Mixed effect modeling of sumatriptan pharmacokinetics during drug development. I: Interspecies allometric scaling

BWC0977, a broad-spectrum antibacterial clinical candidate to treat multidrug resistant infections

The global crisis of antimicrobial resistance (AMR) necessitates the development of broad-spectrum antibacterial drugs effective against multi-drug resistant (MDR) pathogens. BWC0977, a Novel Bacterial Topoisomerase Inhibitor (NBTI) selectively inhibits bacterial DNA replication via inhibition of DNA gyrase and topoisomerase IV. BWC0977 exhibited a minimum inhibitory concentration (MIC90) of 0.03-2 µg/mL against a global panel of MDR Gram-negative bacteria including Enterobacterales and non-fermenters, Gram-positive bacteria, anaerobes and biothreat pathogens. BWC0977 retains activity against isolates resistant to fluoroquinolones (FQs), carbapenems and colistin and demonstrates efficacy against multiple pathogens in two rodent species with significantly higher drug levels in the epithelial lining fluid of infected lungs. In healthy volunteers, single-ascending doses of BWC0977 administered intravenously ( https://clinicaltrials.gov/study/NCT05088421 ) was found to be safe, well tolerated (primary endpoint) and achieved dose-proportional exposures (secondary endpoint) consistent with modelled data from preclinical studies. Here, we show that BWC0977 has the potential to treat a range of critical-care infections including MDR bacterial pneumonias.

Model-Based Interspecies Scaling for Predicting Human Pharmacokinetics of CB 4332, a Complement Factor I Protein

Interspecies scaling of the pharmacokinetics (PK) of CB 4332, a 150 kDa recombinant complement factor I protein, was performed using traditional and model-based approaches to inform first-in-human dose selection. Plasma concentration versus time data from four preclinical PK studies of single intravenous and subcutaneous (SC) CB 4332 dosing in mice, rats and nonhuman primates (NHPs) were modeled simultaneously using naive pooling including allometric scaling. The human-equivalent dose was calculated using the preclinical no observed adverse effect level (NOAEL) as part of the dose-by-factor approach. Pharmacokinetic modeling of CB 4332 revealed species-specific differences in the elimination, which was accounted for by including an additional rat-specific clearance. Signs of anti-drug antibodies (ADA) formation in all rats and some NHPs were observed. Consequently, an additional ADA-induced clearance parameter was estimated including the time of onset. The traditional dose-by-factor approach calculated a maximum recommended starting SC dose of 0.9 mg/kg once weekly, which was predicted it to result in a trough steady-state concentration lower than the determined efficacy target range for CB 4332 in humans. Model simulations predicted the efficacy target range to be reached using 5 mg/kg once weekly SC dosing.

A translational model-based approach to inform the choice of the dose in phase 1 oncology trials: the case study of erdafitinib

PURPOSE

Erdafitinib (JNJ-42756493, BALVERSA) is a tyrosine kinase inhibitor indicated for the treatment of advanced urothelial carcinoma. In this work, a translational model-based approach to inform the choice of the doses in phase 1 trials is illustrated.

METHODS

A pharmacokinetic (PK) model was developed to describe the time course of erdafitinib plasma concentrations in mice and rats. Data from multiple xenograft studies in mice and rats were analyzed using the Simeoni tumor growth inhibition (TGI) model. The model parameters were used to derive a range of erdafitinib exposures that might inform the choice of the doses in oncology phase 1 trials. Conversion of exposures to doses was based on preliminary PK assessments from the first-in human (FIH) study.

RESULTS

A one-compartment PK disposition model, with linear absorption and dose-dependent clearance, adequately described the PK data in both mice and rats via an allometric scaling approach. The TGI model was able to describe tumor growth dynamics, providing quantitative measurements of erdafitinib antitumor potency in mice and rats. Based on these estimates, ranges of efficacious unbound concentration were identified for erdafitinib in mice (0.642-5.364 μg/L) and rats (0.782-2.565 μg/L). Based on the FIH data, it was possible to transpose exposures into doses and doses of above 4 mg/day provided erdafitinib exposures associated with significant TGI in animals. The findings were in agreement with the results of the FIH trial, in which the first hints of clinical activities were observed at 6 mg.

CONCLUSION

The successful modeling exercise of erdafitinib preclinical data showed how translational PK-PD modeling might be a tool to help to inform the choice of the doses in FIH studies.

