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

Moldable Plastics (Polycaprolactone) can be Acutely Toxic to Developing Zebrafish and Activate Nuclear Receptors in Mammalian Cells

Popularized on social media, hand-moldable plastics are formed by consumers into tools, trinkets, and dental prosthetics. Despite the anticipated dermal and oral contact, manufacturers share little information with consumers about these materials, which are typically sold as microplastic-sized resin pellets. Inherent to their function, moldable plastics pose a risk of dermal and oral exposure to unknown leachable substances. We analyzed 12 moldable plastics advertised for modeling and dental applications and determined them to be polycaprolactone (PCL) or thermoplastic polyurethane (TPU). The bioactivities of the most popular brands advertised for modeling applications of each type of polymer were evaluated using a zebrafish embryo bioassay. While water-borne exposure to the TPU pellets did not affect the targeted developmental end points at any concentration tested, the PCL pellets were acutely toxic above 1 pellet/mL. The aqueous leachates of the PCL pellets demonstrated similar toxicity. Methanolic extracts from the PCL pellets were assayed for their bioactivity using the Attagene FACTORIAL platform. Of the 69 measured end points, the extracts activated nuclear receptors and transcription factors for xenobiotic metabolism (pregnane X receptor, PXR), lipid metabolism (peroxisome proliferator-activated receptor γ, PPARγ), and oxidative stress (nuclear factor erythroid 2-related factor 2, NRF2). By nontargeted high-resolution comprehensive two-dimensional gas chromatography (GC × GC-HRT), we tentatively identified several compounds in the methanolic extracts, including PCL oligomers, a phenolic antioxidant, and residues of suspected antihydrolysis and cross-linking additives. In a follow-up zebrafish embryo bioassay, because of its stated high purity, biomedical grade PCL was tested to mitigate any confounding effects due to chemical additives in the PCL pellets; it elicited comparable acute toxicity. From these orthogonal and complementary experiments, we suggest that the toxicity was due to oligomers and nanoplastics released from the PCL rather than chemical additives. These results challenge the perceived and assumed inertness of plastics and highlight their multiple sources of toxicity.

Developing an Approach for Integrating Chemical Analysis and Transcriptional Changes to Assess Contaminants in Water, Sediment, and Fish

Pharmaceuticals in aquatic environments pose threats to aquatic organisms because of their continuous release and potential accumulation. Monitoring methods for these contaminants are inadequate, with targeted analyses falling short in assessing water quality's impact on biota. The present study advocates for integrated strategies combining suspect and targeted chemical analyses with molecular biomarker approaches to better understand the risks posed by complex chemical mixtures to nontarget organisms. The research aimed to integrate chemical analysis and transcriptome changes in fathead minnows to prioritize contaminants, assess their effects, and apply this strategy in Wascana Creek, Canada. Analysis revealed higher pharmaceutical concentrations downstream of a wastewater-treatment plant, with clozapine being the most abundant in fathead minnows, showing notable bioavailability from water and sediment sources. Considering the importance of bioaccumulation factor and biota-sediment accumulation factor in risk assessment, these coefficients were calculated based on field data collected during spring, summer, and fall seasons in 2021. Bioaccumulation was classified as very bioaccumulative with values >5000 L kg-1, suggesting the ability of pharmaceuticals to accumulate in aquatic organisms. The study highlighted the intricate relationship between nutrient availability, water quality, and key pathways affected by pharmaceuticals, personal care products, and rubber components. Prioritization of these chemicals was done through suspect analysis, supported by identifying perturbed pathways (specifically signaling and cellular processes) using transcriptomic analysis in exposed fish. This strategy not only aids in environmental risk assessment but also serves as a practical model for other watersheds, streamlining risk-assessment processes to identify environmental hazards and work toward reducing risks from contaminants of emerging concern. Environ Toxicol Chem 2024;00:1-22. © 2024 SETAC.

