In vitro-in silico-based probabilistic risk assessment of combined exposure to bisphenol A and its analogues by integrating ToxCast high-throughput in vitro assays with in vitro to in vivo extrapolation (IVIVE) via physiologically based pharmacokinetic (PBPK) modeling

Mode of action exploration of reproductive toxicity induced by bisphenol S using human normal ovarian epithelial cells through ERβ-MAPK signaling pathway

BACKGROUND

In the plastics production sector, bisphenol S (BPS) has gained popularity as a replacement for bisphenol A (BPA). However, the mode of action (MOA) of female reproductive toxicity caused by BPS remains unclear and the safety of BPS is controversial.

METHODS

Human normal ovarian epithelial cell line, IOSE80, were exposed to BPS at human-relevant levels for short-term exposure at 24 h or 48 h, or for long-term exposure at 28 days, either alone or together with five signaling pathway inhibitors: ICI 18,2780 (estrogen receptor [ER] antagonist), G15 (GPR30 specific inhibitor), U0126 (extracellular regulated protein kinase [ERK] 1/2 inhibitor), SP600125 (c-Jun N-terminal kinase [JNK] inhibitor) or SB203580 (p38 mitogen‑activated protein kinase [p38MAPK] inhibitor). MOA through ERβ-MAPK signaling pathway interruption was explored, and potential thresholds were estimated by the benchmark dose method.

RESULTS

For short-term exposure, BPS exposure at human-relevant levels elevated the ESR2 and MAPK8 mRNA levels, along with the percentage of the G0/G1 phase. For long-term exposure, BPS raised the MAPK1 and EGFR mRNA levels, the ERβ, p-ERK, and p-JNK protein levels, and the percentage of the G0/G1 phase, which was partly suppressed by U0126. The benchmark dose lower confidence limit (BMDL) of the percentage of the S phase after 24 h exposure was the lowest among all the BMDLs of a good fit, with BMDL5 of 9.55 μM.

CONCLUSIONS

The MOA of female reproductive toxicity caused by BPS at human-relevant levels might involve: molecular initiating event (MIE)-BPS binding to ERβ receptor, key event (KE)1-the interrupted expression of GnRH, KE2-the activation of JNK (for short-term exposure) and ERK pathway (for long-term exposure), KE3-cell cycle arrest (the increased percentage of the G0/G1 phase), and KE4-interruption of cell proliferation (only for short-term exposure). The BMDL of the percentage of the S phase after 24 h exposure was the lowest among all the BMDLs of a good fit, with BMDL5 of 9.55 μM.

Alternatives Exert Higher Health Risks than Bisphenol A on Indo-Pacific Humpback Dolphins

The detrimental effects of bisphenol (BP) exposure are a concern for vulnerable species, Indo-Pacific humpback dolphins (Sousa chinensis). To investigate the characteristics of BP profiles and their adverse impact on humpback dolphins, we assessed the concentrations of six BPs, including bisphenol A (BPA), bisphenol S (BPS), bisphenol F (BPF), bisphenol AF (BPAF), bisphenol B (BPB), and bisphenol P (BPP) in blubber (n = 26) and kidney (n = 12) of humpback dolphins stranded in the Pearl River Estuary, China. BPS accounted for the largest proportion of the total bisphenols (∑BPs) in blubber (55%) and kidney (69%). The concentration of ∑BP in blubber was significantly higher than that in the kidney and liver. The EC50 values of five BPA alternatives were lower than those of BPA in humpback dolphin skin fibroblasts (ScSF) and human skin fibroblasts (HSF). ScSF was more sensitive to BPS, BPAF, BPB, and BPP than HSF. The enrichment pathway of BPA was found to be associated with inflammation and immune dysregulation, while BPP and BPS demonstrated a preference for genotoxicity. BPA, BPP, and BPS, which had risk quotients (RQs) > 1, were found to contribute to subhealth and chronic disease in humpback dolphins. According to the EC50-based risk assessment, BPS poses a higher health risk than BPA for humpback dolphins. This study successfully evaluated the risks of bisphenols in rare and endangered cetacean cell lines using a noninvasive method. More in vivo and in field observations are necessary to know whether the BPA alternatives are likely to be regrettable substitutions.