Calculation of a First-In-Man Dose of 7-O-Succinyl Macrolactin A Based on Allometric Scaling of Data from Mice, Rats, and Dogs

7-O-Succinyl macrolactin A (SMA) exerts several pharmacological effects including anti-bacterial, anti-inflammation, and anti-cancer activities. Recently, SMA has been extensively evaluated as an anti-cancer drug. Thus, the objectives of the present study were to characterise the pharmacokinetics of SMA via both non-compartmental and compartmental analysis in mice, rats, and dogs, and to derive an appropriate first-in-man dose based on allometric scaling of the animal data. The time courses of plasma SMA concentrations after intravenous administration to rats and dogs were analysed retrospectively, as were data collected after intraperitoneal SMA injection in mice. Pharmacokinetic parameters were estimated via both noncompartmental and compartmental analysis, and were correlated with body weight and/or the potential maximum life-span. The clearance and distribution volume of SMA in humans were predicted, and a first-in-man dose proposed. A two-compartment model best described the time courses of SMA plasma concentrations after a saturation elimination process was applied to fit the dataset obtained from rats. Incorporation of the maximum potential life-span during allometric scaling was required to improve the estimation of human clearance. The SMA clearance and the distribution volume in the steady state, in a 70-kg adult male, were estimated to be 30.6 L/h and 19.5 L, respectively. To meet the area under the curve (AUC) required for anti-tumour activity, a dose of 100 mg (∼1.5 mg/kg) was finally proposed as the first dose for a 70-kg human. Although toxicological profiles derived from non-clinical studies must be considered before any final decision is made, our work will facilitate clinical studies on SMA.

An allometric pharmacokinetic/pharmacodynamics model for BI 893923, a novel IGF-1 receptor inhibitor

PURPOSE

BI 893923 is a novel IGF1R/INSR inhibitor with promising anti-tumor efficacy. Dose-limiting hyperglycemia has been observed for other IGF1R/INSR inhibitors in clinical trials. To counterbalance anti-tumor efficacy with the risk of hyperglycemia and to determine the therapeutic window, we aimed to develop a translational pharmacokinetic/pharmacodynamics model for BI 893923. This aimed to translate pharmacokinetics and pharmacodynamics from animals to humans by an allometrically scaled semi-mechanistic model.

METHODS

Model development was based on a previously published PK/PD model for BI 893923 in mice (Titze et al., Cancer Chemother Pharmacol 77:1303-1314, 13). PK and blood glucose parameters were scaled by allometric principles using body weight as a scaling factor along with an estimation of the parameter exponents. Biomarker and tumor growth parameters were extrapolated from mouse to human using the body weight ratio as scaling factor.

RESULTS

The allometric PK/PD model successfully described BI 893923 pharmacokinetics and blood glucose across mouse, rat, dog, minipig, and monkey. BI 893923 human exposure as well as blood glucose and tumor growth were predicted and compared for different dosing scenarios. A comprehensive risk-benefit analysis was conducted by determining the net clinical benefit for each schedule. An oral dose of 2750 mg BI 893923 divided in three evenly distributed doses was identified as the optimal human dosing regimen, predicting a tumor growth inhibition of 90.4% without associated hyperglycemia.

CONCLUSION

Our model supported human therapeutic dose estimation by rationalizing the optimal efficacious dosing regimen with minimal undesired effects. This modeling approach may be useful for PK/PD scaling of other IGF1R/INSR inhibitors.

Interspecies modeling and prediction of human exenatide pharmacokinetics

PURPOSE

To develop a model-based approach for interspecies scaling of the preclinical pharmacokinetics of exenatide and to predict concentration-time profiles in humans.

METHODS

A target-mediated drug disposition (TMDD) model was simultaneously fit to concentration-time profiles of exenatide over a wide range of intravenous (IV) and subcutaneous (SC) doses obtained from mice, rats, and monkeys. Allometric relationships were incorporated into the model to scale parameters based on species body weight. Human pharmacokinetic profiles following IV and SC administration were simulated using the final model structure and parameter estimates and compared to clinical data.

RESULTS

The final model provided a good simultaneous fit to all animal data and reasonable parameter estimates. Exenatide receptor binding affinity and baseline receptor concentrations were species-dependent. Absorption parameters from rat provided the best prediction of exenatide SC absorption in humans, but good predictions could also be obtained using allometric scaling of preclinical absorption parameters.

CONCLUSIONS

A TMDD model combined with allometric scaling was successfully used to simultaneously describe preclinical data for exenatide from three animal species following both IV and SC administration. The majority of model parameters could be shared among the animal species and further used for projecting exenatide behavior in humans.

Interspecies scaling of receptor-mediated pharmacokinetics and pharmacodynamics of type I interferons

PURPOSE

To develop an integrated mechanism-based modeling approach for the interspecies scaling of pharmacokinetic (PK) and pharmacodynamic (PD) properties of type I interferons (IFNs) that exhibit target-mediated drug disposition (TMDD).

METHODS

PK and PD profiles of human IFN-beta1a, IFN-beta1b, and IFN-alpha2a in humans, monkeys, rats, and mice from nine studies were extracted from the literature by digitization. Concentration-time profiles from different species were fitted simultaneously using various allometric relationships to scale model-specific parameters.

