Mathematical modeling and simulation in animal health – Part II : principles, methods, applications, and value of physiologically based pharmacokinetic modeling in veterinary medicine and food safety assessment

Population Pharmacokinetics and Absolute Oral Bioavailability of Lasalocid after Single Intravenous and Intracrop Administration in Laying Hens

Lasalocid sodium is a polyether carboxylic ionophore agent authorized by the EU for use as a coccidiostat in broilers, turkeys, and pullets up to 16 weeks of age, except for laying hens. However, laying hens are the most common nontarget species exposed to lasalocid sodium, mainly due to cross-contamination from feed mills. This exposure may result in potential drug residue deposition in eggs, which could potentially expose consumers to the drug. The breeds commonly used for commercial egg production in Poland are Isa Brown and Green-legged Partridge hens, which have been found to significantly differ in egg-laying performance. This variability may also affect the pharmacokinetics of lasalocid. Data on lasalocid plasma pharmacokinetics in laying hens are lacking. In this study, we aimed to determine typical population pharmacokinetic parameters, absolute oral bioavailability, and how breed may influence the pharmacokinetics of lasalocid. Twenty-layer hens of the two breeds were used in this study. Lasalocid was administered orally at a single dose of either 1 mg or 5 mg/kg body weight or intravenously at a dose of 1 mg/kg body weight, in a crossover design with a three-week washout period between study periods. Blood samples were collected for 72 h, and lasalocid concentrations were measured using high-performance liquid chromatography with fluorescence detection. A population pharmacokinetic analysis was conducted using nonlinear mixed effects modeling. Standard numerical and graphical criteria were used to select the best model, and a stepwise covariate modeling approach was used to determine any influencing factors. The best model was a three-compartment mammillary model with first-order absorption, transit compartments, and linear elimination. The estimated absolute oral bioavailability was low (36%). It was found that breed significantly influenced not only absorption but also the elimination of lasalocid. This study revealed that lasalocid absorption and elimination varied between the two breeds. This variability in pharmacokinetics may result in breed-related differences in drug residue accumulation in eggs, and ultimately, the risk associated with consumer exposure to drug residues may also vary.

Recent Advancements in Molecularly Imprinted Polymers Based Aptasensors: Critical Role of Nanomaterials for the Efficient Food Safety Analysis

Biosensors are being studied extensively for their ability to detect and analyze molecules. There has been a growing interest in combining molecular imprinted polymers (MIPs) and aptamers to create hybrid recognition elements that offer advantages such as target binding, sensitivity, selectivity, and stability. These hybrid elements have been successfully used in identifying a wide range of analytes in food samples. However, the application of MIP-based aptasensors in different sensing approaches is still challenging due to the low conductivity of MIPs-aptamers and limited adsorption capacity of MIPs. To address these limitations, researchers have been exploring the use of nanomaterials (NMs) to design efficient multiple-recognition systems that exploit the synergies between aptamers and MIPs. These hybrid systems can enhance the sensitivity and selectivity of MIP-based aptasensors in quantifying analytical samples. This review provides a comprehensive overview of recent advancements in the field of MIP-based aptasensors. It also introduces technologies that combine MIPs and aptamers to achieve higher sensitivity and selectivity in quantifying analytical samples. The review also highlights potential future trends and practical approaches that can be employed to address the limitations of MIP-based aptasensors, including the use of new NMs, the development of new fabrication techniques, and the integration of MIP-based aptasensors with other analytical tools.

A physiologically based pharmacokinetic/pharmacodynamic model to determine dosage regimens and withdrawal intervals of aditoprim against Streptococcus suis

Introduction: Streptococcus suis (S. suis) is a zoonotic pathogen threatening public health. Aditoprim (ADP), a novel veterinary medicine, exhibits an antibacterial effect against S. suis. In this study, a physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model was used to determine the dosage regimens of ADP against S. suis and withdrawal intervals. Methods: The PBPK model of ADP injection can predict drug concentrations in plasma, liver, kidney, muscle, and fat. A semi-mechanistic pharmacodynamic (PD) model, including susceptible subpopulation and resistant subpopulation, is successfully developed by a nonlinear mixed-effect model to evaluate antibacterial effects. An integrated PBPK/PD model is conducted to predict the time-course of bacterial count change and resistance development under different ADP dosages. Results: ADP injection, administrated at 20 mg/kg with 12 intervals for 3 consecutive days, can exert an excellent antibacterial effect while avoiding resistance emergence. The withdrawal interval at the recommended dosage regimen is determined as 18 days to ensure food safety. Discussion: This study suggests that the PBPK/PD model can be applied as an effective tool for the antibacterial effect and safety evaluation of novel veterinary drugs.

Design of a generic model based on physiology for persistent organic pollutants in laying hens: Applications on chlordecone and chlorinated paraffins

A Physiology Based Pharmacokinetic (PBPK) model has been developed to predict the kinetics of Persistent Organic Pollutants (POPs) in laying hens. Different datasets have enabled the calibration of the model for chlordecone (CLD), an organochlorine pesticide used in the French West Indies between 1972 and 1993, as well as for chlorinated paraffins (CPs), widely used for various industrial applications worldwide. For this purpose, the sensitivity analysis showed that intake parameters, laying rate, partition coefficients of yolk, hepatic clearance, percentage of metabolism and age were key parameters. Applied to CLD and CPs, this model shows a good capacity for prediction, with 88 % of the experimental values ranging within 1.5-fold of the predicted value at steady state for CPs and 100 % for CLD. The fine modelling of the physiology and the laying process contributes to precision of the model and gives genericity, enabling the switch from one bird species to another. The model can be implemented with other POPs if the clearance and partition coefficient are known.

Bayesian estimation in veterinary pharmacology: A conceptual and practical introduction

Sophisticated mathematical and computational tools have become widespread and important in veterinary pharmacology. Although the theoretical basis and practical applications of these have been widely explored in the literature, statistical inference in the context of these models has received less attention. Optimization methods, often with frequentist statistical inference, have been predominant. In contrast, Bayesian statistics have not been widely applied, but offer both practical utility and arguably greater interpretability. Veterinary pharmacology applications are generally well supported by relevant prior information, from either existing substantive knowledge, or an understanding of study and model design. This facilitates practical implementation of Bayesian analyses that can take advantage of this knowledge. This essay will explore the specification of Bayesian models relevant to veterinary pharmacology, including demonstration of prior selection, and illustrate the capability of these models to generate practically useful statistics, including uncertainty statements, that are difficult or impossible to obtain otherwise. Case studies using simulated data will describe applications in clinical trials, pharmacodynamics, and pharmacokinetics, all including multilevel modeling. This content may serve as a suitable starting point for researchers in veterinary pharmacology and related disciplines considering Bayesian estimation for their applied work.

Physiologically based toxicokinetic modelling of Tri(2-chloroethyl) phosphate (TCEP) in mice accounting for multiple exposure routes

Exposure routes are important for health risk assessment of chemical risks. The application of physiologically based toxicokinetic (PBTK) models to predict concentrations in vivo can determine the effects of harmful substances and tissue accumulation on the premise of saving experimental costs. In this study, Tri(2-chloroethyl) phosphate (TCEP), an organophosphate ester (OPE), was used as an example to study the PBTK model of mice exposed to different exposure doses by multiple routes. Different routes of exposure (gavage and intradermal injection) can cause differences in the concentration of chemicals in the organs. TCEP that enters the body through the mouth is mainly concentrated in the gastrointestinal tract and liver. However, the concentrations of chemicals that enter the skin into the mice are higher in skin, rest of body, and blood. In addition, TCEP was absorbed and accumulated very rapidly in mice, within half an hour after a single exposure. We have successfully established a mouse PBTK model of the TCEP accounting for multiple exposure Routes and obtained a series of kinetic parameters. The model includes blood, liver, kidney, stomach, intestine, skin, and rest of body compartments. Oral and dermal exposure route was considered for PBTK model. The PBTK model established in this study has a good predictive ability. More than 70% of the predicted values deviated from the measured values by less than 5-fold. In addition, we extrapolated the model to humans. A human PBTK model is built. We performed a health risk assessment for world populations based on human PBTK model. The risk of TCEP in dust is greater through mouth than through skin. The risk of TCEP in food of Chinese population is greater than dust.

