Mechanistic characterization of oscillatory patterns in unperturbed tumor growth dynamics: The interplay between cancer cells and components of tumor microenvironment.

Mathematical modeling of unperturbed and perturbed tumor growth dynamics (TGD) in preclinical experiments provides an opportunity to establish translational frameworks. The most commonly used unperturbed tumor growth models (i.e. linear, exponential, Gompertz and Simeoni) describe a monotonic increase and although they capture the mean trend of the data reasonably well, systematic model misspecifications can be identified. This represents an opportunity to investigate possible underlying mechanisms controlling tumor growth dynamics through a mathematical framework. The overall goal of this work is to develop a data-driven semi-mechanistic model describing non-monotonic tumor growth in untreated mice. For this purpose, longitudinal tumor volume profiles from different tumor types and cell lines were pooled together and analyzed using the population approach. After characterizing the oscillatory patterns (oscillator half-periods between 8-11 days) and confirming that they were systematically observed across the different preclinical experiments available (p<10-9), a tumor growth model was built including the interplay between resources (i.e. oxygen or nutrients), angiogenesis and cancer cells. The new structure, in addition to improving the model diagnostic compared to the previously used tumor growth models (i.e. AIC reduction of 71.48 and absence of autocorrelation in the residuals (p>0.05)), allows the evaluation of the different oncologic treatments in a mechanistic way. Drug effects can potentially, be included in relevant processes taking place during tumor growth. In brief, the new model, in addition to describing non-monotonic tumor growth and the interaction between biological factors of the tumor microenvironment, can be used to explore different drug scenarios in monotherapy or combination during preclinical drug development.

Integrating Mechanistic and Toxicokinetic Information in Predictive Models of Cholestasis.

Drug development involves the thorough assessment of the candidate's safety and efficacy. In silico toxicology (IST) methods can contribute to the assessment, complementing in vitro and in vivo experimental methods, since they have many advantages in terms of cost and time. Also, they are less demanding concerning the requirements of product and experimental animals. One of these methods, Quantitative Structure-Activity Relationships (QSAR), has been proven successful in predicting simple toxicity end points but has more difficulties in predicting end points involving more complex phenomena. We hypothesize that QSAR models can produce better predictions of these end points by combining multiple QSAR models describing simpler biological phenomena and incorporating pharmacokinetic (PK) information, using quantitative in vitro to in vivo extrapolation (QIVIVE) models. In this study, we applied our methodology to the prediction of cholestasis and compared it with direct QSAR models. Our results show a clear increase in sensitivity. The predictive quality of the models was further assessed to mimic realistic conditions where the query compounds show low similarity with the training series. Again, our methodology shows clear advantages over direct QSAR models in these situations. We conclude that the proposed methodology could improve existing methodologies and could be suitable for being applied to other toxicity end points.

Application of population physiologically based pharmacokinetic modelling to optimize target expression and clearance mechanisms of therapeutic monoclonal antibodies.

AIMS: To use population physiologically based pharmacokinetic (PopPBPK) modelling to optimize target expression, kinetics and clearance of HER1/2 directed therapeutic monoclonal antibodies (mAbs). Thus, to propose a general workflow of PopPBPK modelling and its application in clinical pharmacology. METHODS: Full PBPK model of pertuzumab (PTZ) was developed in patient population using Simcyp V21R1 incorporating mechanistic targeted-mediated drug disposition process by fitting known clinical PK and sparse receptor proteomics data to optimize target expression and kinetics of HER2 receptor. Trastuzumab (TTZ) PBPK modelling was used to validate the optimized HER2 target. Additionally, the simulator was also used to develop a full PBPK model for the HER1-directed mAb cetuximab (CTX) to assess the underlying targeted-mediated drug disposition-independent elimination mechanisms. RESULTS: HER2 final parameterisation coming from the PBPK modelling of PTZ was successfully cross validated through PBPK modelling of TTZ with average fold error (AFE), absolute AFE and percent prediction error values for area under the concentration-time curve (AUC) and maximum plasma concentration (Cmax ) of 1.13, 1.16 and 16, and 1.01, 1.07 and 7, respectively. CTX PBPK model performance was validated after the incorporation of an additional systemic clearance of 0.033 L/h as AFE and absolute AFE showed an acceptable predictive power of AUC and Cmax with percent prediction error of 13% for AUC and 10% for Cmax . CONCLUSIONS: Optimisation of both system and drug related parameters were performed through PBPK modelling to improve model performance of therapeutic mAbs (PTZ, TTZ and CTX). General workflow was proposed to develop and apply PopPBPK to support clinical development of mAbs targeting same receptor.