Implications of variability on medical device chemical equivalence assessment

Chemical equivalence testing can be used to assess the biocompatibility implications of a materials or manufacturing change for a medical device. This testing can provide a relatively facile means to evaluate whether the change may result in additional or different toxicological concerns. However, one of the major challenges in the interpretation of chemical equivalence data is the lack established criteria for determining if two sets of extractables data are effectively equivalent. To address this gap, we propose a two-part approach based upon a relatively simple statistical model. First, the probability of a false positive conclusion, wherein there is an incorrectly perceived increase for a given analyte in the comparator relative to the baseline device, can be reduced to a prescribed level by establishing an appropriate acceptance criterion for the ratio of the observed means. Second, the probability of a false negative conclusion, where an actual increase in a given analyte cannot be discerned from the test results, can be minimized by specifying a limiting value of applicability based on the margin of safety (MoS) of the analyte. This approach provides a quantitative, statistically motivated method to interpret chemical equivalence data, despite the relatively high intrinsic variability and small number of replicates typically associated with a chemical characterization evaluation.

Identification and quantification of medical device extractables and leachables via non-target analysis (NTA); Analytical uncertainty

Leachables are substances that are leached from a medical device during its clinical use and are important due to the patient health-related effects they may have. Thus, medical devices are profiled for leachables (and/or extractables as probable leachables) to assess their potential impact on patient health and safety. This profiling is accomplished by screening extracts or leachates of the medical device for released organic substances via non-targeted analysis (NTA) employing chromatographic methods coupled with mass spectrometric detection. Chromatographic mass spectral response factors (RFs) for extractables and leachables vary significantly from compound to compound, complicating the quantitation of these compounds and the application of assessment strategies such as the Analytical Evaluation Threshold (AET). The analytical uncertainty resulting from response factor variation can be expressed in terms of an uncertainty factor (UF), which estimates the magnitude of response factor variation. This manuscript discusses the concept and impact of analytical uncertainty and provides best practice recommendations for the calculation and use of the uncertainty factor, UF.

Online and Offline Prioritization of Chemicals of Interest in Suspect Screening and Non-targeted Screening with High-Resolution Mass Spectrometry

Recent advances in high-resolution mass spectrometry (HRMS) have enabled the detection of thousands of chemicals from a single sample, while computational methods have improved the identification and quantification of these chemicals in the absence of reference standards typically required in targeted analysis. However, to determine the presence of chemicals of interest that may pose an overall impact on ecological and human health, prioritization strategies must be used to effectively and efficiently highlight chemicals for further investigation. Prioritization can be based on a chemical's physicochemical properties, structure, exposure, and toxicity, in addition to its regulatory status. This Perspective aims to provide a framework for the strategies used for chemical prioritization that can be implemented to facilitate high-quality research and communication of results. These strategies are categorized as either "online" or "offline" prioritization techniques. Online prioritization techniques trigger the isolation and fragmentation of ions from the low-energy mass spectra in real time, with user-defined parameters. Offline prioritization techniques, in contrast, highlight chemicals of interest after the data has been acquired; detected features can be filtered and ranked based on the relative abundance or the predicted structure, toxicity, and concentration imputed from the tandem mass spectrum (MS2). Here we provide an overview of these prioritization techniques and how they have been successfully implemented and reported in the literature to find chemicals of elevated risk to human and ecological environments. A complete list of software and tools is available from https://nontargetedanalysis.org/.

Identification of nonvolatile organic compounds (NVOCs) in biopharmaceuticals through non-target analysis and quantification using complexation-precipitation extraction

Single-use systems in biopharmaceutical manufacturing can potentially release chemical constituents (leachables) into drug products. Prior to conducting toxicological risk assessments, it is crucial to establish the qualitative and quantitative methods for these leachables. In this study, we conducted a comprehensive screening and structure elucidation of 23 leachables (nonvolatile organic compounds, NVOCs) in two antibody drugs using multiple (self-built and public) databases and mass spectral simulation. We identified 7 compounds that have not been previously reported in medical or medicinal extractables and leachables. The confidence levels for identified compounds were classified based on analytical standards, literature references, and fragment assignments. Most of the identified leachables were found to be plasticizers, antioxidants, slip agents or polymer degradants. Polysorbate (namely Tween) is commonly used as an excipient for protein stabilization in biopharmaceutical formulations, but its ionization in liquid chromatography-electrospray ionization mass spectrometry can interfere with compound quantification. To address this, we employed a complexation-precipitation extraction method to reduce polysorbate content and quantify the analytes. The developed quantitative method for target NVOCs demonstrated high sensitivity (limit of quantification: 20 or 50 μg/L), accuracy (recoveries: 77.2 to 109.5 %) and precision (RSD ≤ 8.2 %). Overall, this established method will facilitate the evaluation of NVOC safety in drug products.

