The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment

Comprehensive approaches to preclinical evaluation of monoclonal antibodies and their next-generation derivatives

Biotherapeutics hold great promise for the treatment of several diseases and offer innovative possibilities for new treatments that target previously unaddressed medical needs. Despite successful transitions from preclinical to clinical stages and regulatory approval, there are instances where adverse reactions arise, resulting in product withdrawals. As a result, it is essential to conduct thorough evaluations of safety and effectiveness on an individual basis. This article explores current practices, challenges, and future approaches in conducting comprehensive preclinical assessments to ensure the safety and efficacy of biotherapeutics including monoclonal antibodies, toxin-conjugates, bispecific antibodies, single-chain antibodies, Fc-engineered antibodies, antibody mimetics, and siRNA-antibody/peptide conjugates.

Utility of life stage-specific chemical risk assessments based on New Approach Methodologies (NAMs)

The safety assessments for chemicals targeted for use or expected to be exposed to specific life stages, including infancy, childhood, pregnancy and lactation, and geriatrics, need to account for extrapolation of data from healthy adults to these populations to assess their human health risk. However, often adequate and relevant toxicity or pharmacokinetic (PK) data of chemicals in specific life stages are not available. For such chemicals, New Approach Methodologies (NAMs), such as physiologically based pharmacokinetic (PBPK) modeling, biologically based dose response (BBDR) modeling, in vitro to in vivo extrapolation (IVIVE), etc. can be used to understand the variability of exposure and effects of chemicals in specific life stages and assess their associated risk. A life stage specific PBPK model incorporates the physiological and biochemical changes associated with each life stage and simulates their impact on the absorption, distribution, metabolism, and elimination (ADME) of these chemicals. In our review, we summarize the parameterization of life stage models based on New Approach Methodologies (NAMs) and discuss case studies that highlight the utility of a life stage based PBPK modeling for risk assessment. In addition, we discuss the utility of artificial intelligence (AI)/machine learning (ML) and other computational models, such as those based on in vitro data, as tools for estimation of relevant physiological or physicochemical parameters and selection of model. We also discuss existing gaps in the available toxicological datasets and current challenges that need to be overcome to expand the utility of NAMs for life stage-specific chemical risk assessment.

A guide to the use of bioassays in exploration of natural resources

Bioassays are the main tool to decipher bioactivities from natural resources thus their selection and quality are critical for optimal bioprospecting. They are used both in the early stages of compounds isolation/purification/identification, and in later stages to evaluate their safety and efficacy. In this review, we provide a comprehensive overview of the most common bioassays used in the discovery and development of new bioactive compounds with a focus on marine bioresources. We present a comprehensive list of practical considerations for selecting appropriate bioassays and discuss in detail the bioassays typically used to explore antimicrobial, antibiofilm, cytotoxic, antiviral, antioxidant, and anti-ageing potential. The concept of quality control and bioassay validation are introduced, followed by safety considerations, which are critical to advancing bioactive compounds to a higher stage of development. We conclude by providing an application-oriented view focused on the development of pharmaceuticals, food supplements, and cosmetics, the industrial pipelines where currently known marine natural products hold most potential. We highlight the importance of gaining reliable bioassay results, as these serve as a starting point for application-based development and further testing, as well as for consideration by regulatory authorities.

Studying mixture effects on uptake and tissue distribution of PFAS in zebrafish (Danio rerio) using physiologically based kinetic (PBK) modelling

Per- and polyfluoroalkyl substances (PFAS) are ubiquitously distributed in the aquatic environment. They include persistent, mobile, bioaccumulative, and toxic chemicals and it is therefore critical to increase our understanding on their adsorption, distribution, metabolism, excretion (ADME). The current study focused on uptake of seven emerging PFAS in zebrafish (Danio rerio) and their potential maternal transfer. In addition, we aimed at increasing our understanding on mixture effects on ADME by developing a physiologically based kinetic (PBK) model capable of handling co-exposure scenarios of any number of chemicals. All studied chemicals were taken up in the fish to varying degrees, whereas only perfluorononanoate (PFNA) and perfluorooctanoate (PFOA) were quantified in all analysed tissues. Perfluorooctane sulfonamide (FOSA) was measured at concerningly high concentrations in the brain (Cmax over 15 μg/g) but also in the liver and ovaries. All studied PFAS were maternally transferred to the eggs, with FOSA and 6:2 perfluorooctane sulfonate (6,2 FTSA) showing significant (p < 0.02) signs of elimination from the embryos during the first 6 days of development, while perfluorobutane sulfonate (PFBS), PFNA, and perfluorohexane sulfonate (PFHxS) were not eliminated in embryos during this time-frame. The mixture PBK model resulted in >85 % of predictions within a 10-fold error and 60 % of predictions within a 3-fold error. At studied levels of PFAS exposure, competitive binding was not a critical factor for PFAS kinetics. Gill surface pH influenced uptake for some carboxylates but not the sulfonates. The developed PBK model provides an important tool in understanding kinetics under complex mixture scenarios and this use of New Approach Methodologies (NAMs) is critical in future risk assessment of chemicals and early warning systems.