A minimal PBPK model to accelerate preclinical development of drugs against tuberculosis

Introduction: Understanding drug exposure at disease target sites is pivotal to profiling new drug candidates in terms of tolerability and efficacy. Such quantification is particularly tedious for anti-tuberculosis (TB) compounds as the heterogeneous pulmonary microenvironment due to the infection may alter lung permeability and affect drug disposition. Murine models have been a longstanding support in TB research so far and are here used as human surrogates to unveil the distribution of several anti-TB compounds at the site-of-action via a novel and centralized PBPK design framework. Methods: As an intermediate approach between data-driven pharmacokinetic (PK) models and whole-body physiologically based (PB) PK models, we propose a parsimonious framework for PK investigation (minimal PBPK approach) that retains key physiological processes involved in TB disease, while reducing computational costs and prior knowledge requirements. By lumping together pulmonary TB-unessential organs, our minimal PBPK model counts 9 equations compared to the 36 of published full models, accelerating the simulation more than 3-folds in Matlab 2022b. Results: The model has been successfully tested and validated against 11 anti-TB compounds-rifampicin, rifapentine, pyrazinamide, ethambutol, isoniazid, moxifloxacin, delamanid, pretomanid, bedaquiline, OPC-167832, GSK2556286 - showing robust predictability power in recapitulating PK dynamics in mice. Structural inspections on the proposed design have ensured global identifiability and listed free fraction in plasma and blood-to-plasma ratio as top sensitive parameters for PK metrics. The platform-oriented implementation allows fast comparison of the compounds in terms of exposure and target attainment. Discrepancies in plasma and lung levels for the latest BPaMZ and HPMZ regimens have been analyzed in terms of their impact on preclinical experiment design and on PK/PD indices. Conclusion: The framework we developed requires limited drug- and species-specific information to reconstruct accurate PK dynamics, delivering a unified viewpoint on anti-TB drug distribution at the site-of-action and a flexible fit-for-purpose tool to accelerate model-informed drug design pipelines and facilitate translation into the clinic.

Development and application of an interactive generic physiologically based pharmacokinetic (igPBPK) model for adult beef cattle and lactating dairy cows to estimate tissue distribution and edible tissue and milk withdrawal intervals for per- and polyfluoroalkyl substances (PFAS)

Humans can be exposed to per- and polyfluoroalkyl substances (PFAS) through dietary intake from milk and edible tissues from food animals. This study developed a physiologically based pharmacokinetic (PBPK) model to predict tissue and milk residues and estimate withdrawal intervals (WDIs) for multiple PFAS including PFOA, PFOS and PFHxS in beef cattle and lactating dairy cows. Results showed that model predictions were mostly within a two-fold factor of experimental data for plasma, tissues, and milk with an estimated coefficient of determination (R2) of >0.95. The predicted muscle WDIs for beef cattle were <1 day for PFOA, 449 days for PFOS, and 69 days for PFHxS, while the predicted milk WDIs in dairy cows were <1 day for PFOA, 1345 days for PFOS, and zero day for PFHxS following a high environmental exposure scenario (e.g., 49.3, 193, and 161 ng/kg/day for PFOA, PFOS, and PFHxS, respectively, for beef cattle for 2 years). The model was converted to a web-based interactive generic PBPK (igPBPK) platform to provide a user-friendly dashboard for predictions of tissue and milk WDIs for PFAS in cattle. This model serves as a foundation for extrapolation to other PFAS compounds to improve safety assessment of cattle-derived food products.

A State-of-the-Science Review of Interactions of Per- and Polyfluoroalkyl Substances (PFAS) with Renal Transporters in Health and Disease: Implications for Population Variability in PFAS Toxicokinetics

BACKGROUND

Per- and polyfluoroalkyl substances (PFAS) are ubiquitous in the environment and have been shown to cause various adverse health impacts. In animals, sex- and species-specific differences in PFAS elimination half-lives have been linked to the activity of kidney transporters. However, PFAS molecular interactions with kidney transporters are still not fully understood. Moreover, the impact of kidney disease on PFAS elimination remains unclear.

OBJECTIVES

This state-of-the-science review integrated current knowledge to assess how changes in kidney function and transporter expression from health to disease could affect PFAS toxicokinetics and identified priority research gaps that should be addressed to advance knowledge.

METHODS

We searched for studies that measured PFAS uptake by kidney transporters, quantified transporter-level changes associated with kidney disease status, and developed PFAS pharmacokinetic models. We then used two databases to identify untested kidney transporters that have the potential for PFAS transport based on their endogenous substrates. Finally, we used an existing pharmacokinetic model for perfluorooctanoic acid (PFOA) in male rats to explore the influence of transporter expression levels, glomerular filtration rate (GFR), and serum albumin on serum half-lives.

RESULTS

The literature search identified nine human and eight rat kidney transporters that were previously investigated for their ability to transport PFAS, as well as seven human and three rat transporters that were confirmed to transport specific PFAS. We proposed a candidate list of seven untested kidney transporters with the potential for PFAS transport. Model results indicated PFOA toxicokinetics were more influenced by changes in GFR than in transporter expression.

DISCUSSION

Studies on additional transporters, particularly efflux transporters, and on more PFAS, especially current-use PFAS, are needed to better cover the role of transporters across the PFAS class. Remaining research gaps in transporter expression changes in specific kidney disease states could limit the effectiveness of risk assessment and prevent identification of vulnerable populations. https://doi.org/10.1289/EHP11885.

PBPK Model To Predict Marbofloxacin Distribution in Edible Tissues and Intestinal Exposure in Pigs

Marbofloxacin (MAR) is a fluoroquinolone antibiotic used in food-producing animals in European Union, especially in pigs. In this study, MAR concentrations in plasma, comestible tissues, and intestinal segments were determined in pigs injected with MAR. Based on these data and the literature, a flow-limited PBPK model was developed to predict the tissue distribution of MAR and estimate the withdrawal period after label-use in Europe. A submodel describing the different segments of the intestinal lumen was also developed to assess the intestinal exposure of MAR for the commensal bacteria. During model calibration, only four parameters were estimated. Then, Monte Carlo simulations were performed to generate a virtual population of pigs. The simulation results were compared with the observations from an independent data set during the validation step. A global sensitivity analysis was also carried out to identify the most influential parameters. Overall, the PBPK model was able to adequately predict the MAR kinetics in plasma and edible tissues, as well as in small intestines. However, the simulated concentrations in the large intestine were mostly underestimated, highlighting the need for improvements in the field of PBPK modeling to assess the intestinal exposure of antimicrobials in food animals.