RESULTS

PK/PD profiles of IFN-beta1a in humans and monkeys were successfully characterized by utilizing the same rate constant parameters and scaling the volume of the central compartment to body weight using an allometric exponent of 1. Concentration and effect profiles of other IFNs were also well described by changing only the affinity of the drug to its receptor. PK profiles in rodents were simulated using an allometric exponent of -0.25 for the first-order elimination rate constant, and no receptor-binding was included given the lack of cross-reactivity.

CONCLUSIONS

An integrated TMDD PK/PD model was successfully combined with classic allometric scaling techniques and showed good predictive performance. Several parameters obtained from one IFN can be effectively shared to predict the kinetic behavior of other IFN subtypes.

Scaling pharmacodynamics from in vitro and preclinical animal studies to humans

An important feature of mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) models is the identification of drug- and system-specific factors that determine the intensity and time-course of pharmacological effects. This provides an opportunity to integrate information obtained from in vitro bioassays and preclinical pharmacological studies in animals to anticipate the clinical and adverse responses to drugs in humans. The fact that contemporary PK/PD modeling continues to evolve and seeks to emulate systems level properties should provide enhanced capabilities to scale-up pharmacodynamic data. Critical steps in drug discovery and development, such as lead compound and first in human dose selection, may become more efficient with the implementation and further refinement of translational PK/PD modeling. In this review, we highlight fundamental principles in pharmacodynamics and the basic expectations for in vitro bioassays and traditional allometric scaling in PK/PD modeling. Discussion of PK/PD modeling efforts for recombinant human erythropoietin is also included as a case study showing the potential for advanced systems analysis to facilitate extrapolations and improve understanding of inter-species differences in drug responses.

Development of translational pharmacokinetic-pharmacodynamic models

Contemporary models in the field of pharmacokinetic-pharmacodynamic (PK-PD) modeling often incorporate the fundamental principles of capacity limitation and operation of turnover processes to describe the time course of pharmacological effects in mechanistic terms. This permits the identification of drug- and system-specific factors that govern drug responses. There is considerable interest in utilizing mechanism-based PK-PD models in translational pharmacology, whereby in silico, in vitro, and preclinical data may be effectively coupled with relevant models to streamline the discovery and development of new therapeutic agents. These translational PK-PD models form the subject of this review.

Longitudinal brain magnetic resonance imaging study of the alcohol-preferring rat. Part II: effects of voluntary chronic alcohol consumption

BACKGROUND

Tracking the dynamic course of human alcoholism brain pathology can be accomplished only through naturalistic study and without opportunity for experimental manipulation. Development of an animal model of alcohol-induced brain damage, in which animals consume large amounts of alcohol following cycles of alcohol access and deprivation and are examined regularly with neuroimaging methods, would enable hypothesis testing focused on the degree, nature, and factors resulting in alcohol-induced brain damage and the prospects for recovery or relapse.

METHODS

We report the results of longitudinal magnetic resonance imaging (MRI) studies of the effects of free-choice chronic alcohol intake on the brains of 2 cohorts of selectively bred alcohol-preferring (P) rats. In the companion paper, we described the MRI acquisition and analysis methods, delineation of brain regions, and growth patterns in total brain and selective structures of the control rats in the present study. Both cohorts were studied as adults for about 1 year and consumed high doses of alcohol for most of the study duration. The paradigm involved a 3-bottle choice with 0, 15 (or 20%), and 30% (or 40%) alcohol available in several different exposure schemes: continuous exposure, cycles of 2 weeks on followed by 2 weeks off alcohol, and binge drinking in the dark.

RESULTS

Brain structures of the adult P rats in both the alcohol-exposed and the water control conditions showed significant growth, which was attenuated in a few measures in the alcohol-exposed groups. The region with the greatest demonstrable effect was the corpus callosum, measured on midsagittal images.

CONCLUSION

The P rats showed an age-alcohol interaction different from humans, in that normal growth in selective brain regions that continues in adult rats was retarded.

A global examination of allometric scaling for predicting human drug clearance and the prediction of large vertical allometry**This work was presented at the American Association of Pharmaceutical Scientists Annual meeting, Salt Lake City, USA, Oct. 26, 2003

Allometrically scaled data sets (138 compounds) used for predicting human clearance were obtained from the literature. Our analyses of these data have led to four observations. (1) The current data do not provide strong evidence that systemic clearance (CL(s); n = 102) is more predictable than apparent oral clearance (CL(po); n = 24), but caution needs to be applied because of potential CL(po) prediction error caused by differences in bioavailability across species. (2) CL(s) of proteins (n = 10) can be more accurately predicted than that of non-protein chemicals (n = 102). (3) CL(s) is more predictable for compounds eliminated by renal or biliary excretion (n = 33) than by metabolism (n = 57). (4) CL(s) predictability for hepatically eliminated compounds followed the order: high CL (n = 11) > intermediate CL (n = 17) > low CL (n = 29). All examples of large vertical allometry (% error of prediction greater than 1000%) occurred only when predicting human CL(s) of drugs having very low CL(s). A qualitative analysis revealed the application of two potential rules for predicting the occurrence of large vertical allometry: (1) ratio of unbound fraction of drug in plasma (f(u)) between rats and humans greater than 5; (2) C logP greater than 2. Metabolic elimination could also serve as an additional indicator for expecting large vertical allometry.

