Development and validation of a physiology-based model for the prediction of pharmacokinetics/toxicokinetics in rabbits

Physiologically based pharmacokinetic models for systemic disposition of protein therapeutics in rabbits

Physiologically based pharmacokinetic (PBPK) modelling is an important tool to predict drug disposition in the body. Rabbits play a pivotal role as a highly valued small animal model, particularly in the field of ocular therapeutics, where they serve as a crucial link between preclinical research and clinical applications. In this context, we have developed PBPK models designed specifically for rabbits, with a focus on accurately predicting the pharmacokinetic profiles of protein therapeutics following intravenous administration. Our goal was to comprehend the influence of key physiological factors on systemic disposition of antibodies and their functional derivatives. For the development of the systemic PBPK models, rabbit physiological factors such as gene expression, body weight, neonatal fragment crystallizable receptor (FcRn) binding, target binding, target concentrations, and target turnover rate were meticulously considered. Additionally, key protein parameters, encompassing hydrodynamic radius, binding kinetic constants (KD, koff), internal degradation of the protein-target complex, and renal clearance, were represented in the models. Our final rabbit models demonstrated a robust correlation between predicted and observed serum concentration-time profiles after single intravenous administration in rabbits, covering IgG, Fab, F(ab)2, Fc, and Fc fusion proteins from various publications. These pharmacokinetic simulations offer a promising platform for translating preclinical findings to clinical settings. The presented rabbit intravenous PBPK models lay an important foundation for more specific applications of protein therapeutics in ocular drug development.

Physiologically based kinetic (PBK) modeling of propiconazole using a machine learning-enhanced read-across approach for interspecies extrapolation

A significant challenge in the traditional human health risk assessment of agrochemicals is the uncertainty in quantifying the interspecies differences between animal models and humans. To work toward a more accurate and animal-free risk determination, new approaches such as physiologically based kinetic (PBK) modeling have been used to perform dosimetry extrapolation from animals to humans. However, the regulatory use and acceptance of PBK modeling is limited for chemicals that lack in vivo animal pharmacokinetic (PK) data, given the inability to evaluate models. To address these challenges, this study developed PBK models in the absence of in vivo PK data for the fungicide propiconazole, an activator of constitutive androstane receptor (CAR)/pregnane X receptor (PXR). A fit-for-purpose read-across approach was integrated with hierarchical clustering - an unsupervised machine learning algorithm, to bridge the knowledge gap. The integration allowed the incorporation of a broad spectrum of attributes for analog consideration, and enabled the analog selection in a simple, reproducible, and objective manner. The applicability was evaluated and demonstrated using penconazole (source) and three pseudo-unknown target chemicals (epoxiconazole, tebuconazole and triadimefon). Applying this machine learning-enhanced read-across approach, difenoconazole was selected as the most appropriate analog for propiconazole. A mouse PBK model was developed and evaluated for difenoconazole (source), with the mode of action of CAR/PXR activation incorporated to simulate the in vivo autoinduction of metabolism. The difenoconazole mouse model then served as a template for constructing the propiconazole mouse model. A parallelogram approach was subsequently applied to develop the propiconazole rat and human models, enabling a quantitative assessment of interspecies differences in dosimetry. This integrated approach represents a substantial advancement toward refining risk assessment of propiconazole within the framework of animal alternative safety assessment strategies.

