Prediction Of Clearance Research Articles

Mathematical modelling of a liver hollow fibre bioreactor

A mathematical model has been developed to assist with the development of a hollow fibre bioreactor (HFB) for hepatotoxicity testing of xenobiotics; specifically, to inform the HFB operating set-up, interpret data from HFB outputs and aid in optimizing HFB design to mimic certain hepatic physiological conditions. Additionally, the mathematical model has been used to identify the key HFB and compound parameters that will affect xenobiotic clearance. The analysis of this model has produced novel results that allow the operating set-up to be calculated, and predictions of compound clearance to be generated. The mathematical model predicts the inlet oxygen concentration and volumetric flow rate that gives a physiological oxygen gradient in the HFB to mimic a liver sinusoid. It has also been used to predict the concentration gradients and clearance of a test drug and paradigm hepatotoxin, paracetamol (APAP). The effect of altering the HFB dimensions and fibre properties on APAP clearance under the condition of a physiological oxygen gradient is analysed. These theoretical predictions can be used to design the most appropriate experimental set up and data analysis to quantitatively compare the functionality of cell types that are cultured within the HFB to those in other systems.

Relevance of In Vitro Metabolism Models to PET Radiotracer Development: Prediction of In Vivo Clearance in Rats from Microsomal Stability Data.

The prediction of in vivo clearance from in vitro metabolism models such as liver microsomes is an established procedure in drug discovery. The potentials and limitations of this approach have been extensively evaluated in the pharmaceutical sector; however, this is not the case for the field of positron emission tomography (PET) radiotracer development. The application of PET radiotracers and classical drugs differs greatly with regard to the amount of substance administered. In typical PET imaging sessions, subnanomolar quantities of the radiotracer are injected, resulting in body concentrations that cannot be readily simulated in analytical assays. This raises concerns regarding the predictability of radiotracer clearance from in vitro data. We assessed the accuracy of clearance prediction for three prototypical PET radiotracers developed for imaging the A1 adenosine receptor (A1AR). Using the half-life (t1/2) approach and physiologically based scaling, in vivo clearance in the rat model was predicted from microsomal stability data. Actual clearance could be accurately predicted with an average fold error (AFE) of 0.78 and a root mean square error (RMSE) of 1.6. The observed slight underprediction (1.3-fold) is in accordance with the prediction accuracy reported for classical drugs. This result indicates that the prediction of radiotracer clearance is possible despite concentration differences of more than three orders of magnitude between in vitro and in vivo conditions. Consequently, in vitro metabolism models represent a valuable tool for PET radiotracer development.

Quantitative Proteomics‐based Bottom‐up PBK Modeling: A Case Study of 3 Statins

In the consumer care, cosmetics and chemical industries, there is a growing need for alternatives to animal testing to derive biokinetic data to evaluate both efficacy and safety of chemicals. One promising alternative is bottom‐up physiologically‐based biokinetic (PBK) modeling, which utilizes in vitro‐to‐in vivo extrapolation (IVIVE) for prediction of biokinetic parameters. The main challenges of IVIVE lie in suboptimal biokinetic predictions, particularly when using in vitro transporter data which often requires empirical fitting to human biokinetic data. As part of an Organization for Economic Cooperation and Development (OECD) case study, the primary objective of this work is to develop and validate quantitative proteomics‐based bottom‐up PBK models using a set of chemicals rich with in vitro and human in vivo data. Three HMG‐CoA reductase inhibitors that undergo differential elimination processes were chosen: rosuvastatin (transporter‐dependent), fluvastatin (metabolism‐dependent) and pitavastatin (mixed‐mode). PBK models were built using the Simcyp® Simulator by incorporating: (1) in vitro transporter and metabolism data (Vmax, Jmax, Km and CLint) and (2) animal tissue distribution data from literature to inform tissue‐to‐plasma equilibrium distribution ratio (Kp). Simulations were performed for single intravenous, single oral and multiple oral dosing of these chemicals. The successful prediction was based on a two‐fold criterion when compared against human biokinetic parameters. Our results showed that predicted systemic exposure (AUC0‐∞h), maximum plasma concentration (Cmax), plasma clearance (CL) and time to reach Cmax (Tmax) were within two‐fold of the observed data, with the exception of parameters associated with multiple oral pitavastatin dosing and Tmax of single oral fluvastatin dosing. The use of animal Kp data improved the predicted plasma‐concentration time profiles but did not significantly alter predicted biokinetic parameters (Figure 1). Our study demonstrated that quantitative proteomics‐based mechanistic IVIVE could account for differences in transporter and metabolic enzyme expression levels between in vitro systems and in vivo organs, allowing the prediction of whole organ clearances without any empirical scaling. We conclude that bottom‐up PBK modeling incorporating mechanistic IVIVE could be a viable alternative to animal testing in obtaining predictions of human biokinetics of chemicals.Support or Funding InformationThis work was supported by the Innovations in Food and Chemical Safety Programme [Grant number H18/01/a0/C14] and NUS Department of Pharmacy [Grant number C‐148‐000‐003‐001]. Travel funding for this conference was provided by the Innovations in Food and Chemical Safety Programme and the Skin Research Institute of Singapore.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Characterization of Hepatocytes Uptake Clearance of Organic Anion Transporting Polypeptide (OATPs) Substrates in Human and Cynomolgus Cryopreserved Hepatocytes