A novel model for prediction of human drug clearance by allometric scaling

Sixty-one sets of clearance (CL) values in animal species were allometrically scaled for predicting human clearance. Unbound fractions (f(u)) of drug in plasma in rats and humans were obtained from the literature. A model was developed to predict human CL: CL=33.35 ml/min x (a/Rf(u))(0.770), where Rf(u) is the f(u) ratio between rats and humans and a is the coefficient obtained from allometric scaling. The new model was compared with simple allometric scaling and the "rule of exponents" (ROE). Results indicated that the new model provided better predictability for human values of CL than did ROE. It is especially significant that for the first time the proposed model improves the prediction of CL for drugs illustrating large vertical allometry.

Mixed-effects modelling of the interspecies pharmacokinetic scaling of pegylated human erythropoietin

The aim of this study was to develop a population pharmacokinetic model for interspecies allometric scaling of pegylated r-HuEPO (PEG-EPO) pharmacokinetics to man. A total of 927 serum concentrations from 193 rats, 6 rabbits, 34 monkeys, and 9 dogs obtained after a single dose of PEG-EPO, administered by the i.v. (dose range: 12.5-550 microg/kg) and s.c. (dose range: 12.5-500 microg/kg) routes, were pooled in this analysis. An open two-compartment model with first-order absorption and lag time (Tlag) and linear elimination from the central compartment was fitted to the data using the NONMEM V software. Body weight (WT) was used as a scaling factor and the effect of brain weight (BW), sex, and pregnancy status on the pharmacokinetic parameters was investigated. The final model was evaluated by means of a non-parametric bootstrap analysis and used to predict the PEG-EPO pharmacokinetic parameters in healthy male subjects. The systemic clearance (CL) in males was estimated to be 4.08WT1.030xBW-0.345 ml/h. In females, the CL was 90.7% of the CL in males. The volumes of the central (Vc) and the peripheral (Vp) compartment were characterized as 57.8WT0.959 ml, and 48.1WT1.150 ml, respectively. Intercompartmental flow was estimated at 2.32WT0.930 ml/h. Absorption rate constant (Ka) was estimated at 0.0538WT-0.149. The absolute s.c. bioavailability F was calculated at 52.5, 80.2, and 49.4% in rat, monkey, and dog, respectively. The interindividual variability in the population pharmacokinetic parameters was fairly low (<35%). Non-parametric bootstrap confirmed the accuracy of the NONMEM estimates. The mean model predicted pharmacokinetic parameters in healthy male subjects of 70 kg were estimated at: CL: 26.2 ml/h; Vc: 3.6l; Q: 286 l/h; Vp: 6.9l, and Ka: 0.031 h-1. The population pharmacokinetic model developed was appropriate to describe the time course of PEG-EPO serum concentrations and their variability in different species. The model predicted pharmacokinetics of PEG-EPO in humans suggest a less frequent dosing regimen relative to erythropoietin and darbepoetin, potentially leading to a simplification of anemia management.

Allometric principles for interspecies extrapolation in toxicological risk assessment--empirical investigations

Four types of data (toxicokinetic data of pharmaceuticals from six species including humans, LD(50) values from eight animal species, long-term NOAEL values of pesticides from mice, rats, and dogs, and toxicity data on anti-neoplastic agents from six species including humans) were used for interspecies comparisons. Species differences with regard to kinetic parameters and toxicity were evaluated and the concordance with predictions by allometric scaling according to caloric demand (allometric exponent 0.75) or to body weight (allometric exponent 1) was checked. For LD(50) values, agreement was poor for both allometric concepts. Recently reported concordance of LD(50) species differences with body weight scaling could be traced back to biased data selection. The other three datasets are clearly in agreement with the allometric scaling according to caloric demand. Caloric demand scaling is thus proposed as a generic interspecies extrapolation method in the absence of substance-specific data. Moreover, the evaluated data make it possible to describe uncertainty associated with the process of interspecies extrapolation by allometric rules.

Comparative preclinical toxicology and pharmacology of isophosphoramide mustard, the active metabolite of ifosfamide

BACKGROUND

Isophosphoramide mustard (IPM) is the cytotoxic alkylating metabolite of Ifosfamide (IFOS). IPM is being readied for a phase I clinical trial. In the present preclinical study, IPM was evaluated for usage in multidose intravenous (IV) infusion protocols.