Prediction of pharmacokinetics of an anaplastic lymphoma kinase inhibitor in rat and monkey: application of physiologically based pharmacokinetic model as an alternative tool to minimise animal studies

The pharmacokinetic (PK) and toxicokinetic profile of a drug from its preclinical evaluation helps the researcher determine whether the drug should be tested in humans based on its safety and toxicity.Preclinical studies require time and resources and are prone to error. Moreover, according to the United States Food and Drug Administration Modernisation Act 2, animal testing is no longer mandatory for new drug development, and an animal-free alternative, such as cell-based assay and computer models, can be used.Different physiologically based PK models were developed for an anaplastic lymphoma kinase inhibitor in rats and monkeys after intravenous and oral administration using its physicochemical properties and in vitro characterisation data.The developed model was validated against the in vivo data available in the literature, and the validation results were found within the acceptable limit. A parameter sensitivity analysis was performed to identify the properties of the compound influencing the PK profile.This work demonstrates the application of the physiologically based PK model to predict the PKs of a drug, which will eventually assist in reducing the number of animal studies and save time and cost of drug discovery and development.

AN OVERVIEW OF THE CURRENT CHALLENGES WHEN USING RABBITS FOR PRENATAL DEVELOPMENTAL TOXICITY STUDIES WITH CONSIDERATION OF THE IMPACT ON DATA INTERPRETATION

The rabbit prenatal developmental toxicity study is an international testing requirement for the identification and characterisation of the potential hazards of chemicals to human health. The importance of the rabbit for the detection of chemical teratogens is without question. However, the rabbit when used as a laboratory test species presents unique challenges affecting data interpretation. The purpose of this review is to identify the factors which may impact the behaviour of the pregnant rabbit and lead to significant inter-animal variability, confounding interpretation of maternal toxicity. Additionally, the importance of appropriate dose selection is discussed not least because of the conflicting guidance for identifying and defining acceptable maternal toxicity that lack reference to the rabbit in particular. The test guideline prenatal developmental toxicity study is often unable to distinguish between developmental effects as a consequence of maternal toxicity and those that are a direct effect of the test chemical on the offspring yet there is increasing pressure to use the highest possible dose levels to induce significant maternal toxicity which for the rabbit, a species little understood in toxicological terms and one that is highly susceptible to stress, is defined by very few endpoints. Interpretation of study data is further confounded by dose selection yet the developmental effects, even in the presence of maternal toxicity, are being used in Europe as the basis for classifying agents as reproductive hazards and the maternal effects are being used to define key reference values.

Quantitative systems pharmacology of the eye: Tools and data for ocular QSP

Good eyesight belongs to the most-valued attributes of health, and diseases of the eye are a significant healthcare burden. Case numbers are expected to further increase in the next decades due to an aging society. The development of drugs in ophthalmology, however, is difficult due to limited accessibility of the eye, in terms of drug administration and in terms of sampling of tissues for drug pharmacokinetics (PKs) and pharmacodynamics (PDs). Ocular quantitative systems pharmacology models provide the opportunity to describe the distribution of drugs in the eye as well as the resulting drug-response in specific segments of the eye. In particular, ocular physiologically-based PK (PBPK) models are necessary to describe drug concentration levels in different regions of the eye. Further, ocular effect models using molecular data from specific cellular systems are needed to develop dose-response correlations. We here describe the current status of PK/PBPK as well as PD models for the eyes and discuss cellular systems, data repositories, as well as animal models in ophthalmology. The application of the various concepts is highlighted for the development of new treatments for postoperative fibrosis after glaucoma surgery.

A multi-model approach to predict efficacious clinical dose for an anti-TGF-β antibody (GC2008) in the treatment of osteogenesis imperfecta

