optimized extraction conditions obtained in this study resulted in extracts with high concentrations of polyphenols and high DPPH (2,2-diphenyl-1-picrylhydrazyl) radical-scavenging activity. Optimized extraction conditions were found to be independent of apple variety and therefore can be extended to extraction of phenolics from the pomace of other apple cultivars. This work opens the door for further research on the feasibility of an industrial-scale continuous MAE process for the recovery of these valuable compounds from apple pomace. In addition, there is promise for these value-added extracts to be used in a number of applications, including the extension of product shelf life (as an alternative to synthetic antioxidants), functional food ingredients and dietary supplements.

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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 cm/s, and matrix solubility limit, C = 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.

Many polymeric medical device materials contain color additives which could lead to adverse health effects. The potential health risk of color additives may be assessed by comparing the amount of color additive released over time to levels deemed to be safe based on available toxicity data. We propose a conservative model for exposure that requires only the diffusion coefficient of the additive in the polymer matrix, D, to be specified. The model is applied here using a model polymer (poly(ether-block-amide), PEBAX 2533) and color additive (quinizarin blue) system. Sorption experiments performed in an aqueous dispersion of quinizarin blue (QB) into neat PEBAX yielded a diffusivity D 5 4.8 3 10 210 cm 2 s 21 , and solubility S 5 0.32 wt %. On the basis of these measurements, we validated the model by comparing predictions to the leaching profile of QB from a PEBAX matrix into physiologically representative media. Toxicity data are not available to estimate a safe level of exposure to QB, as a result, we used a Threshold of Toxicological Concern (TTC) value for QB of 90 mg/adult/day. Because only 30% of the QB is released in the first day of leaching for our film thickness and calculated D, we demonstrate that a device may contain significantly more color additive than the TTC value without giving rise to a toxicological concern. The findings suggest that an initial screening-level risk assessment of color additives and other potentially toxic compounds found in device polymers can be improved.

Understanding the release kinetics of antimicrobials from polymer films is important in the design of effective antimicrobial packaging films. The release kinetics of nisin (30 mg/film) from chitosan-alginate polyelectric complex films prepared using various fractions of alginate (33%, 50%, and 66%) was investigated into an aqueous release medium. Films containing higher alginate fractions showed significantly lower (P < 0.05) degree of swelling in water. Total amount of nisin released from films into an aqueous system decreased significantly (P < 0.05) with an increase in alginate concentration. The mechanism of diffusion of nisin from all films was found to be Fickian, and diffusion coefficients varied from 0.872 × 10 to 8.034 ×10 cm /s. Strong complexation was confirmed between chitosan and alginate polymers within the films using isothermal titration calorimetry and viscosity studies, which affects swelling of films and subsequent nisin release. Complexation was also confirmed between nisin and alginate, which limited the amount of free nisin available for diffusion from films. These low-swelling biopolymer complexes have potential to be used as antimicrobial packaging films with sustained nisin release characteristics.

The developers of medical devices evaluate the biocompatibility of their device prior to FDA’s review and subsequent introduction to the market. Chemical characterization, described in ISO 10993-18:2020, can generate information for toxicological risk assessment and is an alternative approach for addressing some biocompatibility end points (e.g., systemic toxicity, genotoxicity, carcinogenicity, reproductive/developmental toxicity) that can reduce the time and cost of testing and the need for animal testing. Additionally, chemical characterization can be used to determine whether modifications to the materials and manufacturing processes alter the chemistry of a patient-contacting device to an extent that could impact device safety. Extractables testing is one approach to chemical characterization that employs combinations of non-targeted analysis, non-targeted screening, and/or targeted analysis to establish the identities and quantities of the various chemical constituents that can be released from a device. Due to the difficulty in obtaining a priori information on all the constituents in finished devices, information generation strategies in the form of analytical chemistry testing are often used. Identified and quantified extractables are then assessed using toxicological risk assessment approaches to determine if reported quantities are sufficiently low to overcome the need for further chemical analysis, biological evaluation of select end points, or risk control. For extractables studies to be useful as a screening tool, comprehensive and reliable non-targeted methods are needed. Although non-targeted methods have been adopted by many laboratories, they are laboratory-specific and require expensive analytical instruments and advanced technical expertise to perform. In this Perspective, we describe the elements of extractables studies and provide an overview of the current practices, identified gaps, and emerging practices that may be adopted on a wider scale in the future. This Perspective is outlined according to the steps of an extractables study: information gathering, extraction, extract sample processing, system selection, qualification, quantification, and identification.