The plasma and tissue kinetics of sulfadiazine and its metabolite in Ictalurus punctatus after oral gavage at two temperatures

A plasma and tissue kinetic study of sulfadiazine (SDZ) and its metabolite, N₄ -acetyl sulfadiazine (ACT-SDZ), was characterized in channel catfish (Ictalurus punctatus) following a single oral dose of 50 mg/kg at 18 and 24°C. Samples were collected at predetermined time points and determined by ultra-performance liquid chromatography. The classical one-compartmental method was used to estimate the pharmacokinetic parameters. Results showed that the changing of temperature was markedly influential on the kinetics of SDZ and ACT-SDZ in plasma and tissues. When the temperature was increased from 18 to 24°C, the elimination half-life (K10_HF) of SDZ was decreased in gill, kidney, and muscle + skin, but increased in liver and plasma. The K10_HF of ACT-SDZ also had a decreased trend in gill, liver, and plasma but had comparable values in kidney and muscle + skin. The absorption half-life (K01_HF), time to peak concentration (T_max ), and area under concentration-time curve (AUC_0-∞ ) of SDZ and ACT-SDZ all exhibited declined tendencies in plasma and tissues. The apparent volume of distribution (V_F) of SDZ in plasma was increased from 0.53 to 1.48 L/kg, and the apparent systemic total body clearance (Cl_F) was increased from 0.028 to 0.060 L/h/kg. In a word, K01_HF, T_max , and AUC_0-∞ of SDZ and ACT-SDZ were decreased in plasma and tissues with the increase of temperature, whereas the V_F and Cl_F of SDZ were increased. Meanwhile, we calculated the percentage of time profile of SDZ concentration more than minimum inhibitory concentration to total time (%T > MIC) to guide clinical usage of SDZ. When the dosage interval was 24 h, the values of %T > MIC were all >90% in plasma and most tissues. Therefore, we recommend an oral dose of SDZ at 50 mg/kg once per 24 h at 18-24°C against the fish pathogens with an MIC value of ≤6.4 μg/mL.

Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling

Physiologically based pharmacokinetic (PBPK) models are useful tools in drug development and risk assessment of environmental chemicals. PBPK model development requires the collection of species-specific physiological, and chemical-specific absorption, distribution, metabolism, and excretion (ADME) parameters, which can be a time-consuming and expensive process. This raises a need to create computational models capable of predicting input parameter values for PBPK models, especially for new compounds. In this review, we summarize an emerging paradigm for integrating PBPK modeling with machine learning (ML) or artificial intelligence (AI)-based computational methods. This paradigm includes 3 steps (1) obtain time-concentration PK data and/or ADME parameters from publicly available databases, (2) develop ML/AI-based approaches to predict ADME parameters, and (3) incorporate the ML/AI models into PBPK models to predict PK summary statistics (eg, area under the curve and maximum plasma concentration). We also discuss a neural network architecture "neural ordinary differential equation (Neural-ODE)" that is capable of providing better predictive capabilities than other ML methods when used to directly predict time-series PK profiles. In order to support applications of ML/AI methods for PBPK model development, several challenges should be addressed (1) as more data become available, it is important to expand the training set by including the structural diversity of compounds to improve the prediction accuracy of ML/AI models; (2) due to the black box nature of many ML models, lack of sufficient interpretability is a limitation; (3) Neural-ODE has great potential to be used to generate time-series PK profiles for new compounds with limited ADME information, but its application remains to be explored. Despite existing challenges, ML/AI approaches will continue to facilitate the efficient development of robust PBPK models for a large number of chemicals.

Comparison of the pharmacokinetics of continuous and intermittent infusions of ampicillin-sulbactam in dogs with septic peritonitis

OBJECTIVE

To evaluate the time-course of ampicillin-sulbactam and percentage of time that its concentration is above a given MIC (T% > MIC) in dogs with septic peritonitis when delivered as either a continuous infusion (CI) or intermittent infusion (II).

ANIMALS

11 dogs with septic peritonitis.

PROCEDURES

Dogs were randomized to receive ampicillin-sulbactam as either CI or II. Continuous infusions were delivered as a 50 mg/kg bolus IV followed by a rate of 0.1 mg/kg/min. Intermittent infusions were administered as 50 mg/kg IV q8h. Serum ampicillin-sulbactam concentrations were measured at hours 0, 1, 6, and every 12 hours after until patients were transitioned to an oral antimicrobial equivalent. All other care was at the discretion of the attending clinician. Statistical analysis was used to determine each patient's percentage of time T% > MIC for 4 MIC breakpoints (0.25, 1.25, 8, and 16 µg/mL).

RESULTS

No dogs experienced adverse events related to ampicillin-sulbactam administration. Both CI and II maintained a T% > MIC of 100% of MIC 0.25 µg/mL and MIC 1.25 µg/mL. The CI group maintained a higher T% > MIC for MIC 8 µg/mL and MIC 16 µg/mL; however, these differences did not reach statistical significance (P = .15 and P = .12, respectively).

CLINICAL RELEVANCE

This study could not demonstrate that ampicillin-sulbactam CI maintains a greater T% > MIC in dogs with septic peritonitis than II; however, marginal differences were noted at higher antimicrobial breakpoints. While these data support the use of antimicrobial CI in septic and critically ill patients, additional prospective trials are needed to fully define the optimal doses and the associated clinical responses.

Ionophore coccidiostats - disposition kinetics in laying hens and residues transfer to eggs

Poultry production is linked with the use of veterinary medicinal products to manage diseases. Ionophore coccidiostats have been permitted for use as feed additives within the European Union (EU) for the prevention of coccidiosis in various species of poultry with except of laying hens. The presence of chemical residues in eggs is a matter of major concern for consumers' health. Despite such prohibition of use in laying hens, they were identified as the most common non-target poultry species being frequently exposed to these class of coccidiostats. Many factors can influence the presence of residues in eggs. Carryover of these class of coccidiostat feed additives in the feed of laying hens has been identified as the main reason of their occurrence in commercial poultry eggs. The physicochemical properties of individual compounds, the physiology of the laying hen, and the biology of egg formation are believed to govern the residue transfer rate and its distribution between the egg white and yolk compartments. This paper reviews the causes of occurrence of residues of ionophore coccidiostats in eggs within the EU with special emphasis on their disposition kinetics in laying hens, and residue transfer into eggs. Additional effort was made to highlight future modeling perspectives on the potential application of pharmacokinetic modeling in predicting drug residue transfer and its concentration in eggs.

A compatibility evaluation between the physiologically based pharmacokinetic (PBPK) model and the compartmental PK model using the lumping method with real cases

Pharmacokinetic (PK) modeling is a useful method for investigating drug absorption, distribution, metabolism, and excretion. The most commonly used mathematical models in PK modeling are the compartment model and physiologically based pharmacokinetic (PBPK) model. Although the theoretical characteristics of each model are well known, there have been few comparative studies of the compatibility of the models. Therefore, we evaluated the compatibility of PBPK and compartment models using the lumping method with 20 model compounds. The PBPK model was theoretically reduced to the lumped model using the principle of grouping tissues and organs that show similar kinetic behaviors. The area under the concentration–time curve (AUC) based on the simulated concentration and PK parameters (drug clearance [CL], central volume of distribution [Vc], peripheral volume of distribution [Vp]) in each model were compared, assuming administration to humans. The AUC and PK parameters in the PBPK model were similar to those in the lumped model within the 2-fold range for 17 of 20 model compounds (85%). In addition, the relationship of the calculated Vd/fu (volume of distribution [Vd], drug-unbound fraction [fu]) and the accuracy of AUC between the lumped model and compartment model confirmed their compatibility. Accordingly, the compatibility between PBPK and compartment models was confirmed by the lumping method. This method can be applied depending on the requirement of compatibility between the two models.

An Interactive Generic Physiologically Based Pharmacokinetic (igPBPK) Modeling Platform to Predict Drug Withdrawal Intervals in Cattle and Swine: A Case Study on Flunixin, Florfenicol and Penicillin G

Violative chemical residues in edible tissues from food-producing animals are of global public health concern. Great efforts have been made to develop physiologically based pharmacokinetic (PBPK) models for estimating withdrawal intervals (WDIs) for extralabel prescribed drugs in food animals. Existing models are insufficient to address the food safety concern as these models are either limited to 1 specific drug or difficult to be used by non-modelers. This study aimed to develop a user-friendly generic PBPK platform that can predict tissue residues and estimate WDIs for multiple drugs including flunixin, florfenicol, and penicillin G in cattle and swine. Mechanism-based in silico methods were used to predict tissue/plasma partition coefficients and the models were calibrated and evaluated with pharmacokinetic data from Food Animal Residue Avoidance Databank (FARAD). Results showed that model predictions were, in general, within a 2-fold factor of experimental data for all 3 drugs in both species. Following extralabel administration and respective U.S. FDA-approved tolerances, predicted WDIs for both cattle and swine were close to or slightly longer than FDA-approved label withdrawal times (eg, predicted 8, 28, and 7 days vs labeled 4, 28, and 4 days for flunixin, florfenicol, and penicillin G in cattle, respectively). The final model was converted to a web-based interactive generic PBPK platform. This PBPK platform serves as a user-friendly quantitative tool for real-time predictions of WDIs for flunixin, florfenicol, and penicillin G following FDA-approved label or extralabel use in both cattle and swine, and provides a basis for extrapolating to other drugs and species.