Quantitative assessment of the exposure-efficacy relationship of glucocerebrosidase using Markovian elements in Gaucher patients treated with enzyme replacement therapy.

AIMS: The aims of this study are (i) to develop a population pharmacokinetic model of enzyme activity in Gaucher-type 1 (GD1) patients after intravenous administration of enzyme replacement therapy (ERT), and (ii) to establish an exposure-efficacy relationship for bone marrow infiltration to propose dose adjustments according to patient covariate values. METHODS: A prospective follow-up, semi-experimental multi-centre study was conducted in four hospitals to evaluate the pharmacokinetics, efficacy and safety of ERT in GD1 patients. Twenty-five individuals with 266 glucocerebrosidase (GCase) observations in plasma and leukocytes and 14 individuals with 68 Spanish magnetic resonance imaging (S-MRI) observations were enrolled. RESULTS: A two concatenated compartment model with zero-order endogenous production and first-order distribution (CL1 = 3.85 × 10-1 L/d) and elimination (CL2 = 1.25 L/d) allowed GCase observations in plasma and leukocytes to be described, respectively. An exponential time dependency (kT = 6.14 × 10-1 d-1 ) effect on CL1 was incorporated. The final exposure-efficacy model was a longitudinal logistic regression model with a first-order Markov element. An Emax function (EC50 = 15.73 U/L and Emax = 2.33) linked steady-state concentrations of GCase in leukocytes to the probability of transition across the different S-MRI stages. CONCLUSION: A population pharmacokinetic model successfully characterized the leukocyte activity-time profiles of GCase following intravenous administration of ERT in GD1 patients together with an exposure-efficacy relationship in bone marrow using Markovian elements. The information obtained from this study could be of high clinical relevance in individualization of ERT in GD1 patients, as this could lead to anticipative decision-making regarding clinical response in bone and optimal dosing strategy.

Evaluation of ABC gene polymorphisms on the pharmacokinetics and pharmacodynamics of capecitabine in colorectal patients: Implications for dosing recommendations.

AIMS: The aims are to develop a population pharmacokinetic model of capecitabine (CAP) and its main metabolites after the oral administration of CAP in colorectal cancer patients with different polymorphisms of the ATP-binding cassette (ABC) gene and a population pharmacokinetic/pharmacodynamic model capable of accounting for the neutropenic effects, and to optimize the dosing strategy based on the polymorphisms of the ABC gene and/or the administration regimen as a single agent or in combination. METHODS: Forty-eight patients diagnosed with colorectal cancer were included, with 432 plasma levels of CAP, 5'-desoxi-5-fluorouridine (5'-DFUR) and 5-fluorouracil (5-FU), and 370 neutrophil observations. Capecitabine doses ranged from 1250 to 2500 mg/m2 /24 h. Plasma measurements of CAP, 5'-DFUR and 5-FU were obtained at 1, 2 and 3 hours post administration. Neutrophil levels were measured between day 15 and day 24 post administration. RESULTS: The pharmacokinetic model incorporates oxaliplatin as a covariate on absorption lag time, rs6720173 (ABCG5 gene) on clearance of 5'-DFUR (182% increase for mutated rs6720173) and rs2271862 (ABCA2 gene) on clearance of 5-FU (184% increase for mutated rs2271862). System- (Circ0 = 3.54 × 109 cells/mL, MTT = 204 hours and γ = 6.0 × 10-2 ) and drug-related (slope [SLP] = 3.1 × 10-2 mL/mg). Co-administration of oxaliplatin resulted in a 2.84-fold increase in SLP. The predicted exposure thresholds to G3/4 neutropenia in combination and monotherapy were 26 and 70 mg·h/L, respectively. CONCLUSIONS: The population pharmacokinetic/pharmacodynamic model characterized the time course of capecitabine and its metabolites in plasma. Dose recommendations of capecitabine in patients with mutated and wild allele for single nucleotide polymorphisms rs2271862 of ≤3000 and ≤2400 mg/m2 /24 h in monotherapy and ≤1750 and ≤600 mg/m2 /24 h in combination with oxaliplatin, respectively, have been proposed.