Predicting partitioning from low density polyethylene to blood and adipose tissue by linear solvation energy relationship models

The variety of polymers utilized in medical devices demands for testing of extractables and leachables according to ISO 10993-18:2020 in combination with ISO 10993-1:2018. The extraction of the materials involves the use of organic solvents as well as aqueous buffers to cover a wide range of polarity and pH-values, respectively. To estimate patient exposure to chemicals leaching from a polymer in direct body contact, simulating solvents are applied to best mimic the solubilization and partitioning behavior of the related tissue or body fluid. Here we apply linear solvation energy relationship (LSER) models to predict blood/water and adipose tissue/water partition coefficients. We suggest this predictive approach to project levels of potential leachables, design extraction experiments, and to identify the optimal composition of simulating extraction solvents. We compare our predictions to LSER predictions for commonly applied surrogates like ethanol/water mixtures, butanol, and octanol as well as olive oil, butanone, 1,4-dioxane for blood and adipose tissue, respectively. We therefore selected a set of 26 experimentally determined blood/water partition coefficients and 33 adipose tissue/water partition coefficients, where we demonstrate that based on the root mean squared error rmse the LSER approach performs better than surrogates like octanol or butanol and equally well as 60:40 ethanol/water for blood. For adipose tissue/water partitioning, the experimentally determined octanol/water partition coefficient performs best but the rmse is at the same range as our LSER approach based on experimentally determined descriptors. Further, we applied our approach for 248 extractables where we calculated blood/low density polyethylene (LDPE) and adipose tissue/LDPE partition coefficients. By this approach, we successfully identified chemicals of potential interest to a toxicological evaluation based on the total risk score.

A comprehensive study of the effect of elevated temperature on the extractability and rate of exaggerated and exhaustive extractions of medical devices

The effectiveness of an elevated temperature on the thermodynamic and kinetic properties of the solvent extraction of medical devices is evaluated in this study. The main objective of the current work is to specifically address the question of how effective a temperature of 50 °C, relative to 37 °C, is in improving the extractability and rate of the exaggerated and exhaustive extractions of medical devices. The extractability at equilibrium is related to the extraction partition coefficient, while the extraction rate is related to the corresponding diffusion coefficient. The partition and diffusion coefficients (or the enthalpies of extraction and diffusional activation energies) of solid-liquid extractions for different polymeric materials, solvents, and types of extractables entities at different temperatures are compiled comprehensively from extensive publications in the literature. The collected partition and diffusion coefficients at different temperatures are used to derive the partition enthalpies and diffusional activation energies in this study. The combined 209 partition enthalpies and 262 diffusional activation energies are then used to calculate the ratios of the partition and diffusion coefficients, when the extraction temperature increases from 37 °C to 50 °C. It is concluded from the study that the maximum improvement in extracted chemical amount with this specific temperature increase is about 3-fold, but the median improvement is only 16%. The most probable improvement is 25%. The maximum improvement (or decrease) in extraction time is 3.2-fold by the change in the diffusional coefficient, but the median value is 1.9-fold. The most probable decrease in extraction time is 2.4-fold. The collected data also allow the calculation of the ratio of the diffusion coefficient for a 10 °C increase, and the results are compared with the "factor 10 rule" in the literature on the relationship between the diffusion coefficient and temperature. The explicit conclusions of the study certainly provide evidences (not assumptions) in designing practical and cost-effective exaggerated and exhaustive extractions in the chemical characterization of medical devices, taking into considerations of extraction cycle time, temperature-dependent chemical stability, and the number of repeated extractions.

Non-targeted analysis (NTA) and suspect screening analysis (SSA): a review of examining the chemical exposome