METHODS

Mice and dogs received IV IPM daily for 3 days. Single-day dosing-oral and IV-to mice, rats, and monkeys is also reviewed for comparison. Complete toxicology studies were completed in the mice and dogs. For mice, dogs and monkeys, IV pharmacokinetic studies were conducted and compared.

RESULTS

For mice, the LD(10) for the 3-day IV schedule for IPM was calculated to be 119 mg/kg (with 95% confidence limits of 87-134 mg/kg) (combined sexes), and for adult male dogs the maximum tolerated dose (MTD) was 5 mg/kg. Pharmacokinetic studies in mice, dogs and monkeys were compared and projected to human dosing. For dogs that received 10 mg/kg of IPM, T(1/2beta) was 0.99 h, and clearance was constant (1.01 l/h/kg). IPM was detected from 0 h to 1.5 h after the 5 mg/kg dose and from 0 h to 2 h after the 10 mg/kg dose; none was detected after 2 h. The IV MTD in dogs was 5 mg/kg per day for 3 days. Renal tubular necrosis and bone marrow failure were the causes of death. Transient liver, renal and bone marrow toxicity and gastrointestinal dysfunction were seen at low doses (<5 mg/kg) in dogs. In mice (receiving 100 mg/kg IV) plasma concentrations disappeared in less than 1 h (T(1/2alpha) 2 min), with a clearance of 8.44 l/h/kg. For monkeys, the mean T(1/2) was 4.2 h. Median clearance was 1.65 l/h/kg and no IPM was detected 4 h after dosing. No potential IPM metabolites could be detected in any of the studies. In vitro, plasma protein bound 90% of IPM within 5 min of incubation.

CONCLUSIONS

Predictions for human pharmacokinetic parameters and dosing are made from allometric analysis using the above three species. Data predicted an acceptable starting dose of 30 mg/m(2) with a clearance of 39.5 l/h, and a T(1/2) of 1 h 45 min for a 70-kg patient.

Pharmacokinetics of sumatriptan nasal spray in children

The authors studied the pharmacokinetics of sumatriptan nasal spray after a single dose in children migraineurs outside of migraine attack. Seventeen subjects (9 females) ages 6 to 11 years were given one dose of sumatriptan nasal spray based on age and weight; children 6 to 8 years of age weighing </= 25 kg received 5 mg (n = 3), children ages 6 to 8 years weighing > 25 kg and children ages 9 to 11 years of age weighing </= 40 kg received 10 mg (n = 10), and children ages 9 to 11 years weighing > 40 kg received 20 mg (n = 4). Plasma sumatriptan concentrations were determined in serial blood samples obtained over 8 hours. Pharmacokinetic analysis included both noncompartmental and population modeling methods. The pharmacokinetic parameter estimates (geometric mean [95% confidence interval]) following 5, 10, and 20 mg sumatriptan were, respectively, as follows: maximum concentration = 8.1 ng/mL (3.6-18.4), 10.8 ng/mL (7.7-15.4), and 12.3 ng/mL (7.6-19.9); half-life = 1.4 hours (1.2-1.8), 1.7 hours (1.4-2.0), and 1.7 hours (1.3-2.3); and AUC = 27.8 ng*h/mL (9.7-79.8), 42.4 ng*h/mL (30.6-58.8), and 49.2 ng*h/mL (32.9-73.7). The median time to maximum concentration for all groups was 2 hours. Population pharmacokinetic modeling included pooled data from this study and from an adolescent study (n = 16). Clearance (CL/F) was 197 L/h for a 30-kg child with between-subject variability of 28%, and the volume of distribution was 751 L, normalized for an 11-year-old child with variability of 43%. The covariate analysis showed that volume increases with age and clearance increases with body size. The absorption was complex, often displaying double-peak plasma concentrations, with a rapid absorption phase and a delayed and rate-limited absorption phase. The dosing scheme based on age and weight resulted in maximal concentrations (C(max)) and systemic exposure (AUC) that were comparable to those observed in adolescents and adults treated with 20 mg. The age- and weight-adjusted dosing scheme appears to an appropriate initial dosing regimen for children with migraine headache. Appropriate safety and efficacy trials will need to be completed in children prior to recommending its use in children.

Prediction of human pharmacokinetics from animal data and molecular structural parameters using multivariate regression analysis: volume of distribution at steady state

The aim of this study was to develop a regression equation for predicting volume of distribution at steady state (Vd(ss)) in humans to enable application to various types of drugs using animal experimental data for rats and dogs and some molecular structural parameters. The Vd(ss) data for rats, dogs and humans of 64 drugs were obtained from literature. The compounds have various structures, pharmacological activities and pharmacokinetic characteristics. In addition, the molecular weight, calculated partition coefficient (clogP), and the number of hydrogen bond acceptors were used as possible descriptors related to the Vd(ss) in humans. Multivariate regression analyses, multiple linear regression analysis and the partial least squares (PLS) method were used to predict Vd(ss) in humans. Interaction terms were also introduced into the regression analysis to evaluate the non-linear relationship. For the data set used in the present study, PLS with quadratic term descriptors gave the best predictive performance. The PLS model using Vd(ss) data for only two animal species and using easily calculated structural parameters could generally predict Vd(ss) in humans better than an allometric method. In addition, the PLS model with only animal data gave almost the same predictive performance as the PLS model with quadratic term descriptors. This model may be easier to use and be practical in a realistic situation, and could predict Vd(ss) in humans better than the allometric method.