EMA Review of Daratumumab (Darzalex) for the Treatment of Adult Patients Newly Diagnosed with Multiple Myeloma.

The use of daratumumab in combination with established regimens for the treatment of newly diagnosed multiple myeloma has recently been authorized by the European Medicines Agency based on results from three separate phase III randomized, active controlled, open-label studies that have confirmed enhanced efficacy and tolerability in both transplant-ineligible (MMY3008 and MMY3007) and transplant-eligible (MMY3006) patients, without compromising transplant ability. Trial MMY3008 showed an improvement in progression-free survival (PFS) when daratumumab was added to lenalidomide and dexamethasone compared with lenalidomide and dexamethasone; the median PFS had not been reached in the daratumumab arm and was 31.9 months in the control arm (hazard ratio [HR], 0.56; 95% confidence interval [CI], 0.43-0.73; p < .0001). Trial MMY3007 showed an improvement in PFS when daratumumab was added to bortezomib, melphalan, and prednisone compared with bortezomib, melphalan, and prednisone; PFS had not been reached in the daratumumab arm and was 18.1 months in the control arm (HR, 0.5; 95% CI, 0.38-0.65; p < .0001). In trial MMY3006, daratumumab added to bortezomib, thalidomide, and dexamethasone was compared with bortezomib, thalidomide, and dexamethasone as induction and consolidation treatment prior to autologous stem cell transplant. The stringent complete response rate at day 100 after transplant in the daratumumab group was 29% compared with 20% in the control group (odds ratio, 1.60; 1.21-2.12 95% CI; p = .0010). Overall adverse events were manageable, with an increased rate of neutropenia and infections in the daratumumab arms. Regulatory assessment of efficacy and safety results from trials MMY3006, MMY3007, and MMY3008 confirmed a positive benefit-risk ratio leading to an approval of the extensions of indication. IMPLICATIONS FOR PRACTICE: A set of extensions of indication was recently approved for daratumumab (Darzalex) in the setting of newly diagnosed multiple myeloma in combination with established regimens. Results of the MMY3006, MMY3007, and MMY3008 trials have shown enhanced efficacy and a favorable side effect profile of several daratumumab-based combinations in patients both ineligible and eligible for transplant, without compromising transplant ability. The combinations of daratumumab with either lenalidomide and low-dose dexamethasone or bortezomib, melphalan, and prednisone were approved for transplant-ineligible patients. The combination of daratumumab with bortezomib, thalidomide, and dexamethasone was approved for transplant-eligible patients. These combinations are expected to improve the survival outlook for patients with multiple myeloma, without an unacceptable risk of increase in adverse events, and updated information on progression-free survival and overall survival is expected from the above trials.

Topiramate pharmacokinetics in neonates undergoing therapeutic hypothermia and proposal of an optimised dosing schedule.