IVIVE-PBPK based new approach methodology for addressing early life toxicity induced by Bisphenol A

Bisphenol A (BPA) is a known endocrine disruptor mimicking natural estrogens with the potential to affect human health, especially during prenatal and postnatal exposure at or below current acceptable daily intake levels. Different adverse effects of BPA are still under investigation, and multiple mechanisms of action remain unexplored. This may be one of the reasons for the continuously changing tolerable daily intake (TDI) of BPA with the emergence of new adverse health effects over time. In addition, translational modelling through in vitro-in vivo extrapolation (IVIVE) can act as prerequisite bridge for translating in-vitro finding into human risk assessment. The objective of this study was to conduct in-vitro experiments and utilize an IVIVE-pregnancy physiologically based pharmacokinetic (P-PBPK) modeling to investigate developmental neurotoxicity and embryotoxicity in humans. The data obtained from human embryonic stem cells-based assays (study conducted between October 2020-2021) were used for the IVIVE-P-PBPK models to obtain the human equivalent doses (HEDs) which were further extrapolated to reference doses (RfDs). The results showed that simulated mean RfDs (μg/kg/day) derived from the HSD3B1 and NFATC2 gene of embryotoxicity and neurodevelopmental toxicity tests, respectively, were 4.94 and 5.18. The simulated RfDs were close to the temporary-tolerable daily intake (t-TDI) recommended by European Food Safety Authority (EFSA) in 2015 (t-TDI: 4 μg/kg·bw) and higher than the TDI of 2023 (0.2 ng/kg·bw). In conclusion, in-vitro toxicogenomics dose-response data combined with PBPK modeling can become a promising alternative new approach methodology (NAM) to support decision-making in chemical risk assessment. Based on the simulated RfDs derived from this NAM, the t-TDI set by EFSA in 2015 may be considered a safe exposure limit for mothers and fetuses at the current BPA intake levels in Chinese mothers. This study provided an animal-free new strategy for NAMs based risk assessment by combining toxicogenomics and computational toxicology.

Worldwide serum concentration-based probabilistic mixture risk assessment of perfluoroalkyl substances among pregnant women, infants, and children

Pregnant women, infants, and children are particularly vulnerable to perfluoroalkyl substances (PFASs), yet little is known about related health risks. Here, we aimed to study the four main PFASs: perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorohexanesulfonic acid (PFHxS), and assess the mixture risks of co-exposure to PFASs for pregnant women and children as well as for infants associated with maternal PFAS exposure at national and global scales, based on biomonitoring data on serum. We conducted a literature search and aggregated 69 data sources across 22 countries/regions from 2010 to 2020 to profile the serum concentrations of these four PFASs in pregnant women and children. Based on toxicity assessments by regulatory authorities, we determined conservative reference levels (RfLs) in the serum for the primary adverse effects of PFASs, including hepatic, developmental, and immune effects. The cumulative hazard quotient (HQ) was combined with probabilistic analysis to compare serum levels with RfLs and to quantify mixture risks. Our analysis revealed that PFOS was the dominant PFAS in maternal and child serum worldwide, with median levels 2.5-10 times higher than those of PFOA, PFNA, and PFHxS. The estimated global median serum levels of PFOS were 6.17 ng/mL for pregnant women and 4.85 ng/mL for children, and their immune effects in pregnant women and children are concerning as their cumulative HQs could exceed 1. For infants, the cumulative HQs for both developmental and immune effects could also be > 1, suggesting that maternal exposure to PFASs during pregnancy and breastfeeding may pose concerns for infant development and immunity. Our national and global serum database and risk assessment offer additional insights into PFAS exposures and mixture risks in susceptible populations, serving as a reference for evaluating the effectiveness of ongoing regulatory mitigation measures.