Transporter‐mediated clearance plays significant roles in drug bioavailability and elimination, and evaluation of potential transporter‐mediated drug‐drug interactions (DDI) is recommended by regulatory agencies during drug development. Currently, the direct extrapolation from in vitro to in vivo is a common approach for human clearance prediction for the compounds that are metabolized by hepatic cytochrome P450 enzymes; however, challenge remains when using the similar approaches in prediction of transporter‐mediated clearance. Recent publications attempted to establish the in‐vitro‐to‐ in vivo scaling based on hepatocyte uptake studies and in vivo pharmacokinetic (PK) data from the preclinical animals. However, the differences in homology of transporter proteins and the associated substrate specificity in transporters between human and preclinical animals complicate the prediction using the correcting factors obtained from the preclinical animals' in‐vitro‐to‐ in vivo scaling. In this study, we obtained the in vitro hepatic uptake clearance in cynomolgus monkey and human for 14 literature compounds that were known as OATPs substrates and had clinical DDI reported. Hepatic uptake was conducted using the oil‐spin method. For each selected substrate, the uptake assay was conducted in the time course from 0.25 minute to 15 minutes in KHB buffer with 10% serum. The uptake clearance was estimated from the linear uptake phase. For each selected substrate, the uptake clearance was characterized in three lots (including single donor and pooled donors lots) of human and monkey cryopreserved hepatocytes. In addition, we tested different lots of human (7 lots) and monkey (10 lots) cryopreserved hepatocytes using rosuvastatin as a control probe to examine the variability among lots and donors. In summary, rosuvastatin uptake clearance in cynomolgus monkey hepatocytes was about 2.5 folds higher on average compared to that in human hepatocytes. Generally, for other OATPs substrates studied, hepatic uptake clearance in cynomolgus monkey appeared to be higher than that in human. Furthermore, variability of uptake clearance was also observed among lots and donors. The results obtained in the current investigations are useful for human prediction through understanding the source of variations and establishing the correlations of in vitro‐in vivo scaling.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

A Novel Unified Approach to Predict Human Hepatic Clearance for Both Enzyme- and Transporter-Mediated Mechanisms Using Suspended Human Hepatocytes.

The accurate prediction of human pharmacokinetics is critically important in modern drug discovery since it drives both pharmacological and toxicological effects. Although significant progress has been made in predicting drug disposition by hepatic drug-metabolizing enzymes, predicting transporter-mediated clearance is still highly uncertain. Furthermore, different approaches are often used to predict clearance with and without transporter involvement, hence the major clearance pathway for a compound must first be determined to know which approach to use. As a result of these challenges, a novel unified method has been developed using cryopreserved suspended human hepatocytes to predict human hepatic clearance for both enzyme- and transporter-mediated mechanisms. This method hypothesizes that, once in vitro metabolic stability is scaled by partition coefficients between hepatocytes and buffer with 4% bovine serum albumin, in vivo clearance can be better predicted. With this method, good in vitro-in vivo correlation of human hepatic clearance has been obtained for a set of 32 structurally diverse compounds, including such transporters as organic anion-transporting polypeptide substrates. The clearance predictions for most compounds are within 3-fold of observed values. This is the first time that multiple compounds result in good in vitro-in vivo extrapolation using an entirely "bottom-up" approach without any empirical scaling factor when transporter-mediated clearance is involved. Potential exceptions are compounds with significant biliary and/or extra-hepatic clearance. The method offers an alternative approach to more accurately predict human hepatic clearance when multiple complex mechanisms are involved.