AIM: The adequate dosing of topiramate in neonates undergoing therapeutic hypothermia has not been established. The aim of this study was to design a dosing schedule capable of providing topiramate serum concentrations within the accepted therapeutic range. METHODS: Neonates (n = 52) with hypoxic ischaemic encephalopathy and subjected to therapeutic hypothermia were dosed with topiramate, 5 mg/kg on day one and 3 mg/kg on days two to five, to decrease seizure events. A total of 451 topiramate serum concentrations obtained in the patients were used to develop a population pharmacokinetic model using a non-linear mixed-effects modelling approach. RESULTS: A one-compartment model with first-order absorption and two different clearance terms, one for the cooling period and another for the post-warming period, were used to describe the concentration-time topiramate data. The probability of no-seizure events could not be related to topiramate concentrations, which was attributed to excessively low topiramate concentrations. A modified dosage schedule was designed with the aim of obtaining more than 90% of patients with topiramate concentrations within the therapeutic range after the first dose. CONCLUSION: The dosage schedule of topiramate in these patients should be modified with the aim of decreasing the frequency of seizure events.

Systematic Modeling and Design Evaluation of Unperturbed Tumor Dynamics in Xenografts.

Xenograft mice are largely used to evaluate the efficacy of oncological drugs during preclinical phases of drug discovery and development. Mathematical models provide a useful tool to quantitatively characterize tumor growth dynamics and also optimize upcoming experiments. To the best of our knowledge, this is the first report where unperturbed growth of a large set of tumor cell lines (n = 28) has been systematically analyzed using a previously proposed model of nonlinear mixed effects (NLME). Exponential growth was identified as the governing mechanism in the majority of the cell lines, with constant rate values ranging from 0.0204 to 0.203 day-1 No common patterns could be observed across tumor types, highlighting the importance of combining information from different cell lines when evaluating drug activity. Overall, typical model parameters were precisely estimated using designs in which tumor size measurements were taken every 2 days. Moreover, reducing the number of measurements to twice per week, or even once per week for cell lines with low growth rates, showed little impact on parameter precision. However, a sample size of at least 50 mice is needed to accurately characterize parameter variability (i.e., relative S.E. values below 50%). This work illustrates the feasibility of systematically applying NLME models to characterize tumor growth in drug discovery and development, and constitutes a valuable source of data to optimize experimental designs by providing an a priori sampling window and minimizing the number of samples required.

Target-Site Investigation for the Plasma Prolactin Response: Mechanism-Based Pharmacokinetic-Pharmacodynamic Analysis of Risperidone and Paliperidone in the Rat.

To understand the drivers in the biological system response to dopamine D2 receptor antagonists, a mechanistic semiphysiologically based (PB) pharmacokinetic-pharmacodymanic (PKPD) model was developed to describe prolactin responses to risperidone (RIS) and its active metabolite paliperidone (PAL). We performed a microdialysis study in rats to obtain detailed plasma, brain extracellular fluid (ECF), and cerebrospinal fluid (CSF) concentrations of PAL and RIS. To assess the impact of P-glycoprotein (P-gp) functioning on brain distribution, we performed experiments in the absence or presence of the P-gp inhibitor tariquidar (TQD). PK and PKPD modeling was performed by nonlinear mixed-effect modeling. Plasma, brain ECF, and CSF PK values of RIS and PAL were well described by a 12-compartmental semi-PBPK model, including metabolic conversion of RIS to PAL. P-gp efflux functionality was identified on brain ECF for RIS and PAL and on CSF only for PAL. In the PKPD analysis, the plasma drug concentrations were more relevant than brain ECF or CSF concentrations to explain the prolactin response; the estimated EC50 was in accordance with reports in the literature for both RIS and PAL. We conclude that for RIS and PAL, the plasma concentrations better explain the prolactin response than do brain ECF or CSF concentrations. This research shows that PKPD modeling is of high value to delineate the target site of drugs.

Population pharmacokinetic/pharmacodynamic modelling of the effects of axomadol and its O-demethyl metabolite on pupil diameter and nociception in healthy subjects.