Prediction of human clearance from animal data and molecular structural parameters using multivariate regression analysis

The aim of the study reported here was to develop a method for predicting human clearance that can be applied to various kinds of drugs using clearance values for rats and dogs and some molecular structural parameters. The clearance data for rats, dogs, and humans of 68 drugs were obtained from literature. The compounds have various structures, pharmacological activities, and pharmacokinetic characteristics. In addition, molecular weight, c log P, and the number of hydrogen bond acceptors were used as possible descriptors related to the human clearance value for each drug. Three types of regression methods, multiple linear regression (MLR) analysis, partial least squares (PLS) method, and artificial neural network (ANN), were used to predict human clearance, and their predictive performances were compared with allometric approaches, which have been widely used in interspecies scaling. In MLR and PLS analyses, interaction terms were introduced to evaluate the nonlinear relationships. For the data sets used in the present study, MLR and PLS with quadratic terms gave the same equation and the best predictive performance. The value of the squared cross-validated correlation coefficient (q(2)) was 0.682. In conclusion, the MLR method using animal clearance data from only two species and using easily calculated structural parameters can generally predict human clearance better than allometric methods. This approach can be applied to drugs with various characteristics.

Non-linear mixed effects modeling of sparse concentration data from rats: application to a glycogen phosphorylase inhibitor

We investigated the use of non-linear mixed effects modeling in two preclinical studies of the glycogen phosphorylase inhibitor 1,4-dideoxy-1,4-imino-D-arabinitol (DAB). In a 28-day repeated-dose toxicity study rats were dosed once daily p.o. with 0, 20, 45, 100, or 470 mg/kg of DAB in aqueous solutions by oral gavage. Three blood samples were obtained from each animal using a staggered sampling scheme. During the cause of model development, data were included from a safety pharmacological cardiovascular study, in which rats were dosed once orally with 0, 4, 40, or 400 mg/kg of DAB thereby enabling an extension of the dose range of the model. DAB was assayed in plasma using a validated LC/MS/MS method. Non-linear mixed effects modeling was performed using the software NONMEM. The covariate analysis comprised dose, sex and time. Exposure results (Cmax, AUC) obtained by mixed effects modeling were compared to results from noncompartmental analysis using naïve pooling of data. The final model was a one-compartment model with first order absorption and a saturation-like dose dependent increase of the (oral) clearance (CL/f) and volume of distribution (V/f). Furthermore, V/f increased (by 55%) from Day 1 to Day 28. The dose dependencies of CL/f and V/f were most likely due to dose dependent decreases of the fraction systemically absorbed (f). The mechanism behind the dose dependencies may be saturation of a (putative) carrier mediated transport or modulation of tight junctions causing a reduced paracellular transport across the intestinal epithelium. Exposure results obtained from the model compared well with results obtained using noncompartmental analysis. An analysis of the data requirements for non-linear mixed effects modeling showed that at least three concentration values per animal were required for model development. We conclude that non-linear mixed effects modeling is feasible even with dose dependent pharmacokinetics in preclinical studies, such as 28-day toxicity studies in rodents. Supplementing data from additional preclinical studies may be required in order to extend the dose range. Non-linear mixed effects models may prove to be valuable tools in early PK and PK-PD modeling during drug development.

Mixed-effects modeling of the interspecies pharmacokinetic scaling of oxytetracycline

Differences in the disposition of certain drugs across mammalian species often arise because of their diverse physiology and anatomical characteristics. Factors such as body mass, brain weight, and maximum lifespan are related to the way that different species of mammals handle drugs. Drug disposition data can be scaled across species when chronological time is substituted by the appropriate measure of pharmacokinetic time. In this study, we developed allometric scaling models for oxytetracycline, using serum disposition data obtained from the Food Animal Residue Avoidance Databank. The data were modeled using the mixed-effects modeling approach. The models obtained were validated using disposition data on swine. Oxytetracycline scaled across species based on body weight and the best interspecies model adequately predicted the value of the pharmacokinetic parameters across species. The population approach allows one to estimate the allometric coefficients and exponents of the pharmacokinetic parameters to obtain a model that best fits the multi-species pooled concentration-time data. Furthermore, this approach allows decisions to be made based on the statistical significance of the parameter estimates and the adequacy of the models that are not possible with traditional approaches.

