Chemical Characterization and Non-targeted Analysis of Medical Device Extracts: A Review of Current Approaches, Gaps, and Emerging Practices.

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.

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 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.

Predicting patient exposure to nickel released from cardiovascular devices using multi-scale modeling.

Many cardiovascular device alloys contain nickel, which if released in sufficient quantities, can lead to adverse health effects. However, in-vivo nickel release from implanted devices and subsequent biodistribution of nickel ions to local tissues and systemic circulation are not well understood. To address this uncertainty, we have developed a multi-scale (material, tissue, and system) biokinetic model. The model links nickel release from an implanted cardiovascular device to concentrations in peri-implant tissue, as well as in serum and urine, which can be readily monitored. The model was parameterized for a specific cardiovascular implant, nitinol septal occluders, using in-vitro nickel release test results, studies of ex-vivo uptake into heart tissue, and in-vivo and clinical measurements from the literature. Our results show that the model accurately predicts nickel concentrations in peri-implant tissue in an animal model and in serum and urine of septal occluder patients. The congruity of the model with these data suggests it may provide useful insight to establish nickel exposure limits and interpret biomonitoring data. Finally, we use the model to predict local and systemic nickel exposure due to passive release from nitinol devices produced using a wide range of manufacturing processes, as well as general relationships between release rate and exposure. These relationships suggest that peri-implant tissue and serum levels of nickel will remain below 5 µg/g and 10 µg/l, respectively, in patients who have received implanted nitinol cardiovascular devices provided the rate of nickel release per device surface area does not exceed 0.074 µg/(cm2 d) and is less than 32 µg/d in total. STATEMENT OF SIGNIFICANCE: The uncertainty in whether in-vitro tests used to evaluate metal ion release from medical products are representative of clinical environments is one of the largest roadblocks to establishing the associated patient risk. We have developed and validated a multi-scale biokinetic model linking nickel release from cardiovascular devices in-vivo to both peri-implant and systemic levels. By providing clinically relevant exposure estimates, the model vastly improves the evaluation of risk posed to patients by the nickel contained within these devices. Our model is the first to address the potential for local and systemic metal ion exposure due to a medical device and can serve as a basis for future efforts aimed at other metal ions and biomedical products.

Characterizing the free volume of ultrahigh molecular weight polyethylene to predict diffusion coefficients in orthopedic liners.

Liners used in orthopedic devices are often made from ultrahigh molecular weight polyethylene (UHMWPE). A general predictive capability for transport coefficients of small molecules in UHMWPE does not exist, making it difficult to assess properties associated with leaching or uptake of small molecules. To address this gap, we describe here how a form of the Vrentas-Duda free volume model can be used to predict upper-bound diffusion coefficients (D) of arbitrary molecules within UHMWPE on the basis of their size and shape. Within this framework, the free-volume microstructure of UHMWPE is defined by analysis of a curated set of model diffusants. We determined an upper limit on D for vitamin E, a common antioxidant added to UHMWPE, to be 7.1 × 10-12 cm2  s-1 . This means that a liner that contains 0.1 wt % or less Vitamin E and has <120 cm2 patient contacting surface area would elute <100 µg/day of vitamin E. Additionally, the model predicts that squalene and cholesterol-two pro-oxidizing biological compounds-do not penetrate over 820 µm into UHMWPE liners over the course of 5 years because their D is ≤7.1 × 10-12 cm2  s-1 . © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 2393-2402, 2018.

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

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.

Improving risk assessment of color 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 = 4.8 × 10-10 cm2  s-1 , and solubility S = 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 µg/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. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 310-319, 2018.

Release Kinetics of Nisin from Chitosan-Alginate Complex Films.

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 × 10-9 to 8.034 ×10-9 cm2 /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.

Modeling development of inhibition zones in an agar diffusion bioassay.

A two-temperature agar diffusion bioassay is commonly used to quantify the concentration of nisin using Micrococcus luteus as the indicator microorganism. A finite element computational model based on Fick's second law of diffusion was used to predict the radius of the inhibition zone in this diffusion bioassay. The model developed was used to calculate nisin concentration profiles as a function of time and position within the agar. The minimum inhibitory concentration (MIC) of nisin against M. luteus was determined experimentally. The critical time (T c) for growth of M. luteus within the agar diffusion bioassay was experimentally determined using incubation studies with nisin. The radius of the inhibition zone was predicted from the computational model as the location where the predicted nisin concentration at T c was equal to MIC. The MIC was experimentally determined to be 0.156 µg mL(-1), and T c was determined to be 7 h. Good agreement (R (2) = 0.984) was obtained between model-predicted and experimentally determined inhibition zone radii.