Prediction of Hepatic Clearance of Stereoselective Metabolism of Carvedilol in Liver Microsomes and Hepatocytes of Sprague-Dawley and Cytochrome P450 2D-Deficient Dark Agouti Rats

Hepatic clearance (CLh) of carvedilol (CAR), which is eliminated via stereoselective metabolism by the CYP2D subfamily of cytochromes P450 (CYPs), was predicted using liver microsomes and hepatocytes from Sprague-Dawley (SD) rats and CYP2D-deficient Dark Agouti (DA) rats to determine the usefulness of prediction method. Plasma concentrations of CAR following intravenous injection to DA rats were higher than those in SD rats. The volume of distribution at steady state and total clearance (CLtot) of S-CAR were approximately two times greater than those of R-CAR in both strains. CLh predicted from in vitro studies using DA rat liver microsomes was different from that obtained from in vivo studies. In contrast, in vitro CLh prediction using DA rat hepatocytes was nearly identical to the CLh observed in DA rats in vivo, and was lower than that in SD rats. The predicted CLh in vitro using hepatocytes correlated well with the observed CLtot in vivo, which is expected to be nearly the same as CLh. These results suggest that in vitro metabolic studies using hepatocytes are more relevant with regard to stereoselectively predicting CLh of CAR than those using liver microsomes.

Use of Segregated Hepatocyte Scaling Factors and Cross-Species Relationships to Resolve Clearance Dependence in the Prediction of Human Hepatic Clearance.

Human and rat hepatocytes have a strong tendency to underpredict hepatic intrinsic clearance (CLint) and the extent of underprediction increases with increasing observed CLint In this study, application of the log average rat hepatocyte-rat in vivo empirical scaling factor (ESF) of 4.2 to human hepatocyte prediction successfully removed bias but did not improve precision. An analogous method using individual drug rat ESFs only achieved marginal improvement in accuracy but not precision. A novel approach to resolve clearance-dependent prediction, involving rat ESFs calculated for particular (order of magnitude) ranges of observed CLint (log average range, 0.12-2.1) improved human prediction precision but only modestly reduced bias. However, rat in vivo CLint was several-fold greater than human in vivo CLint and this was reflected in greater rat hepatocyte and microsome CLint, suggesting that rat metabolic enzymes are more efficient than their human counterparts, by several-fold. By applying the segregated rat ESFs followed by the human/rat CLint ratio, which was consistent regardless of CLint (log average 3.5), both accuracy and precision were improved, providing both a means of mitigating clearance dependence and reaffirming the potential role of rat hepatocytes for prediction of human metabolic CLint These cross-species observations indicate that underprediction from human in vitro systems may be predominantly consequential of an intrinsic property of the in vitro system rather than individual drug properties.

Prediction of Clearance and Dose of Midazolam in Preterm and Term Neonates: A Comparative Study Between Allometric Scaling and Physiologically Based Pharmacokinetic Modeling