Pharmacokinetic/pharmacodynamic studies in drug product development

In the quest of ways for rationalizing and accelerating drug product development, integrated pharmacokinetic/pharmacodynamic (PK/PD) concepts provide a highly promising tool. PK/PD modeling concepts can be applied in all stages of preclinical and clinical drug development, and their benefits are multifold. At the preclinical stage, potential applications might comprise the evaluation of in vivo potency and intrinsic activity, the identification of bio-/surrogate markers, as well as dosage form and regimen selection and optimization. At the clinical stage, analytical PK/PD applications include characterization of the dose-concentration-effect/toxicity relationship, evaluation of food, age and gender effects, drug/drug and drug/disease interactions, tolerance development, and inter- and intraindividual variability in response. Predictive PK/PD applications can also involve extrapolation from preclinical data, simulation of drug responses, as well as clinical trial forecasting. Rigorous implementation of the PK/PD concepts in drug product development provides a rationale, scientifically based framework for efficient decision making regarding the selection of potential drug candidates, for maximum information gain from the performed experiments and studies, and for conducting fewer, more focused clinical trials with improved efficiency and cost effectiveness. Thus, PK/PD concepts are believed to play a pivotal role in streamlining the drug development process of the future.

Allometric scaling of xenobiotic clearance: uncertainty versus universality

Statistical analysis and Monte Carlo simulation were used to characterize uncertainty in the allometric exponent (b) of xenobiotic clearance (CL). CL values for 115 xenobiotics were from published studies in which at least 3 species were used for the purpose of interspecies comparison of pharmacokinetics. The b value for each xenobiotic was calculated along with its confidence interval (CI). For 24 xenobiotics (21%), there was no correlation between log CL and log body weight. For the other 91 cases, the mean +/- standard deviation of the b values was 0.74 +/- 0.16; range: 0.29 to 1.2. Most (81%) of these individual b values did not differ from either 0.67 or 0.75 at P = 0.05. When CL values for the subset of 91 substances were normalized to a common body weight coefficient (a), the b value for the 460 adjusted CL values was 0.74; the 99% CI was 0.71 to 0.76, which excluded 0.67. Monte Carlo simulation indicated that the wide range of observed b values could have resulted from random variability in CL values determined in a limited number of species, even though the underlying b value was 0.75. From the normalized CL values, four xenobiotic subgroups were examined: those that were (i) protein, and those that were (ii) eliminated mainly by renal excretion, (iii) by metabolism, or (iv) by renal excretion and metabolism combined. All subgroups except (ii) showed a b value not different from 0.75. The b value for the renal excretion subgroup (21 xenobiotics, 105 CL values) was 0.65, which differed from 0.75 but not from 0.67.

Mixed effects modeling of the disposition of gentamicin across domestic animal species

An interspecies pharmacokinetic model for gentamicin was developed using the mixed effects modeling approach and serum disposition data obtained from the Food Animal Residue Avoidance Databank (FARAD). Data that met a priori quality criteria was obtained from the database and analysed using the traditional double logarithmic analysis and the mixed effects modeling approach. Body weight, brain weight and fever were the covariates of interest in our study. Population pharmacokinetic models across species were developed and validated with swine data. The parameter volume of distribution was modeled as a function of body weight. The total clearance was initially modeled as a function of body weight. The predictability performance of the model improved dramatically when the parameter brain weight was included in the covariate model for clearance. This was a surprising finding worthy of further study. The covariate fever seemed to influence the magnitude of the volume of distribution, although the scarcity of data pertaining to diseased animals makes this finding uncertain. We conclude that the pharmacokinetic characteristics of drugs such as gentamicin, can be predicted across species using a population pharmacokinetics modeling approach, and that clinical features that affect species in a similar manner can be also explored in this fashion.

The role of population pharmacokinetics in drug development in light of the Food and Drug Administration's 'Guidance for Industry: population pharmacokinetics'

Population pharmacokinetics (PPK) has evolved from a discipline primarily applied to therapeutic drug monitoring to one that plays a significant role in clinical pharmacology in general and drug development in particular. In February 1999 the US Food and Drug Administration issued a 'Guidance for Industry: Population Pharmacokinetics' that sets out the mechanisms and philosophy of PPK and outlines its role in drug development. The application of PPK to the drug development process plays an important role in the efficient development of safe and effective drugs. PPK knowledge is essential for mapping the response surface, explaining subgroup differences, developing and evaluating competing dose administration strategies, and as an aid in designing future studies. The mapping of the response surface is done to maximise the benefit-risk ratio, so that the impact of the input profile and dose magnitude on beneficial and harmful pharmacological effects can be understood and applied to individual patients. PPK combined with simulation methods provides a tool for estimating the expected range of concentrations from competing dose administration strategies. Once extracted, this knowledge can be applied to labelling or used to assess various future study designs. PPK should be implemented across all phases of drug development. For preclinical studies, PPK can be applied to allometric scaling and toxicokinetic analyses, and is useful for determining 'first time in man' doses and explaining toxicological results. Phase I studies provide initial understanding of the structural model and the effect of possible covariates, and may later be used to evaluate PPK differences between patients and healthy individuals. Phase II studies provide the greatest opportunity to map the response surface. With these PPK models it is possible to gain an improved understanding of the role of the dose on the response surface and of the range of expected responses. In phase III and IV studies, PPK is implemented to further refine the PPK model and to explain unexpected responses. Planning for the implementation of PPK across all phases of drug development is necessary, as well as planning for individual PPK studies. Planning should include: defining important questions, identifying covariates and drug-drug interactions that need to be investigated, and identifying the applications and intended use of the model(s). The plan for each project must have a strategy for data management, data collection, data quality assurance, staff training for data collection, data analysis and model validation.