Binding, activity and risk assessment of bisphenols toward farnesoid X receptor pathway: In vitro and in silico study

Bisphenols have been identified as emerging environmental pollutants of high concern with potential adverse effects through interactions with receptor-mediated pathways. However, their potential mechanism of action and health risks through the farnesoid X receptor (FXR) pathway remain poorly understood. In the present study, we aimed to explore the potential disruption mechanism of bisphenols through the FXR signalling pathway. Receptor binding assays showed that bisphenols bound to FXR directly, with tetrabromobisphenol A (TBBPA; 34-fold), tetrachlorobisphenol A (TCBPA; 8.7-fold), bisphenol AF (BPAF; 2.0-fold), and bisphenol B (BPB; 1.9-fold) showing a significantly stronger binding potency than bisphenol A (BPA). In receptor transcriptional activity assays, bisphenols showed agonistic activity toward FXR, with BPAF, BPB, and bisphenol F (BPF) exhibiting higher activity than BPA, but TBBPA and TCBPA showing significantly weaker activity than BPA. Molecular docking results indicated that the number of hydrogen bonds dictated their binding strength. Intracellular concentrations of bisphenols were quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in receptor activity assays, and it was found that the intracellular concentrations of TBBPA and TCBPA were 40-fold lower than those of BPA. Using the bioactivity concentrations in the FXR receptor activity assay, the liver concentrations of bisphenols were estimated using physiologically-based pharmacokinetic (PBPK) models through their serum concentrations, and the hazard quotient (HQ) values were calculated. The results suggest a potentially high concern for the risk of activating the FXR pathway for some populations with high exposure. Overall, these results indicate that bisphenols can bind to and activate FXR receptors, and that the activation mechanism is dependent on cellular uptake and binding strength. This study provides important information regarding the exposure risk of bisphenols, which can promote the development of environmentally friendly bisphenols.

Human health risk assessment of 6:2 Cl-PFESA through quantitative in vitro to in vivo extrapolation by integrating cell-based assays, an epigenetic key event, and physiologically based pharmacokinetic modeling

Human health risk assessment of chemicals is essential but often relies on time-consuming and animal and labor-extensive procedures. Here, we develop a population-based, quantitative in vitro to in vivo extrapolation (QIVIVE) approach which depended on cellular effects monitored by in vitro assays, considered chemical internal concentration determined by LC-MS/MS, extrapolated into in vivo target tissue concentration through physiologically based pharmacokinetic (PBPK) modelling, and assessed populational health risk using in silico modelling. By applying this QIVIVE approach to 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA), as a representative of the emerging pollutants, we find that 6:2 Cl-PFESA disturbed lipid homeostasis in HepG2 cells through enhancement of lipid accumulation and fatty acid β-oxidation, during which miR-93-5p served as a key event towards toxicity and thus, could serve as an efficient toxicity marker for risk assessment; further, the disruption potency of lipid homeostasis of 6:2 Cl-PFESA for the most of studied populations in China might be of moderate concern. Together, our approach improved the reliability of QIVIVE during human health risk assessment, which can readily be used for other chemicals.

Health risk assessment of cadmium exposure by integration of an in silico physiologically based toxicokinetic model and in vitro tests

Cadmium (Cd) is a common environmental pollutant that can damage multiple organs, including the kidney. To prevent renal effects, international authorities have set health-based guidance values of Cd from epidemiological studies. To explore the health risk of Cd exposure and whether human equivalent doses (HEDs) derived from in vitro tests match the current guidance values, we integrated renal tubular epithelial cell-based assays with a physiologically based toxicokinetic model combined with the Monte Carlo method. For females, the HEDs (μg/kg/week) derived from KE2 (DNA damage), KE3 (cell cycle arrest), and KE4 (apoptosis) were 0.20 (2.5th-97.5th percentiles: 0.09-0.48), 0.52 (0.24-1.26), and 2.73 (1.27-6.57), respectively; for males the respective HEDs were 0.23 (0.10-0.49), 0.60 (0.27-1.30), and 3.11 (1.39-6.78). Among them, HED_KE4 (female) was close to the tolerable weekly intake (2.5 μg/kg/week) set by the European Food Safety Authority. The margin of exposure (MOE) derived from HED_KE4 (female) indicated that risks of renal toxicity for populations living in cadmium-contaminated regions should be of concern. This study provided a new approach methodology (NAM) for environmental chemical risk assessment using in silico and in vitro methods.