Non-targeted analysis (NTA) and suspect screening analysis (SSA) are powerful techniques that rely on high-resolution mass spectrometry (HRMS) and computational tools to detect and identify unknown or suspected chemicals in the exposome. Fully understanding the chemical exposome requires characterization of both environmental media and human specimens. As such, we conducted a review to examine the use of different NTA and SSA methods in various exposure media and human samples, including the results and chemicals detected. The literature review was conducted by searching literature databases, such as PubMed and Web of Science, for keywords, such as "non-targeted analysis", "suspect screening analysis" and the exposure media. Sources of human exposure to environmental chemicals discussed in this review include water, air, soil/sediment, dust, and food and consumer products. The use of NTA for exposure discovery in human biospecimen is also reviewed. The chemical space that has been captured using NTA varies by media analyzed and analytical platform. In each media the chemicals that were frequently detected using NTA were: per- and polyfluoroalkyl substances (PFAS) and pharmaceuticals in water, pesticides and polyaromatic hydrocarbons (PAHs) in soil and sediment, volatile and semi-volatile organic compounds in air, flame retardants in dust, plasticizers in consumer products, and plasticizers, pesticides, and halogenated compounds in human samples. Some studies reviewed herein used both liquid chromatography (LC) and gas chromatography (GC) HRMS to increase the detected chemical space (16%); however, the majority (51%) only used LC-HRMS and fewer used GC-HRMS (32%). Finally, we identify knowledge and technology gaps that must be overcome to fully assess potential chemical exposures using NTA. Understanding the chemical space is essential to identifying and prioritizing gaps in our understanding of exposure sources and prior exposures. IMPACT STATEMENT: This review examines the results and chemicals detected by analyzing exposure media and human samples using high-resolution mass spectrometry based non-targeted analysis (NTA) and suspect screening analysis (SSA).

Electrospray Ionization Efficiency Predictions and Analytical Standard Free Quantification for SFC/ESI/HRMS

Supercritical fluid chromatography (SFC) is a promising, sustainable, and complementary alternative to liquid chromatography (LC) and has often been coupled with high resolution mass spectrometry (HRMS) for nontarget screening (NTS). Recent developments in predicting the ionization efficiency for LC/ESI/HRMS have enabled quantification of chemicals detected in NTS even if the analytical standards of the detected and tentatively identified chemicals are unavailable. This poses the question of whether analytical standard free quantification can also be applied in SFC/ES/HRMS. We evaluate both the possibility to transfer an ionization efficiency predictions model, previously trained on LC/ESI/HRMS data, to SFC/ESI/HRMS as well as training a new predictive model on SFC/ESI/HRMS data for 127 chemicals. The response factors of these chemicals ranged over 4 orders of magnitude in spite of a postcolumn makeup flow, expectedly enhancing the ionization of the analytes. The ionization efficiency values were predicted based on a random forest regression model from PaDEL descriptors and predicted values showed statistically significant correlation with the measured response factors (p < 0.05) with Spearman's rho of 0.584 and 0.669 for SFC and LC data, respectively. Moreover, the most significant descriptors showed similarities independent of the chromatography used for collecting the training data. We also investigated the possibility to quantify the detected chemicals based on predicted ionization efficiency values. The model trained on SFC data showed very high prediction accuracy with median prediction error of 2.20×, while the model pretrained on LC/ESI/HRMS data yielded median prediction error of 5.11×. This is expected, as the training and test data for SFC/ESI/HRMS have been collected on the same instrument with the same chromatography. Still, the correlation observed between response factors measured with SFC/ESI/HRMS and predicted with a model trained on LC data hints that more abundant LC/ESI/HRMS data prove useful in understanding and predicting the ionization behavior in SFC/ESI/HRMS.

Organophosphate esters (OPEs) in plastic food packaging: non-target recognition, and migration behavior assessment

Organophosphate esters (OPEs) are widely used as plasticizers in plastic food packaging; however, the migration of OPEs from plastic to food is largely unstudied. We do not even know the specific number of OPEs that exist in the plastic food packaging. Herein, an integrated target, suspect, and nontarget strategy for screening OPEs was optimized using ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). The strategy was used to analyze 106 samples of plastic food packaging collected in Nanjing city, China, in 2020. HRMS allowed full or tentative identification of 42 OPEs, of which seven were reported for the first time. Further, oxidation products of bis(2,4-di-tert-butylphenyl) pentaerythritol diphosphite (AO626) in plastics were identified, implying that the oxidation of organophosphite antioxidants (OPAs) could be an important indirect source of OPEs in plastics. The migration of OPEs was examined with four simulated foods. Twenty-six out of 42 OPEs were detected in at least one of the four simulants, particularly isooctane, in which diverse OPEs were detected at elevated concentrations. Overall, the study supplements the list of OPEs that humans could ingest as well as provides essential information regarding the migration of OPEs from plastic food packaging to food.