Osteogenesis imperfecta (OI) is a heterogeneous group of inherited bone dysplasias characterized by reduced skeletal mass and bone fragility. Although the primary manifestation of the disease involves the skeleton, OI is a generalized connective tissue disorder that requires a multidisciplinary treatment approach. Recent studies indicate that application of a transforming growth factor beta (TGF-β) neutralizing antibody increased bone volume fraction (BVF) and strength in an OI mouse model and improved bone mineral density (BMD) in a small cohort of patients with OI. In this work, we have developed a multitiered quantitative pharmacology approach to predict human efficacious dose of a new anti-TGF-β antibody drug candidate (GC2008). This method aims to translate GC2008 pharmacokinetic/pharmacodynamic (PK/PD) relationship in patients, using a number of appropriate mathematical models and available preclinical and clinical data. Compartmental PK linked with an indirect PD effect model was used to characterize both pre-clinical and clinical PK/PD data and predict a GC2008 dose that would significantly increase BMD or BVF in patients with OI. Furthermore, a physiologically-based pharmacokinetic model incorporating GC2008 and the body's physiological properties was developed and used to predict a GC2008 dose that would decrease the TGF-β level in bone to that of healthy individuals. By using multiple models, we aim to reveal information for different aspects of OI disease that will ultimately lead to a more informed dose projection of GC2008 in humans. The different modeling efforts predicted a similar range of pharmacologically relevant doses in patients with OI providing an informed approach for an early clinical dose setting.

A critical review of effect modeling for ecological risk assessment of plant protection products

A wide diversity of plant protection products (PPP) is used for crop protection leading to the contamination of soil, water, and air, which can have ecotoxicological impacts on living organisms. It is inconceivable to study the effects of each compound on each species from each compartment, experimental studies being time consuming and cost prohibitive, and animal testing having to be avoided. Therefore, numerous models are developed to assess PPP ecotoxicological effects. Our objective was to provide an overview of the modeling approaches enabling the assessment of PPP effects (including biopesticides) on the biota. Six categories of models were inventoried: (Q)SAR, DR and TKTD, population, multi-species, landscape, and mixture models. They were developed for various species (terrestrial and aquatic vertebrates and invertebrates, primary producers, micro-organisms) belonging to diverse environmental compartments, to address different goals (e.g., species sensitivity or PPP bioaccumulation assessment, ecosystem services protection). Among them, mechanistic models are increasingly recognized by EFSA for PPP regulatory risk assessment but, to date, remain not considered in notified guidance documents. The strengths and limits of the reviewed models are discussed together with improvement avenues (multigenerational effects, multiple biotic and abiotic stressors). This review also underlines a lack of model testing by means of field data and of sensitivity and uncertainty analyses. Accurate and robust modeling of PPP effects and other stressors on living organisms, from their application in the field to their functional consequences on the ecosystems at different scales of time and space, would help going toward a more sustainable management of the environment. Graphical Abstract Combination of the keyword lists composing the first bibliographic query. Columns were joined together with the logical operator AND. All keyword lists are available in Supplementary Information at https://doi.org/10.5281/zenodo.5775038 (Larras et al. 2021).

Quantitative Comparison of Avian and Mammalian Physiologies for Parameterization of Physiologically Based Kinetic Models

Physiologically based kinetic (PBK) models facilitate chemical risk assessment by predicting in vivo exposure while reducing the need for animal testing. PBK models for mammals have seen significant progress, which has yet to be achieved for avian systems. Here, we quantitatively compare physiological, metabolic and anatomical characteristics between birds and mammals, with the aim of facilitating bird PBK model development. For some characteristics, there is considerable complementarity between avian and mammalian species with identical values for the following: blood hemoglobin and hemoglobin concentrations per unit erythrocyte volume together with relative weights of the liver, heart, and lungs. There are also systematic differences for some major characteristics between avian and mammalian species including erythrocyte volume, plasma concentrations of albumin, total protein and triglyceride together with liver cell size and relative weights of the kidney, spleen, and ovary. There are also major differences between characteristics between sexually mature and sexually immature female birds. For example, the relative weights of the ovary and oviduct are greater in sexually mature females compared to immature birds as are the plasma concentrations of triglyceride and vitellogenin. Both these sets of differences reflect the genetic "blue print" inherited from ancestral archosaurs such as the production of large eggs with yolk filled oocytes surrounded by egg white proteins, membranes and a calciferous shell together with adaptions for flight in birds or ancestrally in flightless birds.