Discovery of new drug indications for COVID-19: A drug repurposing approach

Motivation

The outbreak of coronavirus health issues caused by COVID-19(SARS-CoV-2) creates a global threat to public health. Therefore, there is a need for effective remedial measures using existing and approved therapies with proven safety measures has several advantages. Dexamethasone (Pubchem ID: CID0000005743), baricitinib(Pubchem ID: CID44205240), remdesivir (PubchemID: CID121304016) are three generic drugs that have demonstrated in-vitro high antiviral activity against SARS-CoV-2. The present study aims to widen the search and explore the anti-SARS-CoV-2 properties of these potential drugs while looking for new drug indications with optimised benefits via in-silico research.

Method

Here, we designed a unique drug-similarity model to repurpose existing drugs against SARS-CoV-2, using the anti-Covid properties of dexamethasone, baricitinib, and remdesivir as references. Known chemical-chemical interactions of reference drugs help extract interactive compounds withimprovedanti-SARS-CoV-2 properties. Here, we calculated the likelihood of these drug compounds treating SARS-CoV-2 related symptoms using chemical-protein interactions between the interactive compounds of the reference drugs and SARS-CoV-2 target genes. In particular, we adopted a two-tier clustering approach to generate a drug similarity model for the final selection of potential anti-SARS-CoV-2 drug molecules. Tier-1 clustering was based on t-Distributed Stochastic Neighbor Embedding (t-SNE) and aimed to filter and discard outlier drugs. The tier-2 analysis incorporated two cluster analyses performed in parallel using Ordering Points To Identify the Clustering Structure (OPTICS) and Hierarchical Agglomerative Clustering (HAC). As a result, itidentified clusters of drugs with similar actions. In addition, we carried out a docking study for in-silico validation of top candidate drugs.

Result

Our drug similarity model highlighted ten drugs, including reference drugs that can act as potential therapeutics against SARS-CoV-2. The docking results suggested that doxorubicin showed the least binding energy compared to reference drugs. Their practical utility as anti-SARS-CoV-2 drugs, either individually or in combination, warrants further investigation.

Residue depletion profiles and withdrawal interval estimations of meloxicam in eggs and ovarian follicles following intravenous (Meloxicam solution for injection) and oral (Meloxidyl®) administration in domestic chickens (Gallus domesticus)

Meloxicam is a non-steroidal anti-inflammatory drug (NSAID) commonly prescribed in an extralabel manner for treating chickens in urbanized settings. The objectives of this study were to determine meloxicam depletion profiles in eggs and ovarian follicles and to estimate associated withdrawal intervals (WDI) in laying hens following a single intravenous or repeated oral administration. The observed peak concentration of meloxicam in ovarian follicles were consistently higher than in egg yolk and egg white samples. Terminal half-lives were 31-h, 113-h and 12-h in ovarian follicles, egg yolk and egg white samples, respectively, for repeated oral administrations at 1 mg/kg for 20 doses at 12-h intervals. The terminal half-life following a single intravenous administration at 1 mg/kg was 50-h for ovarian follicles. Meloxicam WDI estimations using ovarian follicle and egg yolk concentration data following 20 doses at 12-h intervals were 36 and 12 days, respectively. Meloxicam WDI estimation using egg yolk concentration data following 8 doses at 24-h intervals was 12 days. These results improve our understanding on the residue depletion of meloxicam from chickens' reproductive tracts and egg products and provide WDIs to help ensure food safety for humans consuming eggs from treated laying hens.

The construction and application of physiologically based toxicokinetic models for acrylamide, glycidamide and their biomarkers in rats and humans

Acrylamide (AA), a class 2A probable carcinogen to humans classified by the International Agency for Research on Cancer, has attracted extensive attention worldwide since it was widely used in industrial and domestic water treatment and detected in thermal processing foods. The metabolic adducts of AA and its primary metabolite glycidamide (GA) have been served as biomonitoring markers of AA intake, but the physiologically based toxicokinetics (PBTK) models to estimate internal dosimetry still remain unclear. An updated PBTK model for AA, GA and their metabolic biomarkers in rats and humans was developed and extended with time-course datasets from both literatures and our experiments. With adjustments to the model parameters, linear regression correlation coefficient (R²) between the fitting values and the validation datasets of rats and humans was greater than 0.76. The current model fits well with the experimental datasets of urinary N-acetyl-S-(2-carbamoylethyl)-l-cysteine (AAMA) and (N-(R,S)-acetyl-S-(carbamoyl-2-hydroxyethyl)-l-cysteine) (GAMA) of rats exposed to AA from 0.1 to 50 mg/kg b.w. and humans exposed to AA from 0.0005 to 0.020 mg/kg b.w., indicating the robustness of the current models. Parameters for adduct of AA with N-terminal valine of hemoglobin (AAVal) were extended to humans and validated. Kinetic parameters for rats were assessed and validated based upon fit to the experimental datasets for liver N3-(2-carbamoyl-2-hydroxyethyl)-adenine (N3-GA-Ade) and N7-(2-carbamoyl-2-hydroxyethyl)-guanine (N7-GA-Gua) adducts. Compared with the previous model, the developed model included the correlation between AA intake and its mercapturic acid adducts, AAMA and GAMA, in a larger dose range with new experimental data, and parameters for AAVal, N3-GA-Ade and N7-GA-Gua were improved and verified. The current multi-component PBTK models provide a superior foundation for the estimation of short-term to medium and long-term intake levels of human exposure to AA.

Comparative Pharmacokinetics of Sulfadiazine and Its Metabolite N4-Acetyl Sulfadiazine in Grass Carp (Ctenopharyngodon idella) at Different Temperatures after Oral Administration

In this study, the plasma pharmacokinetics and tissue disposition of sulfadiazine (SDZ) and its main metabolite, N₄-acetyl sulfadiazine (ACT-SDZ), were compared between 18 and 24 °C following a single oral administration of SDZ at 50 mg/kg in grass carp (Ctenopharyngodon idella). The plasma and tissues were sampled from 0.167 h up to 96 h and analyzed by ultra-performance liquid chromatography with an ultraviolet detector. The pharmacokinetic parameters were estimated using a one-compartmental approach. Results showed that pharmacokinetics of SDZ and ACT-SDZ in plasma and tissues were notably influenced by the increase of temperature. The increased temperature shortened the absorption half-life (K01_HL) of SDZ and ACT-SDZ in gill, kidney, and plasma, but increased in liver and muscle + skin. The elimination half-life (K10_HF) and the area under concentration-time curve (AUC_0–∞) of SDZ and ACT-SDZ all presented a declined trend. The apparent volume of distribution (V_F) of SDZ in plasma was increased from 0.93 to 1.64 L/kg, and the apparent systemic total body clearance (Cl_F) was also increased from 0.01 to 0.05 L/h/kg. Overall, the rise of temperature decreased K10_HF, AUC_0–∞ of SDZ, and ACT-SDZ in plasma and tissues, but increased V_F and Cl_F in the plasma for SDZ.

Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches

Background

Low delivery efficiency of nanoparticles (NPs) to the tumor is a critical barrier in the field of cancer nanomedicine. Strategies on how to improve NP tumor delivery efficiency remain to be determined.