In Silico and In Vivo Pharmacokinetic Evaluation of 84-B10, a Novel Drug Candidate against Acute Kidney Injury and Chronic Kidney Disease

Acute kidney injury (AKI) and chronic kidney disease (CKD) have become public health problems due to high morbidity and mortality. Currently, drugs recommended for patients with AKI or CKD are extremely limited, and candidates based on a new mechanism need to be explored. 84-B10 is a novel 3-phenylglutaric acid derivative that can activate the mitochondrial protease, Lon protease 1 (LONP1), and may protect against cisplatin-induced AKI and unilateral ureteral obstruction- or 5/6 nephrectomy [5/6Nx]-induced CKD model. Preclinical studies have shown that 84-B10 has a good therapeutic effect, low toxicity, and is a good prospect for further development. In the present study, the UHPLC-MS/MS method was first validated then applied to the pharmacokinetic study and tissue distribution of 84-B10 in rats. Physicochemical properties of 84-B10 were then acquired in silico. Based on these physicochemical and integral physiological parameters, a physiological based pharmacokinetic (PBPK) model was developed using the PK-Sim platform. The fitting accuracy was estimated with the obtained experimental data. Subsequently, the validated model was employed to predict the pharmacokinetic profiles in healthy and chronic kidney injury patients to evaluate potential clinical outcomes. Cmax in CKD patients was about 3250 ng/mL after a single dose of 84-B10 (0.41 mg/kg), and Cmax,ss was 1360 ng/mL after multiple doses. This study may serve in clinical dosage setting in the future.

Unraveling biomarkers of exposure for tenuazonic acid through urinary metabolomics

Mycotoxins are secondary metabolites produced by fungi such as Aspergillus, Alternaria, and Penicillium, affecting nearly 80% of global food crops. Tenuazonic acid (TeA) is the major mycotoxin produced by Alternaria alternata, a prevalent pathogen affecting plants, fruits, and vegetables. TeA is notably prevalent in European diets, however, TeA biomarkers of exposure and metabolites remain unknown. This research aims to bridge this knowledge-gap by gaining insights about human TeA exposure and metabolization. Nine subjects were divided into two groups. The first group received a single bolus of TeA at the Threshold of Toxicological Concern (TTC) to investigate the presence of TeA urinary biomarkers, while the second group served as a control. Sixty-nine urinary samples were prepared and analyzed using UPLC-Xevo TQ-XS for TeA quantification and UPLC-Orbitrap Exploris for polar metabolome acquisition. TeA was rapidly excreted during the first 13 h and the fraction extracted was 0.39 ± 0.22. The polar metabolome compounds effectively discriminating the two groups were filtered using Orthogonal Partial Least Squares-Discriminant Analysis and subsequently annotated (n = 122) at confidence level 4. Finally, the urinary metabolome was compared to in silico predicted TeA metabolites. Nine metabolites, including oxidized, N-alkylated, desaturated, glucuronidated, and sulfonated forms of TeA were detected.

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.

Exploring the complexities of drug formulation selection, storage, and shelf-life for exploration spaceflight

Medications have been a part of space travel dating back to the Apollo missions. Currently, medical kits aboard the International Space Station (ISS) contain medications and supplies to treat a variety of possible medical events. As we prepare for more distant exploration missions to Mars and beyond, risk management planning for astronaut healthcare should include the assembly of a medication formulary that is comprehensive enough to prevent or treat anticipated medical events, remains safe and chemically stable, and retains sufficient potency to last for the duration of the mission. Emerging innovation and technologies in pharmaceutical development, delivery, quality maintenance, and validation offer promise for addressing these challenges. The present editorial will summarize the current state of knowledge regarding innovative formulary optimization strategies, pharmaceutical stability assessment techniques, and storage and packaging solutions that could enhance drug safety and efficacy for future exploration spaceflight missions.

