National Center for Toxicological Research

Gestational antiretroviral therapy (ART) has significantly reduced the risk of vertical transmission of HIV, but concerns linger about its long-term effects on the fetal immune system and intestinal health. Our previous work has demonstrated dose-dependent changes in the fecal and mucosa-associated microbiome of adult rat offspring perinatally exposed to TC-ART (tri-combination ART: dolutegravir, abacavir, and lamivudine). These changes may either be driven by alterations in immune system and intestinal barrier integrity or potentially impact them. In this study, we further investigated the long-term effects of perinatal TC-ART exposure on intestinal permeability, cytokine profiles, and intestinal mucosa morphology. We observed statistically significant sex-dependent differences, with male offspring exhibiting reduced weight gain, a dichotomous response between low and high dose for inflammatory cytokines [interleukin-5 (IL-5), IL-7, and IL-12], differential regulation for the mRNA expression of intestinal permeability-related genes (21 downregulated), and disrupted villous architecture, while females showed dose-dependent decreases in inflammatory cytokines [IL-17, IL-5, and macrophage colony-stimulating factor (M-CSF)]. In females, while some intestinal permeability genes were downregulated, the upregulation of other permeability genes suggests a compensatory mechanism to maintain the intestinal barrier function, indicating an overall milder response to TC-ART. These findings suggest that perinatal exposure to TC-ART may have differential impacts on intestinal health, with females exhibiting a more adaptive response compared to males, highlighting the need for sex-specific considerations in evaluating long-term effects of ART.

Cannabidiol (CBD) is extensively metabolized in humans, with 7-carboxy-CBD being the major metabolite. The biotransformation of CBD in mice, rats, and dogs differs from that in humans. We have investigated if the pharmacokinetics of CBD in rhesus monkeys and New Zealand White rabbits is similar to humans by measuring serum levels of CBD and its phase I and II metabolites after single intragastric (77.5 mg/kg body weight) or intravenous (3.9 mg/kg body weight) CBD doses. In rhesus monkeys, intragastric CBD yielded a maximum concentration (Cmax) of 241.6 nM (males) and 476.5 nM (females), with a terminal half-life (T1/2) of 11.6 and 15.4 h. The area under the curve from zero to infinity (AUC0-inf) was 5,376 nM*h (males) and 7,366 nM*h (females), with bioavailability of 2.5% and 5.5%. 7-Carboxy-CBD showed a Cmax of 334.7 nM (males) and 655.4 nM (females), with AUC0-inf 1.5 to 1.6 times higher than CBD. The levels of other metabolites were minimal. In rabbits, intragastric CBD resulted in a Cmax of 76.6 nM (males) and 117.1 nM (females), with a T1/2 of 11.1 and 14.9 h. The AUC0-inf was 1,443 nM*h (males) and 1,645 nM*h (females), with bioavailability of 2.1% to 2.2%. 7-Carboxy-CBD levels were significantly higher than CBD, with a Cmax of 11,631 nM (males) and 13,278 nM (females), and an AUC0-inf 120 to 133 times higher. In contrast to rhesus monkeys, New Zealand White rabbits exhibit a CBD metabolic profile similar to humans, with high levels of 7-carboxy-CBD, making them a promising model for studying CBD metabolism-driven toxicity.