Streamlining physiologically‐based pharmacokinetic model design for intravenous delivery of nanoparticle drugs

Physiologically‐based pharmacokinetic (PBPK) modeling for nanoparticles elucidates the nanoparticle drug’s disposition in the body and serves a vital role in drug development and clinical studies. This paper offers a systematic and tutorial‐like approach to developing a model structure and writing distribution ordinary differential equations based on asking binary questions involving the physicochemical nature of the drug in question. Further, by synthesizing existing knowledge, we summarize pertinent aspects in PBPK modeling and create a guide for building model structure and distribution equations, optimizing nanoparticle and non‐nanoparticle specific parameters, and performing sensitivity analysis and model validation. The purpose of this paper is to facilitate a streamlined model development process for students and practitioners in the field.

A workflow to build PBTK models for novel species

Physiology-based pharmacokinetic and toxicokinetic (PBPK/TK) models allow us to simulate the concentration of xenobiotica in the plasma and different tissues of an organism. PBPK/TK models are therefore routinely used in many fields of life sciences to simulate the physiological concentration of exogenous compounds in plasma and tissues. The application of PBTK models in ecotoxicology, however, is currently hampered by the limited availability of models for focal species. Here, we present a best practice workflow that describes how to build PBTK models for novel species. To this end, we extrapolated eight previously established rabbit models for several drugs to six additional mammalian species (human, beagle, rat, monkey, mouse, and minipig). We used established PBTK models for these species to account for the species-specific physiology. The parameter sensitivity in the resulting 56 PBTK models was systematically assessed to rank the relevance of the parameters on overall model performance. Interestingly, more than 80% of the 609 considered model parameters showed a negligible sensitivity throughout all models. Only approximately 5% of all parameters had a high sensitivity in at least one of the PBTK models. This approach allowed us to rank the relevance of the various parameters on overall model performance. We used this information to formulate a best practice guideline for the efficient development of PBTK models for novel animal species. We believe that the workflow proposed in this study will significantly support the development of PBTK models for new animal species in the future.

Predictive modeling of aspirin-triggered resolvin D1 pharmacokinetics for the study of Sjögren's syndrome

OBJECTIVES

Sjögren's syndrome (SS) is an autoimmune disease that causes chronic inflammation of the salivary glands leading to secretory dysfunction. Previous studies demonstrated that aspirin-triggered resolvin D1 (AT-RvD1) reduces inflammation and restores tissue integrity in salivary glands. Specifically, progression of SS-like features in NOD/ShiLtJ mice can be systemically halted using AT-RvD1 prior or after disease onset to downregulate proinflammatory cytokines, upregulate anti-inflammatory molecules, and restore saliva production. Therefore, the goal of this paper was to create a physiologically based pharmacokinetic (PBPK) model to offer a reasonable starting point for required total AT-RvD1 dosage to be administered in future mice and humans thereby eliminating the need for excessive use of animals and humans in preclinical and clinical trials, respectively. Likewise, PBPK modeling was employed to increase the range of testable scenarios for elucidating the mechanisms under consideration.

MATERIALS AND METHODS

Pharmacokinetics following intravenous administration of a 0.1 mg/kg dose of AT-RvD1 in NOD/ShiLtJ were predicted in both plasma and saliva using PBPK modeling with PK-Sim® and MoBi® Version 7.4 software.

RESULTS

The model provides high-value pathways for future validation via in vivo studies in NOD/ShiLtJ to corroborate the findings themselves while also establishing this method as a means to better target drug development and clinical study design.

CONCLUSIONS

Clinical and basic research would benefit from knowledge of the potential offered by computer modeling. Specifically, short-term utility of these pharmacokinetic modeling findings involves improved targeting of in vivo studies as well as longer term prospects for drug development and/or better designs for clinical trials.