Children are not small adults because besides size there are subtle physiological and biochemical differences between children and adults. Like adults, children also require medicine for the management or cure for the underlying diseases. To select a right dose in children, pharmacokinetic (PK) information is warranted. However, in many instances, a PK study in neonates and infants may not be possible. Therefore, various methods are used to predict PK parameters in this group of population, and these predicted parameters may help to calculate a safe dose for the very young children. Allometry is widely used for the prediction of PK parameters in children and subsequently one can predict dose from these predicted PK parameters. Physiologically based pharmacokinetic modeling (PBPK) has also become a useful tool to achieve these goals. Therefore, the objective of this study was to compare the predictive performance of allometry and PBPK for a test compound, midazolam in preterm, and term neonates. In this study, there were 5 preterm neonates (gestational age ranging from 34 to 37 weeks) and 5 term neonates (gestational age ranging from 38 to 41 weeks). PBPK modeling was performed using PK-Sim 6.0 and clearance, as well as midazolam dose in neonates was predicted. Clearance and midazolam dose in neonates was also predicted by allometric scaling. In this study, the allometric exponents for the prediction of midazolam clearance in preterm neonates and term neonates were 1.2 and 1.1, respectively. Similarly, for the prediction of midazolam neonatal dose, the exponent of allometry was either 0.9 or 1.0. The predicted midazolam clearance and dose by both methods were then compared with observed midazolam clearance and dose in neonates. The results of the study showed a slightly better prediction of midazolam clearance in neonates by PBPK than allometric scaling. However, the projected dose of midazolam in neonates was comparable between the 2 methods. Overall, it was noted that both PBPK and allometric model can be used to predict clearance and dose of midazolam in neonates.

Impact of hepatic drug distribution on predictions of clearance

Impact of hepatic drug distribution on predictions of clearance

A Pilot Study of Prediction of Creatinine Clearance by Ellipsoid Volumetry of Kidney Using Noncontrast Computed Tomography.

Introduction: Aging is associated with a decline in kidney volume and function. The purpose of this study is to investigate a direct relationship between kidney volume and function in the elderly population and to challenge whether kidney function could be predictable by using the kidney volume. Methods: We conducted a chart review of 366 patients who underwent abdominal computed tomography (CT) and renal function measurement prior to gastrointestinal surgery. The kidney volume was calculated by the ellipsoid method using a coronal section of noncontrast CT images. Results: The patients were 72.2 ± 13.2 years of age, and 39.0% were female. Their average measured creatinine clearance (mCCr) was 72.0 ± 21.5 mL/min. The average kidney volume was 100.3 ± 27.6 cm3 in the right kidney and 109.3 ± 30.9 cm3 in the left. There was a significant positive correlation between the total kidney volume and mCCr. Multivariate regression analysis showed that age, diabetes mellitus, and total kidney volume were dependent variables with which to predict mCCr. The use of total kidney volume predicted mCCr of ≥50 mL/min with moderate accuracy (area under the curve = 0.782; 95% confidence interval = 0.692–0.871). Conclusions: These results indicate a direct relationship between kidney volume and function in the elderly and might provide a pilot method which estimates the renal function using kidney morphology obtained from pre-existing CT images.

Prediction of human hepatic clearance for cytochrome P450 substrates via a new culture method using the collagen vitrigel membrane chamber and PXB-cells

Prediction of human hepatic clearance for cytochrome P450 substrates via a new culture method using the collagen vitrigel membrane chamber and PXB-cells

Antibiotic Dosing in Chronic Kidney Disease and End-Stage Renal Disease: A Focus on Contemporary Challenges.

Infections are an important cause of morbidity and mortality among patients with chronic kidney disease. Therefore, appropriate antibiotic dosing is imperative to achieve positive patient outcomes while minimizing antibiotic dose-related toxicity. Accurately assessing renal function and determining the influence of renal replacement therapy on antibiotic clearance makes drug dosing in this patient population challenging. Furthermore, as technological advances in hemodialysis and peritoneal dialysis occur, research incorporating newer dialysis parameters to guide drug dosing may not be readily available. Currently, there are limited data to guide drug dosing in the setting of automated peritoneal dialysis, short daily hemodialysis, and nocturnal hemodialysis. Antibiotic-dosing recommendations should be carefully evaluated considering the accuracy of the renal function assessment, the similarity of the operating characteristics of the renal replacement therapy studied compared with those being used, and whether the dosing strategy takes advantage of the pharmacodynamic profile of the antibiotic under consideration. After implementing the antibiotic-dosing regimen, therapeutic drug monitoring should occur when possible along with careful monitoring for antibiotic efficacy and safety.