Background: Physiologically based pharmacokinetic (PBPK) models utilize computer-based simulations to predict the pharmacokinetics of drugs. By using mathematical modeling techniques consisting of differential equations to simulate blood flow, tissue compositions, and organ properties, the pharmacokinetic properties of drugs can be better understood. Specifically, PBPK models can provide predictive information about drug absorption, distribution, metabolism, and excretion (ADME). The information gained from PBPK models can be useful in both drug discovery, development, and regulatory science. PBPK models can help to address some of the ethical dilemmas that arise during the drug development process, particularly when examining patient populations where testing a new drug may have significant ethical concerns. Patient populations where significant physiological change (i.e., pregnancy, pediatrics, geriatrics, organ impairment populations, etc.) and pathophysiological influences resulting in PK changes can also benefit from PBPK modeling. Additionally, PBPK models can be utilized to predict variations in drug metabolism resulting from genetic polymorphisms, age, and disease states. Methods: In this mini-review, we examine the various applications of PBPK models in drug metabolism. Current research articles related to drug metabolism in genetics, life-stages, and disease states were reviewed. Results: Several key factors in genetics, life-stage, and disease states that affect metabolism in PBPK models are identified. In genetics, the role of CYP enzymes, genetic polymorphisms, and ethnicity may influence metabolism. Metabolism generally changes over time from neonate, pediatric, adult, geriatric, and perinatal populations. Disease states such as renal and hepatic impairment, weight and other acute and chronic diseases also can also alter metabolism. Several examples of PBPK models applying these physiological changes have been published. Conclusions: The utilization and recognition of these specific areas in PBPK modeling can aid in personalized dosing strategy, clinical trial optimization, and regulatory submission.

The tire rubber antioxidant N-(1,3-dimethylbutyl)-N′-phenyl-p-phenylenediamine (6PPD) and its oxidation product 6PPD-quinone (6PPD-Q) were recently found in human bodies. Though 6PPD/6PPD-Q showed species-dependent toxicity in animals, human relevant data are scarce. Here, primary human hepatocytes (PHHs), the gold standard in vitro model for hepatotoxicity, were used for acute and subacute toxicity assessments, with test concentrations normalized to average human serum concentrations (Cave). Acute exposure in sandwich cultured PHHs decreased glutathione starting at 100-fold Cave of 6PPD (10 ng/mL) or 500-fold Cave of 6PPD-Q (100 ng/mL), and inhibited albumin starting at 10,000-fold Cave of 6PPD, or 2500-fold Cave of 6PPD-Q. Urea was suppressed by 6PPD-Q, but not 6PPD, starting at 2500-fold Cave. Lactate dehydrogenase (LDH) leakage, a measurement of cell death, was unaffected. Subacute exposure of primary human liver spheroids to 6PPD-Q showed no cell death, while 6PPD increased caspase 3/7 activity and LDH leakage and decreased adenosine triphosphate at 50,000-fold Cave. Of 10 cytokines involved in hepatotoxicity, interleukin-8 was increased by 6PPD and 6PPD-Q starting from 200- and 50-fold Cave, respectively. At 50 to 300-fold Cave, the in vivo-relevant concentrations in humans, GSH, caspase 3/7 activity, and interleukin-8 were the only endpoints that were significantly affected by 6PPD and/or 6PPD-Q, and no cell death was observed. These data indicate that 6PPD/6PPD-Q may cause liver dysfunctions and trigger immunotoxicity in heavily exposed individuals but are unlikely to induce significant cell death at regular environmental exposure levels.