AIM: The aim of the present study was to characterize the pharmacokinetic/pharmacodynamic (PK/PD) properties of the active components of axomadol and to quantify their contribution to observed the pupillometric and analgesic (measured through the cold pressor test) effects linking the PD engagement biomarker with clinical response. METHODS: Healthy subjects (n = 74) received either placebo or axomadol orally at doses ranging from 66 mg to 225 mg following multiple dosing regimens in two separate clinical trials. Plasma concentrations of the two enantiomers of axomadol and their metabolites, and PD responses were measured at specific times. The population analysis was performed using NONMEM 7.2. RESULTS: The kinetics of the parent drug and its metabolite could be described simultaneously using an extra compartment mimicking the liver, where the metabolite is formed. The SS parent compound elicited a plasma concentration-dependent increase in pupil diameter, with estimates (percentage relative standard errors) of maximal effect (Emax ) and plasma concentration exerting a half-maximal effect (C50 ) of 0.79 (17.4) mm, and 90.7 (27) ng ml(-1) , respectively. The predicted effect site concentrations of the RR O-demethyl metabolite decreased the pupil diameter linearly, with an estimate of the slope of 0.00967 (18.7) mm·ml ng(-1) . An additive model, integrating the net effect on pupil diameter, described adequately the reduction in pain with a linear function. The PK/PD model revealed that each 0.5 mm change in pupil diameter is associated with a 10% decrease in cold pressor area under the concentration-time curve effects. CONCLUSIONS: The PK/PD analysis performed enabled the individual contributions of the active compounds to the observed effects to be identified and quantified. These effects were in accordance with the known mechanisms of action - namely, opioid agonism and noradrenaline reuptake inhibition.

Semimechanistic cell-cycle type-based pharmacokinetic/pharmacodynamic model of chemotherapy-induced neutropenic effects of diflomotecan under different dosing schedules.

The current work integrates cell-cycle dynamics occurring in the bone marrow compartment as a key element in the structure of a semimechanistic pharmacokinetic/pharmacodynamic model for neutropenic effects, aiming to describe, with the same set of system- and drug-related parameters, longitudinal data of neutropenia gathered after the administration of the anticancer drug diflomotecan (9,10-difluoro-homocamptothecin) under different dosing schedules to patients (n = 111) with advanced solid tumors. To achieve such an objective, the general framework of the neutropenia models was expanded, including one additional physiologic process resembling cell cycle dynamics. The main assumptions of the proposed model are as follows: within the stem cell compartment, proliferative and quiescent cells coexist, and only cells in the proliferative condition are sensitive to drug effects and capable of following the maturation chain. Cell cycle dynamics were characterized by two new parameters, FProl (the fraction of proliferative [Prol] cells that enters into the maturation chain) and kcycle (first-order rate constant governing cell cycle dynamics within the stem cell compartment). Both model parameters were identifiable as indicated by the results from a bootstrap analysis, and their estimates were supported by date from the literature. The estimates of FProl and kcycle were 0.58 and 1.94 day(-1), respectively. The new model could properly describe the neutropenic effects of diflomotecan after very different dosing scenarios, and can be used to explore the potential impact of dosing schedule dependencies on neutropenia prediction.

Investigating the Discriminatory Power of BCS-Biowaiver in Vitro Methodology to Detect Bioavailability Differences between Immediate Release Products Containing a Class I Drug.

The purpose of this work is to investigate the discriminatory power of the Biopharmaceutics Classification System (BCS)-biowaiver in vitro methodology, i.e., to investigate if a BCS-biowaiver approach would have detected the Cmax differences observed between two zolpidem tablets and to identify the cause of the in vivo difference. Several dissolution conditions were tested with three zolpidem formulations: the reference (Stilnox), a bioequivalent formulation (BE), and a nonbioequivalent formulation (N-BE). Zolpidem is highly soluble at pH 1.2, 4.5, and 6.8. Its permeability in Caco-2 cells is higher than that of metoprolol and its transport mechanism is passive diffusion. None of the excipients (alone or in combination) showed any effect on permeability. All formulations dissolved more than 85% in 15 min in the paddle apparatus at 50 rpm in all dissolution media. However, at 30 rpm the nonbioequivalent formulation exhibited a slower dissolution rate. A slower gastric emptying rate was also observed in rats for the nonbioequivalent formulation. A slower disintegration and dissolution or a delay in gastric emptying might explain the Cmax infra-bioavailability for a highly permeable drug with short half-life. The BCS-biowaiver approach would have declared bioequivalence, although the in vivo study was not conclusive but detected a 14% mean difference in Cmax that precluded the bioequivalence demonstration. Nonetheless, these findings suggest that a slower dissolution rate is more discriminatory and that rotation speeds higher than 50 rpm should not be used in BCS-biowaivers, even if a coning effect occurs.