THE ESTIMATION OF PHARMACOKINETIC PARAMETERS AND ACCURACY OF THE PREDICTED EQUATION FOR LITHIUM DOSE IN CHILDREN: A PILOT STUDY AT THE YUWAPRASART WAITHAYOPATHUM CHILD PSYCHIATRIC HOSPITAL

Objective: The purpose of the study was to estimate the pharmacokinetic parameters and calculate the precision (%RMSE) of the predicted lithium concentration equation.Methods: This research was studied from blood Lithium levels of Children who had visited Yuwaprasart Waithayopathum Child Psychiatric Hospital from 31 December 2009-1 January 2011 The accuracy and precision of the equation were evaluated by the mathematical principle. The assist package software (WIN-NONLIN) was used to create pharmacokinetic parameters.Results: Twenty-nine patients were recruited. The characteristics (mean+SD) presented as the following; age = 15.79+2.64 y, weight = 69.75+22.28 kg and the daily dose = 858.62+274.53 mg. The trough Lithium concentrations (mean+SD) = 0.56+19 mg/l. The kinetic parameter (Mean+SD) presented as the following; t1/2 =7.23+3.38 hr., ke =0.12+0.07 hr-1, Vd = 48.83+15.60 L, AUC0-12 =11.01+5.61 mg x hr/l. The population pharmacokinetic parameters; ke, and AUC (0-∞) = 0.151 hr-1 and 169.81, mg x hr./l respectively. The modified equation from Yukawa for lithium clearance calculation and prediction lithium concentrations were CL (mL/min) = [36.5+(0.242x BW (kg)-7.79]/Scr (mg/dL) and lithium concentration (mg/l) = 4 x Dose (mg)/CL (mL/min)x73.89, respectively with 6.39 %RMSE (test for 20 patients data).Conclusion: In conclusion, the modified Yukawa equation may be used for the prediction of lithium concentration with 6.39% RMSE.

Hepatic Organic Anion Transporting Polypeptide-Mediated Clearance in the Beagle Dog: Assessing In Vitro-In Vivo Relationships and Applying Cross-Species Empirical Scaling Factors to Improve Prediction of Human Clearance.

In the present study, the beagle dog was evaluated as a preclinical model to investigate organic anion transporting polypeptide (OATP)-mediated hepatic clearance. In vitro studies were performed with nine OATP substrates in three lots of plated male dog hepatocytes ± OATP inhibitor cocktail to determine total uptake clearance (CLuptake) and total and unbound cell-to-medium concentration ratio (Kpuu). In vivo intrinsic hepatic clearances (CLint,H) were determined following intravenous drug administration (0.1 mg/kg) in male beagle dogs. The in vitro parameters were compared with those previously reported in plated human, monkey, and rat hepatocytes; the ability of cross-species scaling factors to improve prediction of human in vivo clearance was assessed. CLuptake in dog hepatocytes ranged from 9.4 to 135 µl/min/106 cells for fexofenadine and telmisartan, respectively. Active process contributed >75% to CLuptake for 5/9 drugs. Rosuvastatin and valsartan showed Kpuu > 10, whereas cerivastatin, pitavastatin, repaglinide, and telmisartan had Kpuu < 5. The extent of hepatocellular binding in dog was consistent with other preclinical species and humans. The bias (2.73-fold) obtained from comparison of predicted versus in vivo dog CLint,H was applied as an average empirical scaling factor (ESFav) for in vitro-in vivo extrapolation of human CLint,H The ESFav based on dog reduced underprediction of human CLint,H for the same data set (geometric mean fold error = 2.1), highlighting its utility as a preclinical model to investigate OATP-mediated uptake. The ESFav from all preclinical species resulted in comparable improvement of human clearance prediction, in contrast to drug-specific empirical scalars, rationalized by species differences in expression and/or relative contribution of particular transporters to drug hepatic uptake.

PBPK and its Virtual Populations: the Impact of Physiology on Pediatric Pharmacokinetic Predictions of Tramadol.