Use of nonlinear mixed effect modeling for the meta-analysis of preclinical pharmacokinetic data: application to S 20342 in the rat

The standard two-stage analysis of separate preclinical pharmacokinetic (PK) and toxicokinetic (TK) studies may lead to good information on the bioavailability in the rat at a low (pharmacologic) dose but only an idea on the dose/exposure relationship, on gender, and on time effect. In view of these drawbacks, we decided therefore to explore the usefulness of the implementation of a meta-analysis in preclinical studies in a given species (the rat in this case) taking as an example S 20342, an investigational new drug with potential antipsychotic properties. A nonlinear mixed-effect PK model was built from all intravenous (IV) and oral (PO) data collected until the completion of the 4-week toxicity study. The database included data from 201 Wistar rats (161 males and 40 females). Forty animals received the drug IV and 161 PO. The treatment duration ranged from 1 day to 4 weeks. IV doses were 3, 5, and 20 mg/kg, and 11 different oral doses were tested in the range of 5 to 200 mg/kg. Three different salts were administered PO: hydrochloride, sulfate, and mesylate. The modeling was performed with NONMEM IV. The best pharmacokinetic model was a two-compartment model with simultaneous first-order and zero-order absorption. The combination of these two input functions allowed the model to fit the peak plasma concentrations observed in the first hour (first order), especially after oral administration of low doses, and to take into account the prolonged absorption phase when the dose increased (zero order). A significant gender effect was found on CL. In addition, significant positive correlations were found between weight and CL, weight and Vc, and dose and the dose fraction after a zero-order absorption. No covariate significantly influenced the other parameters. In conclusion, the meta-analysis of preclinical data allowed for an objective assessment of statistically significant effects throughout the model-building process, leading to a better knowledge (and thus a better understanding) of preclinical PK in the rat. Moreover, the model obtained could be used to interpret further preclinical specific studies involving a sparse sampling design (e.g., further TK studies and PK/PD studies). Although this meta-analysis is more complicated than the noncompartmental approach and requires a case-by-case effort, it could be very useful to integrate this approach in the preclinical development process.

Mixed effect modeling of sumatriptan pharmacokinetics during drug development: II. From healthy subjects to phase 2 dose ranging in patients

Sumatriptan is indicated for the treatment of migraine attack and cluster headache; it is currently marketed as a subcutaneous injection, nasal spray, and oral tablet. New formulations are under consideration. The knowledge of sumatriptan absorption, combined with PK/PD information would help the design of more efficient formulations. In this perspective, we attempted to model the absorption of sumatriptan by population PK analysis. Data following administration by the intravenous (i.v.), the subcutaneous (s.c.), and the oral (po) route in healthy subjects were analyzed. A large database with full kinetic profiles was constituted. Sumatriptan was administered to 215 healthy subjects (i.v., s.c., and po) and to 143 migraine sufferers (po). The mean age was 31 years (18-86 years) in healthy subject population and was 38 years (18-65 years) in migraine patients. The mean weights were 74 kg (54-104 kg) and 66 kg (38-136 kg) in healthy subjects and migraine patients, respectively, and the mean heights were 176 cm (157-193 cm) and 164 cm (152-183 cm) in healthy subjects and migraine patients, respectively. A NONMEN analysis was performed using a two-compartment disposition model. Oral absorption was modeled with a first-order input followed by a zero-order input. Less biased results were obtained using the FOCE method. The total clearance and the distribution volume at steady state were 71.2 L/hr and 94.5 L after i.v. dosing and 68.7 L/hr and 109 L after inclusion of the s.c. and po data. The absorption phase appeared to last for about 5 hr. The interindividual variability of the main PK parameters was low: It was around 20% for the total clearance and around 30% for the distribution volume at steady state. Although significant, the combination of age and height on clearance did not decrease considerably the interindividual variability of this parameter (decrease of 2.2%); nor was it possible to establish clearly if a migraine attack has an effect on drug absorption because of the sampling scheme during absorption. Simulations have shown that it would have been possible to estimate all the PK parameters with a data set reduced to one quarter of its actual number of samples.