Methods

This study analyzed the roles of NP physicochemical properties, tumor models, and cancer types in NP tumor delivery efficiency using multiple machine learning and artificial intelligence methods, using data from a recently published Nano-Tumor Database that contains 376 datasets generated from a physiologically based pharmacokinetic (PBPK) model.

Results

The deep neural network model adequately predicted the delivery efficiency of different NPs to different tumors and it outperformed all other machine learning methods; including random forest, support vector machine, linear regression, and bagged model methods. The adjusted determination coefficients (R2) in the full training dataset were 0.92, 0.77, 0.77 and 0.76 for the maximum delivery efficiency (DEmax), delivery efficiency at 24 h (DE24), at 168 h (DE168), and at the last sampling time (DETlast). The corresponding R2 values in the test dataset were 0.70, 0.46, 0.33 and 0.63, respectively. Also, this study showed that cancer type was an important determinant for the deep neural network model in predicting the tumor delivery efficiency across all endpoints (19-29%). Among all physicochemical properties, the Zeta potential and core material played a greater role than other properties, such as the type, shape, and targeting strategy.

Conclusion

This study provides a quantitative model to improve the design of cancer nanomedicine with greater tumor delivery efficiency. These results help to improve our understanding of the causes of low NP tumor delivery efficiency. This study demonstrates the feasibility of integrating artificial intelligence with PBPK modeling approaches to study cancer nanomedicine.

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.

Bayesian Refinement of the Permeability-Limited Physiologically Based Pharmacokinetic Model for Perfluorooctanoic Acid in Male Rats

Physiologically based pharmacokinetic (PBPK) modeling is a powerful technique to inform risk assessment of xenobiotic substances such as perfluorooctanoic acid (PFOA). In our previous study, a permeability-limited PBPK model was developed to simulate the toxicokinetics and tissue distribution of PFOA in male rats. However, due to limited information on some key model parameters (e.g., protein binding and active transport rates), the uncertainty of the permeability-limited PBPK model was quite high. To address this issue, a hierarchical Bayesian analysis with Markov chain Monte Carlo (MCMC) was applied to reduce the uncertainty of parameters and improve the performance of the PBPK model. With the optimized posterior parameters, the PBPK model was evaluated by comparing its prediction with experimental data from three different studies. The results show that the uncertainties of the posterior model parameters were reduced substantially. In addition, most of the PBPK model predictions were improved: with the posterior parameters, most of the predicted plasma toxicokinetics (e.g., half-life) and tissue distribution fell well within a factor of 2.0 of the experimental data. Finally, the Bayesian framework could provide insights into the molecular mechanisms driving PFOA toxicokinetics: PFOA-protein binding, membrane permeability, and active transport.

Apply a Physiologically Based Pharmacokinetic Model to Promote the Development of Enrofloxacin Granules: Predict Withdrawal Interval and Toxicity Dose

Enrofloxacin (ENR) granules were developed to prevent and control the infections caused by foodborne zoonotic intestinal pathogens in our previous studies. To promote the further development of ENR granules and standardize their usage in pigs, a physiologically based pharmacokinetic (PBPK) model of the ENR granule in pigs was built to determine the withdrawal time (WT) and evaluate the toxicity to pigs. Meanwhile, the population WT was determined by a Monte Carlo analysis to guarantee pork safety. The fitting results of the model showed that the tissue residual concentrations of ENR, ciprofloxacin, and ENR plus ciprofloxacin were all well predicted by the built PBPK model (R² > 0.82). When comparing with the EMA's WT1.4 software method, the final WT (6 d) of the ENR granules in the population of pigs was well predicted. Moreover, by combining the cytotoxicity concentration (225.9 µg/mL) of ENR against pig hepatocytes, the orally safe dosage range (≤130 mg/kg b.w.) of the ENR granules to pigs was calculated based on the validated PBPK model. The well-predicted WTs and a few uses in animals proved that the PBPK model is a potential tool for promoting the judicious use of antimicrobial agents and evaluating the toxicity of the veterinary antimicrobial products.

Development and Application of an interactive Physiologically Based Pharmacokinetic (iPBPK) Model to Predict Oxytetracycline Tissue Distribution and Withdrawal Intervals in Market-Age Sheep and Goats

Oxytetracycline (OTC) is a widely used antibiotic in food-producing animals. Extralabel use of OTC is common and may lead to violative residues in edible tissues. It is important to have a quantitative tool to predict scientifically-based withdrawal intervals (WDIs) after extralabel use in food animals to ensure human food safety. This study focuses on developing a physiologically based pharmacokinetic (PBPK) model for OTC in sheep and goats. The model included seven compartments: plasma, lung, liver, kidneys, muscle, fat, and rest of the body. The model was calibrated with serum and tissue (liver, muscle, kidney, and fat) concentration data following a single intramuscular (IM, 20 mg/kg) and/or intravenous (IV, 10 mg/kg) administration of a long-acting formulation in sheep and goats. The model was evaluated with independent datasets from Food Animal Residue Avoidance Databank (FARAD). Results showed that the model adequately simulated the calibration datasets with an overall estimated coefficient of determination (R2) of 0.95 and 0.92, respectively, for sheep and goat models and had acceptable accuracy for the validation datasets. Monte Carlo sampling technique was applied to predict the time needed for drug concentrations in edible tissues to fall below tolerances for the 99th percentiles of the population. The model was converted to a web-based interactive PBPK (iPBPK) interface to facilitate model applications. This iPBPK model provides a useful tool to estimate WDIs for OTC after extralabel use in small ruminants to ensure food safety and serves as a basis for extrapolation to other tetracycline drugs and other food animals.

Application of physiologically based pharmacokinetic models to promote the development of veterinary drugs with high efficacy and safety

Physiologically based pharmacokinetic (PBPK) models have become important tools for the development of novel human drugs. Food-producing animals and pets comprise an important part of human life, and the development of veterinary drugs (VDs) has greatly impacted human health. Owing to increased affordability of and demand for drug development, VD manufacturing companies should have more PBPK models required to reduce drug production costs. So far, little attention has been paid on applying PBPK models for the development of VDs. This review begins with the development processes of VDs; then summarizes case studies of PBPK models in human or VD development; and analyzes the application, potential, and advantages of PBPK in VD development, including candidate screening, formulation optimization, food effects, target-species safety, and dosing optimization. Then, the challenges of applying the PBPK model to VD development are discussed. Finally, future opportunities of PBPK models in designing dosing regimens for intracellular pathogenic infections and for efficient oral absorption of VDs are further forecasted. This review will be relevant to readers who are interested in using a PBPK model to develop new VDs.

A history of antimicrobial drugs in animals: Evolution and revolution

The evolutionary process of antimicrobial drug (AMD) uses in animals over a mere eight decades (1940-2020) has led to a revolutionary outcome, and both evolution and revolution are ongoing, with reports on a range of uses, misuses and abuses escalating logarithmically. As well as veterinary therapeutic perspectives (efficacy, safety, host toxicity, residues, selection of drug, determination of dose and measurement of outcome in treating animal diseases), there are also broader, nontherapeutic uses, some of which have been abandoned, whilst others hopefully will soon be discontinued, at least in more developed countries. Although AMD uses for treatment of animal diseases will continue, it must: (a) be sustainable within the One Health paradigm; and (b) devolve into more prudent, rationally based therapeutic uses. As this review on AMDs is published in a Journal of Pharmacology and Therapeutics, its scope has been made broader than most recent reviews in this field. Many reviews have focused on negative aspects of AMD actions and uses, especially on the question of antimicrobial resistance. This review recognizes these concerns but also emphasizes the many positive aspects deriving from the use of AMDs, including the major research-based advances underlying both the prudent and rational use of AMDs. It is structured in seven sections: (1) Introduction; (2) Sulfonamide history; (3) Nontherapeutic and empirical uses of AMDs (roles of agronomists and veterinarians); (4) Rational uses of AMDs (roles of pharmacologists, clinicians, industry and regulatory controls); (5) Prudent use (residue monitoring, antimicrobial resistance); (6) International and inter-disciplinary actions; and (7) Conclusions.