In pediatric PBPK models, age-related changes in the body are known to occur. Given the sparsity of and the variability associated with relevant physiological parameters, different PBPK software providers may vary in their system's data. In this work, three commercially available PBPK software packages (PK-Sim®, Simcyp®, and Gastroplus®) were investigated regarding their differences in system-related information, possibly affecting clearance prediction. Three retrograde PBPK clearance models were set up to enable prediction of pediatric tramadol clearance. These models were qualified in terms of total, CYP2D6, and renal clearance in adults. Tramadol pediatric clearance predictions from PBPK were compared with a pooled popPK model covering clearance ranging from neonates to adults. Fold prediction errors were used to evaluate the results. Marked differences in liver clearance prediction between PBPK models were observed. In general, the prediction bias of total clearance was greatest at the youngest population and decreased with age. Regarding CYP2D6 and renal clearance, important differences exist between PBPK software tools. Interestingly, the PBPK model with the shortest CYP2D6 maturation half-life (PK-Sim) agreed best with the in vivo CYP2D6 maturation model. Marked differences in physiological data explain the observed differences in hepatic clearance prediction in early life between the various PBPK software providers tested. Consensus on the most suited pediatric data to use should harmonize and optimize pediatric clearance predictions. Moreover, the combination of bottom-up and top-down approaches, using a convenient probe substrate, has the potential to update system-related parameters in order to better represent pediatric physiology.

A Strategy to Refine the Phenotyping Approach and Its Implementation to Predict Drug Clearance: A Physiologically Based Pharmacokinetic Simulation Study.

The phenotyping approach to predict drug metabolism activity is often hampered by a lack of correlation between the probe and the drug of interest. In this article, we present a strategy to refine the phenotyping approach based on a physiologically based pharmacokinetic simulation (implemented in Simcyp Simulator version 17) using previously published models. The apparent clearance (CL/F) of erlotinib was better predicted by the sum of caffeine and i.v. midazolam CL/F (r 2 = 0.60) compared to that of either probe drug alone. The clearance of atorvastatin and repaglinide had a strong correlation (r 2 = 0.70 and 0.63, respectively) with that of pitavastatin (a SLCO1B1 probe). Use of multiple probes for drugs that are predominantly metabolized by more than one cytochrome P450 (CYP) enzyme should be considered. In a case in which hepatic uptake transporters play a significant role in the disposition of a drug, the pharmacokinetic of a transporter probe will provide better predictions of the drug clearance.

Age- and Bodyweight-dependent Allometric Exponent Model for Scaling Clearance and Maintenance Dose of Theophylline From Neonates to Adults.

In population pharmacokinetic modeling, bodyweight is often incorporated as an important covariate using fixed (0.75) or single-exponent model. In recent years, several variations of allometric models have been suggested for the prediction of drug clearance across a wide age range. The objective of this study is to develop and evaluate single-exponent, bodyweight-dependent allometric exponent (BDE), age-dependent exponent (ADE), and segmented regression models for predicting clearance and maintenance dose of theophylline. The BDE model was described by the following equation: (Equation is included in full-text article.), where L × BW defines the BDE for clearance. The coefficient and the exponents L and M were estimated. The ADE model consisted of several empirical exponents based on age and ranged from 0.75 (children >5 years and adults) to 1.2 (premature neonates). Data for model development and validation were based on 52 subjects each. All structural and statistical parameters were estimated with acceptable precision for single-exponent and BDE models (<30%); however, the BDE model was superior in describing theophylline clearance across a wide age range for the training data. The segmented regression model on log-transformed data also adequately described theophylline clearance. When models were evaluated with validation data, a single-exponent model overpredicted clearance and dosing rate in premature neonates and adults with a mean prediction error of ≥50%. For premature neonates and adults, mean clearance and dosing rate were predicted within a 30% prediction error using the BDE, ADE, and segmented models. This study demonstrates that the BDE, ADE, and segmented models performed better than a single-exponent model for predicting clearance and dose of theophylline across a wide age range.

Toward a Combinatorial Approach for the Prediction of IgG Half-Life and Clearance.

