An Introduction to the Benchmarking and Publications for Non-Targeted Analysis Working Group.

Non-targeted analysis (NTA) encompasses a rapidly evolving set of mass spectrometry techniques aimed at characterizing the chemical composition of complex samples, identifying unknown compounds, and/or classifying samples, without prior knowledge regarding the chemical content of the samples. Recent advances in NTA are the result of improved and more accessible instrumentation for data generation and analysis tools for data evaluation and interpretation. As researchers continue to develop NTA approaches in various scientific fields, there is a growing need to identify, disseminate, and adopt community-wide method reporting guidelines. In 2018, NTA researchers formed the Benchmarking and Publications for Non-Targeted Analysis Working Group (BP4NTA) to address this need. Consisting of participants from around the world and representing fields ranging from environmental science and food chemistry to 'omics and toxicology, BP4NTA provides resources addressing a variety of challenges associated with NTA. Thus far, BP4NTA group members have aimed to establish a consensus on NTA-related terms and concepts and to create consistency in reporting practices by providing resources on a public Web site, including consensus definitions, reference content, and lists of available tools. Moving forward, BP4NTA will provide a setting for NTA researchers to continue discussing emerging challenges and contribute to additional harmonization efforts.

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.

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.

Deriving a provisional tolerable intake for intravenous exposure to silver nanoparticles released from medical devices.

Silver nanoparticles (AgNP) are incorporated into medical devices for their anti-microbial characteristics. The potential exposure and toxicity of AgNPs is unknown due to varying physicochemical particle properties and lack of toxicological data. The aim of this safety assessment is to derive a provisional tolerable intake (pTI) value for AgNPs released from blood-contacting medical devices. A literature review of in vivo studies investigating critical health effects induced from intravenous (i. v.) exposure to AgNPs was evaluated by the Annapolis Accords principles and Toxicological Data Reliability Assessment Tool (ToxRTool). The point of departure (POD) was based on an i. v. 28-day repeated AgNP (20 nm) dose toxicity study reporting an increase in relative spleen weight in rats with a 5% lower confidence bound of the benchmark dose (BMDL05) of 0.14 mg/kg bw/day. The POD was extrapolated to humans by a modifying factor of 1,000 to account for intraspecies variability, interspecies differences and lack of long-term toxicity data. The pTI for long-term i. v. exposure to 20 nm AgNPs released from blood-contacting medical devices was 0.14 µg/kg bw/day. This pTI may not be appropriate for nanoparticles of other physicochemical properties or routes of administration. The methodology is appropriate for deriving pTIs for nanoparticles in general.

CoMFA modeling of enzyme kinetics: K(m) values for sulfation of diverse phenolic substrates by human catecholamine sulfotransferase SULT1A3.

Three-dimensional QSAR models were developed for predicting kinetic Michaelis constant (K(m)) values for phenolic substrates of human catecholamine sulfating sulfotransferase (SULT1A3). The K(m) values were correlated to the steric and electronic molecular fields of the substrates utilizing Comparative Molecular Field Analysis (CoMFA). The evaluated SULT1A3 substrate data set consisted of 95 different substituted phenols, catechols, catecholamines, steroids, and related structures for which the K(m) values were available. The data set was divided in three different subgroups in the initial analysis: (1). for the first CoMFA model substrates with only one reacting hydroxyl group were selected (n = 51), (2).the second model was build with structurally rigid substrates (n = 59), and (3). finally all substrates of the data set were included in the analysis (n = 95). Substrate molecules were aligned using the aromatic ring and the reacting hydroxyl group as a template. After the initial analysis different substrate alignment rules based on the existing knowledge of the SULT1A3 active site structure were evaluated. After this optimization a final CoMFA model was built including all 95 substrates of the data set. Cross-validated q(2) values (leave-one-out and leave-n-out) and coefficient contour maps were calculated for all derived CoMFA models. All four CoMFA models were statistically significant with q(2) values up to 0.624. These predictive QSAR models will provide us information about the factors that affect substrate binding at the active site of human catecholamine sulfotransferase SULT1A3.

Conjugation of catechols by recombinant human sulfotransferases, UDP-glucuronosyltransferases, and soluble catechol O-methyltransferase: structure-conjugation relationships and predictive models.

Conjugation of a structurally diverse set of 53 catechol compounds was studied in vitro using six recombinant human sulfotransferases (SULTs), five UDP-glucuronosyltransferases (UGT) and the soluble form of catechol O-methyltransferase (S-COMT) as catalyst. The catechol set comprised endogenous compounds, such as catecholamines and catecholestrogens, drugs, natural plant constituents, and other catechols with diverse substituent properties and substitution patterns. Most of the catechols studied were substrates of S-COMT and four SULT isoforms (1A1, 1A2, 1A3, and 1B1), but the rates of conjugation varied considerably, depending on the substrate structure and the enzyme form. SULT1E1 sulfated fewer catechols. Only low activities were observed for SULT1C2. UGT1A9 glucuronidated catechols representing various structural classes, and almost half of the studied compounds were glucuronidated at a high rate. The other UGT enzymes (1A1, 1A6, 2B7, and 2B15) showed narrower substrate specificity for catechols, but each glucuronidated some catechols at a high rate. Dependence of specificity and rate of conjugation on the molecular structure of the substrate was characterized by structure-activity relationship analysis and quantitative structure-activity relationship modeling. Twelve structural descriptors were used to characterize lipophilicity/polar interaction properties, steric properties, and electronic effects of the substituents modifying the catechol structure. PLS models explaining more than 80% and predicting more than 70% of the variance in conjugation activity were derived for the representative enzyme forms SULT1A3, UGT1A9, and S-COMT. Several structural factors governing the conjugation of catechol hormones, metabolites, and drugs were identified. The results have significant implications for predicting the metabolic fate of catechols.

Induction of T(4) UDP-GT activity, serum thyroid stimulating hormone, and thyroid follicular cell proliferation in mice treated with microsomal enzyme inducers.

The microsomal enzyme inducers phenobarbital (PB), pregnenolone-16 alpha-carbonitrile (PCN), 3-methylcholanthrene (3MC), and Aroclor 1254 (PCB) are known to induce thyroxine (T(4)) glucuronidation and reduce serum T(4) concentrations in rats. Also, microsomal enzyme inducers that increase serum TSH (i.e., PB and PCN) also increase thyroid follicular cell proliferation in rats. Little is known about the effects of these microsomal enzyme inducers on T(4) glucuronidation, serum thyroid hormone concentrations, serum TSH, and thyroid gland growth in mice. Therefore, we tested the hypothesis that microsomal enzyme inducers induce T(4) UDP-GT activity, resulting in reduced serum T(4) concentrations, as well as increased serum TSH and thyroid follicular cell proliferation in mice. B6C3F male mice were fed a control diet or a diet containing PB (600, 1200, 1800, or 2400 ppm), PCN (250, 500, 1000, or 2000 ppm), 3MC (62.5, 125, 250, or 500 ppm), or PCB (10, 30, 100, or 300 ppm) for 21 days. All four inducers increased liver weight and hepatic microsomal UDP-GT activity toward chloramphenicol, alpha-naphthol, and T(4). PB and PCB decreased serum total T(4), but PCN and 3MC did not. Serum thyroid stimulating hormone was markedly increased by PCN and 3MC treatments, and slightly increased by PB and PCB treatments. All four microsomal enzyme inducers dramatically increased thyroid follicular cell proliferation in mice. The findings suggest that PB, PCN, 3MC, and PCB disrupt thyroid hormone homeostasis in mice.