Credibility of In Silico Trial Technologies-A Theoretical Framing

Different research communities have developed various approaches to assess the credibility of predictive models. Each approach usually works well for a specific type of model, and under some epistemic conditions that are normally satisfied within that specific research domain. Some regulatory agencies recently started to consider evidences of safety and efficacy on new medical products obtained using computer modelling and simulation (which is referred to as In Silico Trials); this has raised the attention in the computational medicine research community on the regulatory science aspects of this emerging discipline. But this poses a foundational problem: in the domain of biomedical research the use of computer modelling is relatively recent, without a widely accepted epistemic framing for model credibility. Also, because of the inherent complexity of living organisms, biomedical modellers tend to use a variety of modelling methods, sometimes mixing them in the solution of a single problem. In such context merely adopting credibility approaches developed within other research communities might not be appropriate. In this paper we propose a theoretical framing for assessing the credibility of a predictive models for In Silico Trials, which accounts for the epistemic specificity of this research field and is general enough to be used for different type of models.

ATLAS mPBPK: A MATLAB-Based Tool for Modeling and Simulation of Minimal Physiologically-Based Pharmacokinetic Models

Minimal physiologically-based pharmacokinetic (mPBPK) models are frequently used to model plasma pharmacokinetic (PK) data and utilize and yield physiologically relevant parameters. Compared with classical compartment and whole-body physiologically-based pharmacokinetic modeling approaches, mPBPK models maintain a structure of intermediate physiological complexity that can be adequately informed by plasma PK data. In this tutorial, we present a MATLAB-based tool for the modeling and simulation of mPBPK models (ATLAS mPBPK) of small and large molecules. This tool enables the users to perform the following: (i) PK data visualization, (ii) simulation, (iii) parameter optimization, and (iv) local sensitivity analysis of mPBPK models in a simple and efficient manner. In addition to the theoretical background and implementation of the different tool functionalities, this tutorial includes simulation and sensitivity analysis showcases of small and large molecules with and without target-mediated drug disposition.

On the unphysical hypotheses in pharmacokinetics and oral drug absorption: Time to utilize instantaneous rate coefficients instead of rate constants

This work aims to explore the unphysical assumptions associated with i) the homogeneity of the well mixed compartments of pharmacokinetics and ii) the diffusion limited model of drug dissolution. To this end, we i) tested the homogeneity hypothesis using Monte Carlo simulations for a reaction and a diffusional process that take place in Euclidean and fractal media, ii) re-considered the flip-flop kinetics assuming that the absorption rate for a one-compartment model is governed by an instantaneous rate coefficient instead of a rate constant, and, iii) re-considered the extent of drug absorption as a function of dose using an in vivo reaction limited model of drug dissolution with integer and non-integer stoichiometry values. We found that drug diffusional processes and reactions are slowed down in heterogeneous media and the environmental heterogeneity leads to increased fluctuations of the measurable quantities. Highly variable experimental literature data with measurements in intrathecal space and gastrointestinal fluids were explained accordingly. Next, by applying power law and Weibull input functions to a one-compartment model of disposition we show that the shape of concentration-time curves is highly dependent on the time exponent of the input functions. Realistic examples based on PK data of three compounds known to exhibit flip-flop kinetics are analyzed. The need to use time dependent coefficients instead of rate constants in PBPK modeling and virtual bioequivalence is underlined. Finally, the shape of the fraction absorbed as a function of dose plots, using an in vivo reaction limited model of drug dissolution were found to be dependent on the stoichiometry value and the solubility of drug. Ascending and descending limbs were observed for the higher stoichiometries (2.0 and 1.5) with the low solubility drug. In contrast, for the more soluble drug, a continuous increase of fraction absorbed as a function of dose is observed when the higher stoichiometries are used (2.0 and 1.5). For both drugs, the fraction absorbed for the lower values of stoichiometry (0.7 and 1.0) exhibit a non-dependency on dose profile. Our results give an insight into the complex picture of in vivo drug dissolution since diffusion-limited and reaction-limited processes seem to operate under in vivo conditions concurrently.