Cannabidiol (CBD) undergoes oxidation to 7-hydroxy-CBD in the liver via cytochrome P450 enzymes. 7-Hydroxy-CBD can be further oxidized to 7-carboxy-CBD, the principal circulating metabolite in humans. An aldehyde intermediate, 7-formyl-CBD, is hypothesized to be the precursor of 7-carboxy-CBD; however, the formation of 7-formyl-CBD and the enzymes leading to its formation and metabolism have not been thoroughly investigated. Upon incubating 7-hydroxy-CBD with human liver S9 or microsomes, and using O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine (PFBHA) as a trapping agent, we demonstrated the formation of 7-formyl-CBD as its oxime derivative 7-pentafluorobenzyl oxime-CBD (7-PFBO-CBD). The transformation of 7-hydroxy-CBD to 7-formyl-CBD in S9 or microsomes required NAD+ or NADP+. Trapping 7-formyl-CBD with PFBHA decreased the formation of 7-carboxy-CBD, indicating that the formation of 7-carboxy-CBD depends on the availability of 7-formyl-CBD. The flavonoid kaempferol, which inhibits xanthine oxidoreductase and hydroxysteroid dehydrogenases, suppressed the formation of 7-PFBO-CBD and 7-carboxy-CBD in human liver S9 and microsomes incubated with 7-hydroxy-CBD. The xanthine oxidoreductase inhibitor allopurinol and its substrate xanthine did not affect the metabolism of 7-hydroxy-CBD. The hydroxysteroids estradiol and dehydroepiandrosterone reduced the formation of 7-carboxy-CBD in liver microsomes and S9. These results suggest that alcohol oxidoreductases associated with hydroxysteroid metabolism may play a role in the conversion of 7-hydroxy-CBD to 7-formyl-CBD. The irreversible aldehyde dehydrogenase inhibitors, disulfiram and WIN 18,446, inhibited the formation of 7-carboxy-CBD and led to a significant accumulation of 7-PFBO-CBD in the S9 and microsomal incubations. The accumulation of the aldehyde intermediate may play a role in the enhanced cytotoxicity of 7-hydroxy-CBD in HepG2 cells when co-treated with disulfiram. These findings indicate that NAD(P)+-dependent alcohol oxidoreductases may catalyze the conversion of 7-hydroxy-CBD to 7-formyl-CBD in human liver S9 and microsomes. The potentially toxic aldehyde intermediate is further oxidized by aldehyde dehydrogenase to 7-carboxy-CBD.

Pharmacovigilance is essential for protecting patient health by monitoring and managing medication-related risks. Traditional methods like spontaneous reporting systems and clinical trials are valuable for identifying adverse drug events, but face delays in data access. Social media platforms, with their real-time data, offer a novel avenue for pharmacovigilance by providing a wealth of user-generated content on medication usage, adverse drug events, and public sentiment. However, the unstructured nature of social media content presents challenges in data analysis, including variability and potential biases. Advanced techniques like natural language processing and machine learning are increasingly being employed to extract meaningful information from social media data, aiding in early adverse drug event detection and real-time medication safety monitoring. Ensuring data reliability and addressing ethical considerations are crucial in this context. This review examines the existing literature on the use of social media data for drug safety analysis, highlighting the platforms involved, methodologies applied, and research questions explored. It also discusses the challenges, limitations, and future directions of this emerging field, emphasizing the need for ethical principles, transparency, and interdisciplinary collaboration to maximize the potential of social media in enhancing pharmacovigilance efforts.

In 1996, a special zebrafish (Danio rerio) issue of the journal Development, with a 481-page volume containing 37 papers from four different laboratories, published genetic and phenotypic details of hundreds of different mutants, obtained through mutagenesis screening [...].

To determine if prenatal socioeconomic status (SES) is associated with childhood working memory (WM), we constructed a more precise, integrative measure of WM using variables from multiple tasks that may provide a more representative measure of WM. We used data from a prospective birth cohort study in Mexico City, Mexico, with N = 515 children aged 6-9 years. Prenatal SES was measured using the Mexican Association of Marketing Research and Public Opinion Agencies (AMAI) index. We created a latent variable for nonverbal working memory using multiple tasks (Cambridge Neuropsychological Test Automated Battery spatial working memory, operant chamber Delayed Match to Sample and Incremental Repeated Acquisition). Structural equation models were used to assess associations between prenatal SES and nonverbal working memory, adjusting for child demographics (e.g., age and sex), prenatal exposures (e.g., exposures to lead, arsenic, and secondhand smoke), and family (current SES, maternal IQ) variables. Children had a mean age of 6.6 years [SD 0.6], and 50.5% were boys. Using confirmatory factor analysis, we constructed a latent variable of nonverbal working memory, which was measurement invariant across child sex. Prenatal SES was associated with childhood nonverbal working memory (standardized factor loading = 0.17; p = 0.004). These associations were modified by child sex. Higher prenatal SES was significantly associated with higher childhood WM in females (standardized factor loading = 0.26; p = 0.002), but not in males. Prenatal socioeconomic status is a predictor of childhood working memory, but it may be a stronger predictor for girls compared with for boys.