In vitro-in vivo correlations: general concepts, methodologies and regulatory applications.

The major objective of in vitro-in vivo correlations is to be able to use in vitro data to predict in vivo performance serving as a surrogate for an in vivo bioavailability test and to support biowaivers. Therefore, the aims of this review are: (i) to clarify the factors involved during bio-predictive dissolution method development; and (ii) the elements that may affect the mathematical analysis in order to exploit all information available. This article covers the basic aspects of dissolution media and apparatus used in the development of in vivo predictive dissolution methods, including the latest proposals in this field as well as the summary of the mathematical methods for establishing the in vitro-in vivo relationship and their scope and limitations. The incorporation of physiological relevant factors in the in vitro dissolution method is essential to get accurate in vivo predictions. Standard quality control dissolution methods do not necessarily reflect the in vivo behavior, so they rarely are useful for predicting in vivo performance. The combination of physiological based dissolution methods with physiological-based pharmacokinetics models incorporating gastrointestinal variables will lead to robust tools for drug and formulation development, nevertheless their regulatory use for biowaiver application still require harmonization of the mathematical methods proposed and more detailed recommendations about the procedures for setting up dissolution specifications.

Modified nonsink equation for permeability estimation in cell monolayers: comparison with standard methods.

Cell culture permeability experiments are valuable tools in drug development and candidate selection, but the monolayer preparation protocols and the calculations procedures can affect the permeability estimation. Hence, standardization and method suitability demonstration are necessary steps for using permeability data for regulatory and in vivo prediction purposes. Much attention is usually paid to experimental procedure validation and less to the mathematical analysis of the results although the standard equations used imply several assumptions that many times do not hold. The aim of this study was to use a simulation strategy to explore the performance of a new proposed modified nonsink equation (MNS) for unidirectional apparent permeability estimation in different types of profiles (of cumulative drug amounts versus time) including those in which the initial permeation rate is altered, considering several levels of experimental variability. The second objective was to compare the MNS method with the classical sink and nonsink approaches and finally to explore its usefulness for BCS classification. Real data from permeability experiments representing atypical profiles have been used for fitting with the three approaches, MNS, sink, and nonsink equations, in order to validate the performance of the new proposed model. The results demonstrated that the MNS method is a precise and accurate equation for calculating the apparent unidirectional permeability in any type of profile and different scenarios of variability, in any sink and nonsink conditions, while the standard nonsink equation fails in obtaining good permeability estimations in those situations in which the initial permeation rate is altered. Linear regression models (S and SC) are not valid under nonsink conditions, as expected, as the underlying assumptions (sink conditions) do not hold, but also in situations in which sink conditions are fulfilled but the system variability is high.

Impact of Time on Parameters for Assessing the Microstructure Equivalence of Topical Products: Diclofenac 1% Emulsion as a Case Study.