The serum half-life and clearance of therapeutic monoclonal antibodies (mAbs) are critical factors that impact their efficacy and optimal dosing regimen. The pH-dependent binding of an mAb to the neonatal Fc receptor (FcRn) has long been recognized as an important determinant of its pharmacokinetics. However, FcRn affinity alone is not a reliable predictor of mAb half-life, suggesting that other biologic or biophysical mechanisms must be accounted for. mAb thermal stability, which reflects its unfolding and aggregation propensities, may also relate to its pharmacokinetic properties. However, no rigorous statistical regression methods have been used to identify combinations of physical parameters that best predict biologic properties. In this work, a panel of eight mAbs with published human pharmacokinetic data were selected for biophysical analyses of FcRn binding and thermal stability. Biolayer interferometry was used to characterize FcRn/mAb binding at acidic and neutral pH, while differential scanning calorimetry was used to determine thermodynamic unfolding parameters. Individual binding or stability parameters were generally weakly correlated with half-life and clearance values. Least absolute shrinkage and selection operator regression was used to identify the combination of two parameters with the best correlation to half-life and clearance as being the FcRn binding response at pH 7.0 and the change in heat capacity. Leave-one-out subsampling yielded a root mean square difference between observed and predicted half-life of just 2.7 days (16%). Thus, the incorporation of multiple biophysical parameters into a cohesive model may facilitate early-stage prediction of in vivo half-life and clearance based on simple in vitro experiments.

A Comparative Study Between Allometric Scaling and Physiologically Based Pharmacokinetic Modeling for the Prediction of Drug Clearance From Neonates to Adolescents.

The objective of this study was to compare the predictive performance of an allometric model with that of a physiologically based pharmacokinetic (PBPK) model to predict clearance or area under the concentration-time curve (AUC) of drugs in subjects from neonates to adolescents. From the literature, 10 studies were identified in which clearance or AUC of drugs from neonates to adolescents was predicted by PBPK models. In these published studies, drugs were given to children either by intravenous or oral route. The allometric model was an age-dependent exponent (ADE) model for the prediction of clearance across the age groups. The predicted clearance or AUC values from the PBPK and ADE models were compared with the experimental values. The acceptable prediction error was the percentage of subjects within an 0.5- to 2-fold or 0.5- to 1.5-fold prediction error. There were 73 drugs with a total of 372 observations. From PBPK and allometric models, 91.1% and 90.6% of observations were within 0.5- to 2-fold prediction error, respectively. For children ≤2 years old (n = 130), PBPK and allometric models had 89% and 87% of observations within the 0.5- to 2-fold prediction error, respectively. This study indicates that the predictive power of PBPK and allometric models was essentially similar for the prediction of clearance or AUC in pediatric subjects ranging from neonates to adolescents.

Xenobiotic Metabolism in Alginate-Encapsulated Primary Human Hepatocytes Over Long Timeframes

Introduction: Application of in vitro-to-in vivo extrapolation to chemical safety assessment has gained significant attention in the past few years. Accurate prediction of hepatic metabolic clearance from in vitro data is critical in this regard as it determines compound pharmacokinetics and exposure at sites of action. To estimate hepatic metabolic clearance, intrinsic clearance (CLint) is typically measured using in vitro systems such as primary hepatocytes or subcellular fractions derived from liver tissues. However, currently available in vitro systems used in these studies often lack long-term metabolic competence, making it challenging to estimate CLint for poorly metabolized and slowly cleared chemicals. Materials and Methods: To address this challenge, we developed a three-dimensional (3D) primary human hepatocyte cell culture system using alginate hydrogels (“alginate bead culture”) with extended viability and metabolic competence. Results: Alginate bead culture generates comparable estimates of metabolism to other in vitro and in vivo systems. In addition, expression of several xenobiotic metabolizing enzymes over long timeframes in beads is comparable to freshly isolated hepatocytes in suspension culture. Discussion: We compare CLint estimated from traditional suspension versus alginate bead culture for two chemicals (S-warfarin and coumarin) and show that alginate bead culture holds promise to increase confidence in estimates of CLint for slowly cleared chemicals. Conclusions: In addition to providing an improved in vitro tool to estimate metabolic clearance for a broad range of chemicals, this simple 3D hepatocyte culture can be adapted to a continuous flow-based bioreactor system allowing repeated exposure experiments over long periods in vitro, tackling an important challenge in in vitro-based chemical safety assessment.