Integrating Physiologically Based Pharmacokinetic Modeling-Based Forward Dosimetry and in Vitro Bioassays to Improve the Risk Assessment of Organophosphate Esters on Human Health

The ability to accurately assess the health risks of contaminants is limited by the shortcomings of toxicological standards. Using organophosphate esters (OPEs) as an example, this study attempted to integrate physiologically based pharmacokinetic (PBPK)-based forward dosimetry and in vitro bioassays to assess the likelihood of contaminants inducing biological effects in humans. The total exposure level of OPEs for Chinese residents was 19.5 ± 8.71 ng/kg/day with inhalation being the main exposure pathway. Then, human PBPK models were developed for individual OPEs to predict their steady-state concentrations in human tissues, and the predicted median levels in blood were close to the measurements. The reference doses (RfDs) of OPEs based on in vitro bioassays were comparable to in vivo animal-derived RfDs, demonstrating the reliability of in vitro bioassays. Therefore, the likelihood of OPEs inducing bioactivities in humans (RQ_in-vitro) was calculated using in vitro toxicity data and OPE levels in human tissues. The RQ_in-vitros of tris(2-chloroisopropyl) phosphate, tris(1,3-dichloropropyl) phosphate, and triphenyl phosphate (7.68 × 10^-5-3.18 × 10^-3) were comparable to the risks assessed using traditional RfDs (5.22 × 10^-5-1.94 × 10^-3), indicating the credibility of the method proposed in this study. This study establishes a new framework to improve the health risk assessment of contaminants without sufficient toxicity data and minimize the need for animal experimentation.

TOXRIC: a comprehensive database of toxicological data and benchmarks

The toxic effects of compounds on environment, humans, and other organisms have been a major focus of many research areas, including drug discovery and ecological research. Identifying the potential toxicity in the early stage of compound/drug discovery is critical. The rapid development of computational methods for evaluating various toxicity categories has increased the need for comprehensive and system-level collection of toxicological data, associated attributes, and benchmarks. To contribute toward this goal, we proposed TOXRIC (https://toxric.bioinforai.tech/), a database with comprehensive toxicological data, standardized attribute data, practical benchmarks, informative visualization of molecular representations, and an intuitive function interface. The data stored in TOXRIC contains 113 372 compounds, 13 toxicity categories, 1474 toxicity endpoints covering in vivo/in vitro endpoints and 39 feature types, covering structural, target, transcriptome, metabolic data, and other descriptors. All the curated datasets of endpoints and features can be retrieved, downloaded and directly used as output or input to Machine Learning (ML)-based prediction models. In addition to serving as a data repository, TOXRIC also provides visualization of benchmarks and molecular representations for all endpoint datasets. Based on these results, researchers can better understand and select optimal feature types, molecular representations, and baseline algorithms for each endpoint prediction task. We believe that the rich information on compound toxicology, ML-ready datasets, benchmarks and molecular representation distribution can greatly facilitate toxicological investigations, interpretation of toxicological mechanisms, compound/drug discovery and the development of computational methods.

High-throughput screening paradigms in ecotoxicity testing: Emerging prospects and ongoing challenges

The rapidly increasing number of new production chemicals coupled with stringent implementation of global chemical management programs necessities a paradigm shift towards boarder uses of low-cost and high-throughput ecotoxicity testing strategies as well as deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity that can be used in effective risk assessment. The latter will require automated acquisition of biological data, new capabilities for big data analysis as well as computational simulations capable of translating new data into in vivo relevance. However, very few efforts have been so far devoted into the development of automated bioanalytical systems in ecotoxicology. This is in stark contrast to standardized and high-throughput chemical screening and prioritization routines found in modern drug discovery pipelines. As a result, the high-throughput and high-content data acquisition in ecotoxicology is still in its infancy with limited examples focused on cell-free and cell-based assays. In this work we outline recent developments and emerging prospects of high-throughput bioanalytical approaches in ecotoxicology that reach beyond in vitro biotests. We discuss future importance of automated quantitative data acquisition for cell-free, cell-based as well as developments in phytotoxicity and in vivo biotests utilizing small aquatic model organisms. We also discuss recent innovations such as organs-on-a-chip technologies and existing challenges for emerging high-throughput ecotoxicity testing strategies. Lastly, we provide seminal examples of the small number of successful high-throughput implementations that have been employed in prioritization of chemicals and accelerated environmental risk assessment.