Development and Application of a Water Temperature Related Physiologically Based Pharmacokinetic Model for Enrofloxacin and Its Metabolite Ciprofloxacin in Rainbow Trout

Enrofloxacin (ENR) has been approved for the treatment of infections in aquaculture, but it may cause tissue residue. This research aimed to develop and validate a water temperature related PBPK model, including both ENR and ciprofloxacin (CIP), in rainbow trout, and to predict further their residue concentrations and the withdrawal periods for ENR at different water temperatures. With the published concentrations data, a flow-limited PBPK model including both ENR and CIP sub-models was developed to predict ENR and CIP concentrations in tissues and plasma/serum after intravenous, oral, or immersion administration. A Monte Carlo simulation including 500 iterations was further incorporated into this model. Based on the model and Monte Carlo analysis, the withdrawal intervals were estimated for different dosage regimens and at different water temperatures, ranging from 80 to 272 degree-days. All of these values were shorter than the labeled withdrawal period (500 degree-days) in fish. This model provided a useful tool for predicting the tissue residues of ENR and CIP in rainbow trout under different dosage regimens and at different water temperatures.

Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part III: Sheep and goat

This report is the third in a series of studies that aimed to compile physiological parameters related to develop physiologically based pharmacokinetic (PBPK) models for drugs and environmental chemicals in food‐producing animals including swine and cattle (Part I), chickens and turkeys (Part II), and finally sheep and goats (the focus of this manuscript). Literature searches were conducted in multiple databases (PubMed, Google Scholar, ScienceDirect, and ProQuest), with data on relevant parameters including body weight, relative organ weight (% of body weight), cardiac output, relative organ blood flow (% of cardiac output), residual blood volume (% of organ weight), and hematocrit reviewed and statistically summarized. The mean and standard deviation of each parameter are presented in tables. Equations describing the growth curves of sheep and goats are presented in figures. When data are sufficient, parameter values are reported for different ages or production classes of sheep, including fetal sheep, lambs, and market‐age sheep (mature sheep). These data provide a reference database for developing standardized PBPK models to predict drug withdrawal intervals in sheep and goats, and also provide a basis for extrapolating PBPK models from major species such as cattle to minor species such as sheep and goats.

Risk Assessment of Veterinary Drug Residues in Meat Products

With the improvement of the global food safety regulatory system, there is an increasing importance for food safety risk assessment. Veterinary drugs are widely used in poultry and livestock products. The abuse of veterinary drugs seriously threatens human health. This article explains the necessity of risk assessment for veterinary drug residues in meat products, describes the principles and functions of risk assessment, then summarizes the risk assessment process of veterinary drug residues, and then outlines the qualitative and quantitative risk assessment methods used in this field. We propose the establishment of a new meat product safety supervision model with a view to improve the current meat product safety supervision system.

Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part II: Chicken and turkey

Physiologically based pharmacokinetic (PBPK) models are growing in popularity due to human food safety concerns and for estimating drug residue distribution and estimating withdrawal intervals for veterinary products originating from livestock species. This paper focuses on the physiological and anatomical data, including cardiac output, organ weight, and blood flow values, needed for PBPK modeling applications for avian species commonly consumed in the poultry market. Experimental and field studies from 1940 to 2019 for broiler chickens (1-70 days old, 40 g - 3.2 kg), laying hens (4-15 months old, 1.1-2.0 kg), and turkeys (1 day-14 months old, 60 g -12.7 kg) were searched systematically using PubMed, Google Scholar, ProQuest, and ScienceDirect for data collection in 2019 and 2020. Relevant data were extracted from the literature with mean and standard deviation (SD) being calculated and compiled in tables of relative organ weights (% of body weight) and relative blood flows (% of cardiac output). Trends of organ or tissue weight growth during different life stages were calculated when sufficient data were available. These compiled data sets facilitate future PBPK model development and applications, especially in estimating chemical residue concentrations in edible tissues to calculate food safety withdrawal intervals for poultry.

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

Combined risk assessment of endocrine effects of bisphenol A (BPA) and its analogues, such as bisphenols S, F, and AF (BPS, BPF, and BPAF), is challenging due to lack of related common toxicity metrics. This study conducted a population-based in vitro-to-in vivo extrapolation using physiologically based pharmacokinetic (PBPK) models coupled with Monte Carlo simulations to convert ToxCast in vitro estrogen receptor (ER) assays to human equivalent doses (HEDs). The ER pathway-based HEDs were compared with HEDs from animal studies and used to assess the combined risks for different populations across different countries/regions in a probabilistic manner. The estimated ER pathway-based HEDs for the four bisphenols (BPs) matched the animal-derived HEDs. The HEDs for the ER gene transcription (the common biological process target among BPs) were 0.40 (2.5th-97.5th percentiles: 0.06-5.42), 4.43 (0.69-53.84), 3.30 (0.51-626.57), and 1.12 (0.16-9.73) mg/kg/day for BPA, BPS, BPF, and BPAF, respectively. Results suggest a potentially moderate concern for combined risks of activating the ER pathway for toddlers and adults with high dietary exposures. This study presents in vitro-based credible HEDs for the four BPs and represents an advancement in the application of in vitro-in silico-based alternative approaches in human health risk assessment.

A study to assess the correlation between plasma, oral fluid and urine concentrations of flunixin meglumine with the tissue residue depletion profile in finishing-age swine

Background

Flunixin meglumine (FM) was investigated for the effectiveness of plasma, oral fluid, and urine concentrations to predict tissue residue depletion profiles in finishing-age swine, along with the potential for untreated pigs to acquire tissue residues following commingled housing with FM-treated pigs. Twenty pigs were housed in groups of three treated and one untreated control. Treated pigs received one 2.2 mg/kg dose of FM intramuscularly. Before treatment and at 1, 3, 6, 12, 24, 36, and 48 h (h) after treatment, plasma samples were taken. At 1, 4, 8, 12 and 16 days (d) post-treatment, necropsy and collection of plasma, urine, oral fluid, muscle, liver, kidney, and injection site samples took place. Analysis of flunixin concentrations using liquid chromatography/tandem mass spectrometry was done. A published physiologically based pharmacokinetic (PBPK) model for flunixin in cattle was extrapolated to swine to simulate the measured data.

Results

Plasma concentrations of flunixin were the highest at 1 h post-treatment, ranging from 1534 to 7040 ng/mL, and were less than limit of quantification (LOQ) of 5 ng/mL in all samples on Day 4. Flunixin was detected in the liver and kidney only on Day 1, but was not found 4–16 d post-treatment. Flunixin was either not seen or found less than LOQ in the muscle, with the exception of one sample on Day 16 at a level close to LOQ. Flunixin was found in the urine of untreated pigs after commingled housing with FM-treated pigs. The PBPK model adequately correlated plasma, oral fluid and urine concentrations of flunixin with residue depletion profiles in liver, kidney, and muscle of finishing-age pigs, especially within 24 h after dosing.

Conclusions

Results indicate untreated pigs can be exposed to flunixin by shared housing with FM-treated pigs due to environmental contamination. Plasma and urine samples may serve as less invasive and more easily accessible biological matrices to predict tissue residue statuses of flunixin in pigs at earlier time points (≤24 h) by using a PBPK model.

