Physiologically based pharmacokinetic modeling: A promising tool for translational research and regulatory toxicology

EDC-induced mechanisms of immunotoxicity: a systematic review

Endocrine-disrupting chemicals (EDCs) refer to a group of chemicals that cause adverse effects in human health, impairing hormone production and regulation, resulting in alteration of homeostasis, reproductive, and developmental, and immune system impairments. The immunotoxicity of EDCs involves many mechanisms altering gene expression that depend on the activation of nuclear receptors such as the aryl hydrocarbon receptor (AHR), the estrogen receptor (ER), and the peroxisome proliferator-activated receptor (PPAR), which also results in skin and intestinal disorders, microbiota alterations and inflammatory diseases. This systematic review aims to review different mechanisms of immunotoxicity and immunomodulation of T cells, focusing on T regulatory (Treg) and Th17 subsets, B cells, and dendritic cells (DCs) caused by specific EDCs such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), bisphenols (BPs) and polyfluoroalkyl substances (PFASs). To achieve this objective, a systematic study was conducted searching various databases including PubMed and Scopus to find in-vitro, in-vivo, and biomonitoring studies that examine EDC-dependent mechanisms of immunotoxicity. While doing the systematic review, we found species- and cell-specific outcomes and a translational gap between in-vitro and in-vivo experiments. Finally, an adverse outcome pathway (AOP) framework is proposed, which explains mechanistically toxicity endpoints emerging from different EDCs having similar key events and can help to improve our understanding of EDCs mechanisms of immunotoxicity. In conclusion, this review provides insights into the mechanisms of immunotoxicity mediated by EDCs and will help to improve human health risk assessment.

The use of in vitro methods in assessing human health risks associated with short-chain perfluoroalkyl and polyfluoroalkyl substances (PFAS)

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are a large class of industrial chemicals with a ubiquitous and persistent presence in the environment. Of the thousands of PFAS used by consumers and industry, very few have been thoroughly characterized for potential adverse effects. This is especially true for the novel short-chain (C < 8) alternatives that replaced legacy PFAS. Perfluoroalkyl and polyfluoroalkyl substances have revealed inconsistencies in the toxicokinetics predicted by animal models and empirical findings in humans. To adequately assess the possible health effects of short-chain PFAS, there is a need for robust aggregated data sets on the mechanistic underpinnings and physiochemical properties of these alternatives. Acquiring relevant data on the health effects of short-chain PFAS can be achieved through high-throughput methods supported by in vitro human cell-based models. This review briefly summarizes some of the toxicity data obtained using human cells in vitro, discusses the advantages and limitations of cell-based models, and provides insights on potential solutions to challenges presented with the use of these methods for use in safety assessments.

Integrating toxicokinetics into toxicology studies and the human health risk assessment process for chemicals: Reduced uncertainty, better health protection

The database of practical examples where toxicokinetic (TK) data has benefitted all stages of the human health risk assessment process are increasingly being published and accepted. This review aimed to highlight and summarise notable examples and to describe the "state of the art" in this field. The overall recommendation is that for any in vivo animal study conducted, measurements of TK should be very carefully considered for inclusion as the numerous benefits this brings continues to grow, particularly during the current march towards animal free toxicology testing and ambitions to eventually conduct human health risk assessments entirely based upon non-animal methods.

Application of in vitro data in physiologically-based kinetic models for quantitative in vitro-in vivo extrapolation: A case-study for baclofen

Physiologically-based kinetic (PBK) models can simulate concentrations of chemicals in tissues over time without animal experiments. Nevertheless, in vivo data are often used to parameterise PBK models. This study aims to illustrate that a combination of kinetic and dynamic readouts from in vitro assays can be used to parameterise PBK models simulating neurologically-active concentrations of xenobiotics. Baclofen, an intrathecally administered drug to treat spasticity, was used as a proof-of-principle xenobiotic. An in vitro blood-brain barrier (BBB) model was used to determine the BBB permeability of baclofen needed to simulate plasma and cerebrospinal concentrations. Simulated baclofen concentrations in individuals and populations of adults and children generally fall within 2-fold of measured clinical study concentrations. Further, in vitro micro-electrode array recordings were used to determine the effect of baclofen on neuronal activity (cell signalling). Using quantitative in vitro-in vivo extrapolations (QIVIVE) corresponding doses of baclofen were estimated. QIVIVE showed that up to 4600 times lower intrathecal doses than oral and intravenous doses induce comparable neurological effects. Most simulated doses were in the range of administered doses. This show that PBK models predict concentrations in the central nervous system for various routes of administration accurately without the need for additional in vivo data.

Physiologically based pharmacokinetic (PBPK) modeling of RNAi therapeutics: Opportunities and challenges

Physiologically based pharmacokinetic (PBPK) modeling is a powerful tool with many demonstrated applications in various phases of drug development and regulatory review. RNA interference (RNAi)-based therapeutics are a class of drugs that have unique pharmacokinetic properties and mechanisms of action. With an increasing number of RNAi therapeutics in the pipeline and reaching the market, there is a considerable amount of active research in this area requiring a multidisciplinary approach. The application of PBPK models for RNAi therapeutics is in its infancy and its utility to facilitate the development of this new class of drugs is yet to be fully evaluated. From this perspective, we briefly discuss some of the current computational modeling approaches used in support of efficient development and approval of RNAi therapeutics. Considerations for PBPK model development are highlighted both in a relative context between small molecules and large molecules such as monoclonal antibodies and as it applies to RNAi therapeutics. In addition, the prospects for drawing upon other recognized avenues of PBPK modeling and some of the foreseeable challenges in PBPK model development for these chemical modalities are briefly discussed. Finally, an exploration of the potential application of PBPK model development for RNAi therapeutics is provided. We hope these preliminary thoughts will help initiate a dialogue between scientists in the relevant sectors to examine the value of PBPK modeling for RNAi therapeutics. Such evaluations could help standardize the practice in the future and support appropriate guidance development for strengthening the RNAi therapeutics development program.