The demonstration of bioequivalence proposed in the European Medicines Agency's (EMA's) draft guideline for topical products with the same qualitative and quantitative composition requires the confirmation of the internal structure equivalence. The impact of the shelf-life on the parameters proposed for internal structure comparison has not been studied. The objectives of this work were: (1) to quantify the effect of the time since manufacturing on the mean value and variability of the parameters proposed by the EMA to characterize the internal structure and performance of topical formulations of a complex topical formulation, and (2) to evaluate the impact of these changes on the assessment of the microstructure equivalence. A total of 5 batches of a topical emulgel containing 1% diclofenac diethylamine were evaluated 5, 14, and 23 months after manufacture. The zero-shear viscosity (η0), viscosity at 100 s-1 (η100), yield stress (σ0), elastic (G') and viscous (G″) moduli, internal phase droplet size and in vitro release of the active ingredient were characterized. While no change in variability over time was detected, the mean value of all the parameters changed, especially the droplet size and in vitro release. Thus, combining data from batches of different manufacturing dates may compromise the determination of bioequivalence. The results confirm that to assess the microstructural similarity of complex formulations (such as emulgel), the 90% confidence interval limit for the mean difference in rheological and in vitro release parameters should be 20% and 25%, respectively.

Bioequivalence risk assessment of oral formulations containing racemic ibuprofen through a chiral physiologically based pharmacokinetic model of ibuprofen enantiomers.

The characterization of the time course of ibuprofen enantiomers can be useful in the selection of the most sensitive analyte in bioequivalence studies. Physiologically based pharmacokinetic (PBPK) modelling and simulation represents the most efficient methodology to virtually assess bioequivalence outcomes. In this work, we aim to develop and verify a PBPK model for ibuprofen enantiomers administered as a racemic mixture with different immediate release dosage forms to anticipate bioequivalence outcomes based on different particle size distributions. A PBPK model incorporating stereoselectivity and non-linearity in plasma protein binding and metabolism as well as R-to-S unidirectional inversion has been developed in Simcyp®. A dataset composed of 11 Phase I clinical trials with 54 scenarios (27 per enantiomer) and 14,452 observations (7129 for R-ibuprofen and 7323 for S-ibuprofen) was used. Prediction errors for AUC0-t and Cmax for both enantiomers fell within the 0.8-1.25 range in 50/54 (93 %) and 42/54 (78 %) of scenarios, respectively. Outstanding model performance, with 10/10 (100 %) of Cmax and 9/10 (90 %) of AUC0-t within the 0.9-1.1 range, was demonstrated for oral suspensions, which strongly supported its use for bioequivalence risk assessment. The deterministic bioequivalence risk assessment has revealed R-ibuprofen as the most sensitive analyte to detect differences in particle size distribution for oral suspensions containing 400 mg of racemic ibuprofen, suggesting that achiral bioanalytical methods would increase type II error and declare non-bioequivalence for formulations that are bioequivalent for the eutomer.

Population Pharmacokinetic-Pharmacodynamic Analysis of a Reserpine-Induced Myalgia Model in Rats.

(1) Background: Fibromyalgia syndrome (FMS) is a chronic pain condition with widespread pain and multiple comorbidities, for which conventional therapies offer limited benefits. The reserpine-induced myalgia (RIM) model is an efficient animal model of FMS in rodents. This study aimed to develop a pharmacokinetic-pharmacodynamic (PK-PD) model of reserpine in rats, linking to its impact on monoamines (MAs). (2) Methods: Reserpine was administered daily for three consecutive days at dose levels of 0.1, 0.5, and 1 mg/kg. A total of 120 rats were included, and 120 PK and 828 PD observations were collected from 48 to 96 h after the first dose of reserpine. Non-linear mixed-effect data analysis was applied for structural PK-PD model definition, variability characterization, and covariate analysis. (3) Results: A one-compartment model best described reserpine in rats (V = 1.3 mL/kg and CL = 4.5 × 10-1 mL/h/kg). A precursor-pool PK-PD model (kin = 6.1 × 10-3 mg/h, kp = 8.6 × 10-4 h-1 and kout = 2.7 × 10-2 h-1) with a parallel transit chain (k0 = 1.9 × 10-1 h-1) characterized the longitudinal levels of MA in the prefrontal cortex, spinal cord, and amygdala in rats. Reserpine stimulates the degradation of MA from the pool compartment (Slope1 = 1.1 × 10-1 h) and the elimination of MA (Slope2 = 1.25 h) through the transit chain. Regarding the reference dose (1 mg/kg) of the RIM model, the administration of 4 mg/kg would lead to a mean reduction of 65% (Cmax), 80% (Cmin), and 70% (AUC) of MA across the brain regions tested. (4) Conclusions: Regional brain variations in neurotransmitter depletion were identified, particularly in the amygdala, offering insights for therapeutic strategies and biomarker identification in FMS research.