Pharmacokinetic Parameters and Estimated Milk Withdrawal Intervals for Domestic Goats (Capra Aegagrus Hircus) After Administration of Single and Multiple Intravenous and Subcutaneous Doses of Flunixin Meglumine

Introduction: The study objectives were to estimate plasma flunixin (FLU) pharmacokinetic parameters and milk depletion profiles for FLU and its metabolite (5-hydroxy flunixin; 5-OH) after subcutaneous (SC) and intravenous (IV) administration of single and multiple flunixin meglumine (FM) doses to non-lactating (nulliparous and pregnant does) and lactating dairy goats. Analytical methods (ELISA and UPLC-MS/MS) for quantifying plasma FLU concentrations were compared. The final objective was to use regulatory (FDA and EMA) methods to estimate milk withdrawal intervals following extra-label drug use in goats.

Methods: FM was administered IV and SC to commercial dairy goats at 1.1 mg/kg for single and multiple doses. Plasma and milk samples were analyzed for FLU and 5-OH via UPLC-MS/MS. Plasma samples were also analyzed for FLU concentrations via ELISA. Using statistical approaches recommended by regulatory agencies, milk withdrawal intervals were estimated following FM extra-label use.

Results: Following IV administration of a single FM dose, clearances were 127, 199, and 365 ml/kg/h for non-lactating (NL) pregnant does, NL nulliparous does, and lactating dairy does, respectively. Following multiple SC doses, clearance/F was 199 ml/kg/h for lactating does. After IV administration of a single FM dose, terminal elimination half-lives were 4.08, 2.87, and 3.77 h for NL pregnant does, NL nulliparous does, and lactating dairy does, respectively. After multiple SC doses, the terminal elimination half-life was 3.03 h for lactating dairy does. No significant differences were noted for samples analyzed by UPLC-MS/MS or ELISA. Milk withdrawal intervals ranged from 36 to 60 h depending on the regulatory statistical method and dosage regimen.

Conclusions: Subcutaneous administration of FM to goats results in similar plasma pharmacokinetic parameters as IV administration. ELISA analysis is an alternative method to UPLC-MS/MS for quantifying FLU concentrations in caprine plasma samples. Following FM extra-label administration to dairy goats, clinicians could consider 36–60 h milk withdrawal intervals.

Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part I: Cattle and swine

Physiologically based pharmacokinetic (PBPK) models for chemicals in food animals are a useful tool in estimating chemical tissue residues and withdrawal intervals. Physiological parameters such as organ weights and blood flows are an important component of a PBPK model. The objective of this study was to compile PBPK‐related physiological parameter data in food animals, including cattle and swine. Comprehensive literature searches were performed in PubMed, Google Scholar, ScienceDirect, and ProQuest. Relevant literature was reviewed and tables of relevant parameters such as relative organ weights (% of body weight) and relative blood flows (% of cardiac output) were compiled for different production classes of cattle and swine. The mean and standard deviation of each parameter were calculated to characterize their variability and uncertainty and to allow investigators to conduct population PBPK analysis via Monte Carlo simulations. Regression equations using weight or age were created for parameters having sufficient data. These compiled data provide a comprehensive physiological parameter database for developing PBPK models of chemicals in cattle and swine to support animal‐derived food safety assessment. This work also provides a basis to compile data in other food animal species, including goats, sheep, chickens, and turkeys.

A physiologically based pharmacokinetic model of doxycycline for predicting tissue residues and withdrawal intervals in grass carp (Ctenopharyngodon idella)

The extensive use of doxycycline in aquaculture results in drug residue violations that negatively impact human food safety. This study aimed to develop a physiologically based pharmacokinetic (PBPK) model for doxycycline to predict drug residues and withdrawal times (WTs) in grass carp (Ctenopharyngodon idella) after daily oral administration for 3 days. Physiological parameters including cardiac output and organ weights were measured experimentally. Chemical-specific parameters were obtained from the literature or estimated by fitting to the observed data. The model properly captured the observed kinetic profiles of doxycycline in tissues (i.e., liver, kidney, muscle + skin and gill). The predicted WT in muscle + skin by Monte Carlo analysis based on sensitive parameters identified at 24 h after drug administration was 41 d, which was similar to 43 d calculated using the tolerance limit method. Sensitivity analysis identified two additional sensitive parameters at 6 weeks: intestinal transit rate constant and urinary elimination rate constant. The predicted WT in muscle + skin based on sensitive parameters identified at 6 weeks was 54 d. This model provides a useful tool to estimate tissue residues and withdrawal times for doxycycline in grass carp and also serves a foundation for extrapolation to other fish species and other tetracyclines.

Tissue residue depletion and estimation of extralabel meat withdrawal intervals for tulathromycin in calves after pneumatic dart administration

The objectives of this study were to evaluate the injection site pathology and determine tissue residue depletion of tulathromycin in calves following pneumatic dart administration and to calculate the associated extralabel withdrawal interval (WDI). Castrated male Holstein calves were injected with ~2.6 mg/kg tulathromycin via pneumatic dart administration. At 1 (n = 2), 6, 12, 18, and 24 d after drug injection (n = 3/time point), calves were euthanized, and muscle, liver, kidney, fat, and injection site samples were harvested and analyzed for tulathromycin concentrations using a LC-MS/MS method. Gross pathology and histopathology evaluations on the injection site samples were also performed. Pneumatic dart administration of tulathromycin caused severe localized lesions of hemorrhage and edema on days 1 and 6, as well as severe pathological reactions in the subcutaneous muscle on days 1, 6, and 12. Slight to moderate reactions were still observed in the majority of the skin or subcutaneous/muscle samples on day 24. Measured tulathromycin concentrations were converted to calculate the concentrations of the marker residue CP-60,300 by dividing a conversion factor of 1.4. The data were used to calculate extralabel WDIs based on the guidelines from U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA). The results showed that tulathromycin concentrations were the highest in the liver (4,877.84 ± 65.33 µg/kg), kidney (5,819.52 ± 1,087.00 µg/kg), muscle (1,717.04 ± 140.35 µg/kg), injection site (51,884.05 ± 7,529.34 µg/kg), and fat (161.69 ± 36.48 µg/kg) at 6, 1, 1, 1, and 1 d, respectively, after treatment. Tulathromycin concentrations remained above the limit of quantification of 5 µg/kg in all tissues at 24 d. The calculated WDIs based on kidney data were 26 d using EMA method, 36 d using FDA method based on CP-60,300 data, and 45 d using FDA method based on tulathromycin data. These results suggest that pneumatic dart administration of tulathromycin causes injection site reactions in calves and an extended WDI is needed. One limitation of this study was the small sample size of 3 that did not meet FDA guideline requirement. Therefore, the calculated WDIs should be considered as preliminary and additional studies that use a larger number of animals and directly measure the concentrations of the marker residue CP-60,300 are needed to make a more conclusive recommendation on the extralabel WDI.

Strategic Priorities for Research on Antibiotic Alternatives in Animal Agriculture-Results From an Expert Workshop

The emergence, spread, and expansion of antibiotic resistance and increasing restrictions on the use of antibiotics in animal agriculture have created a need for efficacious alternatives that remains unmet. Prioritizing research needs in the development of alternatives is key to ensuring that scarce research resources are dedicated to the most promising approaches. However, frameworks to enable a consistent, systematic, and transparent evaluation of antibiotic alternative candidates are lacking. Here, we present such an evaluation framework.