Modeling extraction of medical device polymers for biocompatibility evaluation

Extraction testing is critical for biocompatibility evaluation of medical devices, whether to generate samples for biological testing or form the basis for toxicological risk assessment. However, it is not always clear how to compare extraction testing between different extraction conditions and sample geometries. We employ a physics-based model to elucidate the theoretical impact of extraction conditions, sample geometry and material properties on extraction efficiency (M/M⁰) and extract concentration (C/C⁰) for single-step and iterative/exhaustive extraction test methods. The model is specified by three parameters: thermodynamic contributions (Ψ), kinetic contributions (τ), and number of extraction iterations (N). We find that over the range of typical parameters for single-step extractions, M/M⁰ only approaches one (complete exhaustion) for relatively large values of Ψ (≥10) and τ(≥1). Further, the model suggests that test article geometry and solvent volume can have a dramatic and sometimes opposing effect on M/M⁰ and C/C⁰. Our results imply that iterative extractions can be approximated as a single-step extraction with scaled parameters Ψ' = ΨN and τ' = τN. The model provides a framework to reduce the biocompatibility evaluation test burden by optimizing test article and extraction condition selection and guiding development of new test protocols.

A Chemical Characterization Workflow for Nontargeted Analysis of Complex Extracts from Polymer Based Medical Device Using High Resolution LC/MS

The chemical characterization of extractables and leachables (E&Ls) is an important aspect of biosafety and biocompatibility assessment in medical device industry. The advent of the body-contact use of medical devices in patient treatment has introduced a potential source for extractables and leachables as these medical devices are comprised of various polymeric materials. Several industry working groups, the FDA and USP, have recognized the guidance for chemical characterizations and nontargeted analysis of medical device extracts, such as ISO 10993-18:2020. The MS application of nontargeted analysis has played a critical role in understanding the E&Ls from medical device extracts. However, there have been very few reports about the MS based workflow with nontargeted analysis for medical device extracts and there is little guidance about the exact methodologies which should be used, even though there is an urgent need for a clearly defined process for the identification of medical device extracts. In this study, we demonstrated an analytical LC/MS (liquid chromatography/mass spectrometry) workflow using high resolution Exploris120 Orbitrap instrument for data acquisition and Compound Discoverer 3.3 intelligent software for data processing to profile the polymer related E&Ls from a balloon dilation catheter device extracted with 40% ethanol. An E&L ID workflow combining LC separation, data-informed MS acquisition strategy, MS information mining (including adduct ions, MS information from both electrospray ionization (ESI) (+) and ESI (-), in-source fragmentation, common fragment ions (CFIs), common neutral losses (CNLs), and in silico MS simulation was described with intelligent software processing and manual data interpretation. The workflow developed in this study was proven to be effective to provide a comprehensive profile of polymer related degradation products, polymer impurities and additives including surfactants, UV curing agent, antioxidants, and plasticizers for the device analyzed. The classification of E&L compounds using CFIs and CNLs was very effective to facilitate the identification of polymer related impurities and extract the polymer related impurities with common structures in a large data result set.

Chemical Characterization of Leachables in Catheter Device

Extractables or leachables of biomaterials or residues of additives used in the manufacturing process that are potentially released from a medical device may have an adverse effect on a patient. Chemical characterization of leachable chemicals and degradation products in a medical device is an important aspect of its overall biocompatibility assessment process, which helps to ensure that the therapeutical benefits exceed the potential biological risks associated with the use of the device or its components or materials. By evaluating the types and amounts of chemicals that may migrate from a device to a patient during clinical use, potential toxicological risks can be assessed. A semipolar solvent, 40% ethanol in water (v/v), an appropriate surrogate for blood and blood related substances, was used as an extraction medium to mimic the body fluid in contact with a medical device. The extraction was conducted at 37 °C for 24 h for limited exposure medical devices per ISO 10993-12:2021. From gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) analysis, leachable chemicals of polylactams, linear polyamides, cyclic polytetramethylene ether (PTME), poly(tetramethylene ether) glycol (PTMEG), cyclic and linear poly(tetramethylene ether) glycol adipate (PTMEGA), cyclic and linear poly(tetramethylene ether) glycol adipamide (PTMEGAA) were structurally elucidated. The workflow presented in this study was proven to be a successful approach for rapid extractable and leachable profiling and identification with confidence.