Machine learning and artificial intelligence in toxicological sciences

Machine learning and artificial intelligence approaches have revolutionized multiple disciplines, including toxicology. This review summarizes representative recent applications of machine learning and artificial intelligence approaches in different areas of toxicology, including physiologically based pharmacokinetic (PBPK) modeling, quantitative structure-activity relationship modeling for toxicity prediction, adverse outcome pathway analysis, high-throughput screening, toxicogenomics, big data and toxicological databases. By leveraging machine learning and artificial intelligence approaches, now it is possible to develop PBPK models for hundreds of chemicals efficiently, to create in silico models to predict toxicity for a large number of chemicals with similar accuracies compared to in vivo animal experiments, and to analyze a large amount of different types of data (toxicogenomics, high-content image data, etc.) to generate new insights into toxicity mechanisms rapidly, which was impossible by manual approaches in the past. To continue advancing the field of toxicological sciences, several challenges should be considered: (1) not all machine learning models are equally useful for a particular type of toxicology data, and thus it is important to test different methods to determine the optimal approach; (2) current toxicity prediction is mainly on bioactivity classification (yes/no), so additional studies are needed to predict the intensity of effect or dose-response relationship; (3) as more data become available, it is crucial to perform rigorous data quality check and develop infrastructure to store, share, analyze, evaluate, and manage big data; and (4) it is important to convert machine learning models to user-friendly interfaces to facilitate their applications by both computational and bench scientists.

Chemical and biological assessments of environmental mixtures: A review of current trends, advances, and future perspectives

Considering the chemical complexity and toxicity data gaps of environmental mixtures, most studies evaluate the chemical risk individually. However, humans are usually exposed to a cocktail of chemicals in real life. Mixture health assessment remains to be a research area having significant knowledge gaps. Characterization of chemical composition and bioactivity/toxicity are the two critical aspects of mixture health assessments. This review seeks to introduce the recent progress and tools for the chemical and biological characterization of environmental mixtures. The state-of-the-art techniques include the sampling, extraction, rapid detection methods, and the in vitro, in vivo, and in silico approaches to generate the toxicity data of an environmental mixture. Application of these novel methods, or new approach methodologies (NAMs), has increased the throughput of generating chemical and toxicity data for mixtures and thus refined the mixture health assessment. Combined with computational methods, the chemical and biological information would shed light on identifying the bioactive/toxic components in an environmental mixture.

Integration of Toxicogenomics and Physiologically Based Pharmacokinetic Modeling in Human Health Risk Assessment of Perfluorooctane Sulfonate

Toxicogenomics and physiologically based pharmacokinetic (PBPK) models are useful approaches in chemical risk assessment, but the methodology to incorporate toxicogenomic data into a PBPK model to inform risk assessment remains to be developed. This study aimed to develop a probabilistic human health risk assessment approach by integrating toxicogenomic dose-response data and PBPK modeling using perfluorooctane sulfonate (PFOS) as a case study. Based on the available human in vitro and mouse in vivo toxicogenomic data, we identified the differentially expressed genes (DEGs) at each exposure paradigm/duration. Kyoto Encyclopedia of Genes and Genomes and disease ontology enrichment analyses were conducted on the DEGs to identify significantly enriched pathways and diseases. The dose-response data of DEGs were analyzed using the Bayesian benchmark dose (BMD) method. Using a previously published PBPK model, the gene BMDs were converted to human equivalent doses (HEDs), which were summarized to pathway and disease HEDs and then extrapolated to reference doses (RfDs) by considering an uncertainty factor of 30 for mouse in vivo data and 10 for human in vitro data. The results suggested that the median RfDs at different exposure paradigms were similar to the 2016 U.S. Environmental Protection Agency's recommended RfD, while the RfDs for the most sensitive pathways and diseases were closer to the recent European Food Safety Authority's guidance values. In conclusion, genomic dose-response data and PBPK modeling can be integrated to become a useful alternative approach in risk assessment of environmental chemicals. This approach considers multiple endpoints, provides toxicity mechanistic insights, and does not rely on apical toxicity endpoints.