Physiologically based modelling of the pharmacokinetics of three beta-lactam antibiotics after intra-mammary administration in dairy cows

Understanding the pharmacokinetics of intra-mammary antibiotics is important for the prediction of drug residues in milk and for the design of optimal dosage regimens. Unfortunately, compartmental pharmacokinetic models are not valid for this unique system. A minimal physiologically based pharmacokinetic model is presented incorporating the physiology of milk secretion, drug administration at the quarter level, drug absorption and dispersion, drug retention during the inter-milking interval and episodic drug elimination at milking. The primary objective of the study was the development and exploration of a model for major factors controlling drug concentration in milk, rather than generation of rigorously predictive pharmaco-statistical models for any particular drug. This model was implemented in a two-stage approach, using published concentration data for penicillin, cefuroxime, cephapirin and desacetyl-cephapirin in milk of healthy cows. Model simulations evaluated sensitivity and developed predictions of drug residues. The model successfully predicted both drug concentrations and drug residues in milk. The postmilking residual milk volume did not adequately explain antibiotic pharmacokinetics, requiring additional considerations for drug retention. Local sensitivity analysis indicated that increasing the number of quarters treated, the dosage, or the duration of the inter-milking interval prolonged both the persistence of drug residues and the duration that antibiotic concentration exceeded typical minimum inhibitory concentrations. The model was flexible across different beta-lactam drugs as a general description of intra-mammary pharmacokinetics. This model is suitable for the design and analysis of dosage regimens, and could be applied for the prediction of withholding periods when these antibiotic preparations are used off-label. The final model indicates that explicit consideration of the milking regimen is fundamental to the design and interpretation of pharmacokinetic studies of antibiotics in bovine milk.

Tissue residue depletion kinetics and withdrawal time estimation of doxycycline in grass carp, Ctenopharyngodon idella, following multiple oral administrations

This study aimed to determine the plasma and tissue residue depletion kinetics of doxycycline (DC) in grass carp (Ctenopharyngodon idella) after daily oral administrations at 20 mg/kg for 3 days, and to calculate the corresponding withdrawal times. Following drug administrations, samples of plasma, liver, kidney, gill and muscle + skin were collected at predetermined time points (0.25, 0.5, 1, 3, 5, 7, 14, 21, 28, 35, 42, 49 and 56 days) and analyzed for concentrations of DC using a LC-MS/MS method. The results showed that liver had the highest concentrations and the slowest depletion compared to other tissues, with detectable DC up to 49 days (58.9 ± 12.8 μg/kg). The WT 1.4 software and "reschem" package were used to calculate withdrawal times, and the results were similar. The results suggest a withdrawal time of 41 days for Europe and China and 50 days for Japan is needed for DC in grass carp after 3 daily oral administrations at 20 mg/kg. Overall, this study improves our understanding of the tissue residue depletion kinetics of DC in fish, and the results may help regulatory agencies to determine proper withdrawal periods based on different regulatory standards in different countries to ensure safety of aquatic food products.

Integration of Food Animal Residue Avoidance Databank (FARAD) empirical methods for drug withdrawal interval determination with a mechanistic population-based interactive physiologically based pharmacokinetic (iPBPK) modeling platform: example for flunixin meglumine administration

Violative chemical residues in animal-derived food products affect food safety globally and have impact on the trade of international agricultural products. The Food Animal Residue Avoidance Databank program has been developing scientific tools to provide appropriate withdrawal interval (WDI) estimations after extralabel drug use in food animals for the past three decades. One of the tools is physiologically based pharmacokinetic (PBPK) modeling, which is a mechanistic-based approach that can be used to predict tissue residues and WDIs. However, PBPK models are complicated and difficult to use by non-modelers. Therefore, a user-friendly PBPK modeling framework is needed to move this field forward. Flunixin was one of the top five violative drug residues identified in the United States from 2010 to 2016. The objective of this study was to establish a web-based user-friendly framework for the development of new PBPK models for drugs administered to food animals. Specifically, a new PBPK model for both cattle and swine after administration of flunixin meglumine was developed. Population analysis using Monte Carlo simulations was incorporated into the model to predict WDIs following extralabel administration of flunixin meglumine. The population PBPK model was converted to a web-based interactive PBPK (iPBPK) framework to facilitate its application. This iPBPK framework serves as a proof-of-concept for further improvements in the future and it can be applied to develop new models for other drugs in other food animal species, thereby facilitating the application of PBPK modeling in WDI estimation and food safety assessment.

An integrated experimental and physiologically based pharmacokinetic modeling study of penicillin G in heavy sows

Penicillin G is widely used in food-producing animals at extralabel doses and is one of the most frequently identified violative drug residues in animal-derived food products. In this study, the plasma pharmacokinetics and tissue residue depletion of penicillin G in heavy sows after repeated intramuscular administrations at label (6.5 mg/kg) and 5 × label (32.5 mg/kg) doses were determined. Plasma, urine, and environmental samples were tested as potential antemortem markers for penicillin G residues. The collected new data and other available data from the literature were used to develop a population physiologically based pharmacokinetic (PBPK) model for penicillin G in heavy sows. The results showed that antemortem testing of urine provided potential correlation with tissue residue levels. Based on the United States Department of Agriculture Food Safety and Inspection Service action limit of 25 ng/g, the model estimated a withdrawal interval of 38 days for penicillin G in heavy sows after 3 repeated intramuscular injections at 5 × label dose. This study improves our understanding of penicillin G pharmacokinetics and tissue residue depletion in heavy sows and provides a tool to predict proper withdrawal intervals after extralabel use of penicillin G in heavy sows, thereby helping safety assessment of sow-derived meat products.

Assessing Global Human Exposure to T-2 Toxin via Poultry Meat Consumption Using a Lifetime Physiologically Based Pharmacokinetic Model

Residue depletion of T-2 toxin in chickens after oral gavage at 2.0 mg/kg twice daily for 2 days was determined in this study. A flow-limited physiologically based pharmacokinetic (PBPK) model was developed for lifetime exposure assessment in chickens. The model was calibrated with data from the residue depletion study and then validated with independent data. A local sensitivity analysis was performed, and 16 sensitive parameters were subjected to Monte Carlo analysis. The population PBPK model was applied to estimate daily intake values of T-2 toxin in different countries based on reported consumption factors and the guidance value of 0.25 mg/kg in feed for chickens by the European Food Safety Authority (EFSA). The predicted daily intakes in different countries were all lower than the EFSA's total daily intake, suggesting that the EFSA's guidance value has minimal risk. This model provides a foundation for scaling to other mycotoxins and other food animal species.

Expanding behavior pattern sensitivity analysis with model selection and survival analysis

Background

Sensitivity analysis is an essential step in mathematical modeling because it identifies parameters with a strong influence on model output, due to natural variation or uncertainty in the parameter values. Recently behavior pattern sensitivity analysis has been suggested as a method for sensitivity analyses on models with more than one mode of output behavior. The model output is classified by behavior mode and several behavior pattern measures, defined by the researcher, are calculated for each behavior mode. Significant associations between model inputs and outputs are identified by building linear regression models with the model parameters as independent variables and the behavior pattern measures as the dependent variables. We applied the behavior pattern sensitivity analysis to a mathematical model of tetracycline-resistant enteric bacteria in beef cattle administered chlortetracycline orally. The model included 29 parameters related to bacterial population dynamics, chlortetracycline pharmacokinetics and pharmacodynamics. The prevalence of enteric resistance during and after chlortetracycline administration was the model output. Cox proportional hazard models were used when linear regression assumptions were not met.

Results

We have expanded the behavior pattern sensitivity analysis procedure by incorporating model selection techniques to produce parsimonious linear regression models that efficiently prioritize input parameters. We also demonstrate how to address common violations of linear regression model assumptions. Finally, we explore the semi-parametric Cox proportional hazards model as an alternative to linear regression for situations with censored data. In the example mathematical model, the resistant bacteria exhibited three behaviors during the simulation period: (1) increasing, (2) decreasing, and (3) increasing during antimicrobial therapy and decreasing after therapy ceases. The behavior pattern sensitivity analysis identified bacterial population parameters as high importance in determining the trajectory of the resistant bacteria population.

Conclusions

Interventions aimed at the enteric bacterial population ecology, such as diet changes, may be effective at reducing the prevalence of tetracycline-resistant enteric bacteria in beef cattle. Behavior pattern sensitivity analysis is a useful and flexible tool for conducting a sensitivity analysis on models with varied output behavior, enabling prioritization of input parameters via regression model selection techniques. Cox proportional hazard models are an alternative to linear regression when behavior pattern measures are censored or linear regression assumptions cannot be met.