Development and Evaluation of Amorphous Solid Dispersion of Riluzole with PBPK Model to Simulate the Pharmacokinetic Profile

In the current work, screening of polymers viz. polyacrylic acid (PAA), polyvinyl pyrrolidone vinyl acetate (PVP VA), and hydroxypropyl methyl cellulose acetate succinate (HPMC AS) based on drug-polymer interaction and wetting property was done for the production of a stable amorphous solid dispersion (ASD) of a poorly water-soluble drug Riluzole (RLZ). PAA showed maximum interaction and wetting property hence, was selected for further studies. Solid state characterization studies confirmed the formation of ASD with PAA. Saturation solubility, dissolution profile, and in vivo pharmacokinetic data of the ASD formulation were generated in rats against its marketed tablet Rilutor. The RLZ:PAA ASD showed exponential enhancement in the dissolution of RLZ. Predicted and observed pharmacokinetic data in rats showed enhanced area under curve (AUC) and Cmax in plasma and brain with respect to Rilutor. Furthermore, a physiologically based pharmacokinetic (PBPK) model of rats for Rilutor and RLZ ASD was developed and then extrapolated to humans where physiological parameters were changed along with a biochemical parameter. The partition coefficient was kept similar in both species. The model was used to predict different exposure scenarios, and the simulated data was compared with observed data points. The PBPK model simulated Cmax and AUC was within two times the experimental data for plasma and brain. The Cmax and AUC in the brain increased with ASD compared to Rilutor for humans showing its potential in improving its biopharmaceutical performance and hence enhanced therapeutic efficacy. The model can predict the RLZ concentration in multiple compartments including plasma and liver.

Computational Amendment of Parenteral In Situ Forming Particulates' Characteristics: Design of Experiment and PBPK Physiological Modeling

Lipid and/or polymer-based drug conjugates can potentially minimize side effects by increasing drug accumulation at target sites and thus augment patient compliance. Formulation factors can present a potent influence on the characteristics of the obtained systems. The selection of an appropriate solvent with satisfactory rheological properties, miscibility, and biocompatibility is essential to optimize drug release. This work presents a computational study of the effect of the basic formulation factors on the characteristics of the obtained in situ-forming particulates (IFPs) encapsulating a model drug using a 21.31 full factorial experimental design. The emulsion method was employed for the preparation of lipid and/or polymer-based IFPs. The IFP release profiles and parameters were computed. Additionally, a desirability study was carried out to choose the optimum formulation for further morphological examination, rheological study, and PBPK physiological modeling. Results revealed that the type of particulate forming agent (lipid/polymer) and the incorporation of structure additives like Brij 52 and Eudragit RL can effectively augment the release profile as well as the burst of the drug. The optimized formulation exhibited a pseudoplastic rheological behavior and yielded uniformly spherical-shaped dense particulates with a PS of 573.92 ± 23.5 nm upon injection. Physiological modeling simulation revealed the pioneer pharmacokinetic properties of the optimized formulation compared to the observed data. These results assure the importance of controlling the formulation factors during drug development, the potentiality of the optimized IFPs for the intramuscular delivery of piroxicam, and the reliability of PBPK physiological modeling in predicting the biological performance of new formulations with effective cost management.

Physiologically Based Pharmacokinetic Modeling of Extracellular Vesicles

Extracellular vesicles (EVs) are lipid membrane bound-cell-derived structures that are a key player in intercellular communication and facilitate numerous cellular functions such as tumor growth, metastasis, immunosuppression, and angiogenesis. They can be used as a drug delivery platform because they can protect drugs from degradation and target specific cells or tissues. With the advancement in the technologies and methods in EV research, EV-therapeutics are one of the fast-growing domains in the human health sector. Therapeutic translation of EVs in clinics requires assessing the quality, safety, and efficacy of the EVs, in which pharmacokinetics is very crucial. We report here the application of physiologically based pharmacokinetic (PBPK) modeling as a principal tool for the prediction of absorption, distribution, metabolism, and excretion of EVs. To create a PBPK model of EVs, researchers would need to gather data on the size, shape, and composition of the EVs, as well as the physiological processes that affect their behavior in the body. The PBPK model would then be used to predict the pharmacokinetics of drugs delivered via EVs, such as the rate at which the drug is absorbed and distributed throughout the body, the rate at which it is metabolized and eliminated, and the maximum concentration of the drug in the body. This information can be used to optimize the design of EV-based drug delivery systems, including the size and composition of the EVs, the route of administration, and the dose of the drug. There has not been any dedicated review article that describes the PBPK modeling of EV. This review provides an overview of the absorption, distribution, metabolism, and excretion (ADME) phenomena of EVs. In addition, we will briefly describe the different computer-based modeling approaches that may help in the future of EV-based therapeutic research.