Liver-Based Probabilistic Risk Assessment of Exposure to Organophosphate Esters via Dust Ingestion Using a Physiologically Based Toxicokinetic (PBTK) Model

Organophosphate esters (OPEs) are widely used and harmful to organisms and human health. Dust ingestion is an important exposure route for OPEs to humans. In this study, by integrating ToxCast high-throughput in vitro assays with in vitro to in vivo extrapolation (IVIVE) via physiologically based Toxicokinetic (PBTK) modeling, we assessed the hepatocyte-based health risk for humans around the world due to exposure to two typical OPEs (TPHP and TDCPP) through the dust ingestion exposure route. Results showed that the health guidance value of TPHP and TCDPP obtained in this study was lower than the value obtained through animal experiments. In addition, probabilistic risk assessment results indicate that populations worldwide are at low risk of exposure to TPHP and TDCPP through dust ingestion due to low estimated daily intakes (EDIs) which are much lower than the reference dose (RfDs) published by the US EPA, except in some regional cases. Most margin of exposure (MOE) ranges of TDCPP for children are less than 100, which indicates a moderately high risk. Researchers should be concerned about exposure to TDCPP in this area. The method proposed in this study is expected to be applied to the health risk assessment of other chemicals.

An integrated exposure and pharmacokinetic modeling framework for assessing population-scale risks of phthalates and their substitutes

To effectively incorporate in vitro-in silico-based methods into the regulation of consumer product safety, a quantitative connection between product phthalate concentrations and in vitro bioactivity data must be established for the general population. We developed, evaluated, and demonstrated a modeling framework that integrates exposure and pharmacokinetic models to convert product phthalate concentrations into population-scale risks for phthalates and their substitutes. A probabilistic exposure model was developed to generate the distribution of multi-route exposures based on product phthalate concentrations, chemical properties, and human activities. Pharmacokinetic models were developed to simulate population toxicokinetics using Bayesian analysis via the Markov chain Monte Carlo method. Both exposure and pharmacokinetic models demonstrated good predictive capability when compared with worldwide studies. The distributions of exposures and pharmacokinetics were integrated to predict the population distributions of internal dosimetry. The predicted distributions showed reasonable agreement with the U.S. biomonitoring surveys of urinary metabolites. The "source-to-outcome" local sensitivity analysis revealed that food contact materials had the greatest impact on body burden for di(2-ethylhexyl) adipate (DEHA), di-2-ethylhexyl phthalate (DEHP), di(isononyl) cyclohexane-1,2-dicarboxylate (DINCH), and di(2-propylheptyl) phthalate (DPHP), whereas the body burden of diethyl phthalate (DEP) was most sensitive to the concentration in personal care products. The upper bounds of predicted plasma concentrations showed no overlap with ToxCast in vitro bioactivity values. Compared with the in vitro-to-in vivo extrapolation (IVIVE) approach, the integrated modeling framework has significant advantages in mapping product phthalate concentrations to multi-route risks, and thus is of great significance for regulatory use with a relatively low input requirement. Further integration with new approach methodologies will facilitate these in vitro-in silico-based risk assessments for a broad range of products containing an equally broad range of chemicals.

Preparation of solid dispersion systems for enhanced dissolution of poorly water soluble diacerein: In-vitro evaluation, optimization and physiologically based pharmacokinetic modeling

Diacerein (DCN), a BCS II compound, suffers from poor aqueous solubility and limited bioavailability. Solid dispersion systems (SD) of DCN were prepared by solvent evaporation, using hydrophilic polymers. In-vitro dissolution studies were performed and dissolution parameters were evaluated. I-Optimal factorial design was employed to study the effect of formulation variables (drug:polymer ratio and polymer type) on the measured responses including; drug content (DC) (%), dissolution efficiency at 15 min (DE _{(15 min)}%) and 60 min (DE _{(60 min)}%) and mean dissolution time (MDT) (min). The optimized SD was selected, prepared and evaluated, allowing 10.83 and 3.42 fold increase in DE _{(15 min)}%, DE _{(60 min)}%, respectively and 6.07 decrease in MDT, compared to plain drug. DSC, XRD analysis and SEM micrographs confirmed complete amorphization of DCN within the optimized SD. Physiologically based pharmacokinetic (PBPK) modeling was employed to predict PK parameters of DCN in middle aged healthy adults and geriatrics. Simcyp^® software established in-vivo plasma concentration time curves of the optimized SD, compared to plain DCN. Relative bioavailability of the optimized SD compared to plain drug was 229.52% and 262.02% in healthy adults and geriatrics, respectively. Our study reports the utility of PBPK modeling for formulation development of BCS II APIs, via predicting their oral bio-performance.