New insights into the role of VKORC1 polymorphisms for optimal warfarin dose selection in Caribbean Hispanic patients through an external validation of a population PK/PD model.

Warfarin, an oral anticoagulant, has been used for decades to prevent thromboembolic events. The complex interplay between CYP2C9 and VKORC1 genotypes on warfarin PK and PD properties is not fully understood in special sub-groups of patients. This study aimed to externally validate a population pharmacokinetic/pharmacodynamic (PK/PD) model for the effect of warfarin on international normalized ratio (INR) and to evaluate optimal dosing strategies based on the selected covariates in Caribbean Hispanic patients. INR, and CYP2C9 and VKORC1 genotypes from 138 patients were used to develop a population PK/PD model in NONMEM. The structural definition of a previously published PD model for INR was implemented. A numerical evaluation of the parameter-covariate relationship was performed. Simulations were conducted to determine optimal dosing strategies for each genotype combinations, focusing on achieving therapeutic INR levels. Findings revealed elevated IC50 for G/G, G/A, and A/A VKORC1 haplotypes (11.76, 10.49, and 9.22 mg/L, respectively), in this population compared to previous reports. The model-guided dosing analysis recommended daily warfarin doses of 3-5 mg for most genotypes to maintain desired INR levels, although subjects with combination of CYP2C9 and VKORC1 genotypes * 2/* 2-, * 2/* 3- and * 2/* 5-A/A would require only 1 mg daily. This research underscores the potential of population PK/PD modeling to inform personalized warfarin dosing in populations typically underrepresented in clinical studies, potentially leading to improved treatment outcomes and patient safety. By integrating genetic factors and clinical data, this approach could pave the way for more effective and tailored anticoagulation therapy in diverse patient groups.

Model-Informed Precision Dosing for Personalized Ustekinumab Treatment in Plaque Psoriasis.

BACKGROUND/OBJECTIVES: Implementing model-informed precision dosing (MIPD) strategies guided by population pharmacokinetic/pharmacodynamic (PK/PD) models could enhance the management of inflammatory diseases such as psoriasis. However, the extent of individual experimental data gathered during MIPD significantly influences the uncertainty in estimating individual PK/PD parameters, affecting clinical dose selection decisions. METHODS: This study proposes a methodology to individualize ustekinumab (UTK) dosing strategies for 23 Spanish patients with moderate to severe chronic plaque psoriasis., considering the uncertainty of individual parameters within a population PK/PD model. RESULTS: An indirect response model from previous research was used to describe the PK/PD relationship between UTK serum concentrations and the Psoriasis Area and Severity Index (PASI) score. A maximum inhibition drug effect (Imax) model was selected, and a first-order remission constant rate of psoriatic skin lesion (kout = 0.016 d-1) was estimated. CONCLUSIONS: The MIPD approach predicted that 35% and 26% of the patients would need an optimized and intensified dosage regimen, respectively, compared to the regimen typically used in clinical practice. This analysis demonstrated its utility as a tool for selecting personalized UTK dosing regimens in clinical practice in order to optimize the probability of achieving targeted clinical outcomes in patients with psoriasis.

Towards precision medicine of long-acting aripiprazole through population pharmacokinetic modelling.

Population pharmacokinetic (popPK) models constitute a valuable tool for characterizing the pharmacokinetic properties of once-monthly long-acting injectable aripiprazole (LAI aripiprazole) and quantifying the sources of variability in drug exposure. Our aim is to develop a popPK model of both aripiprazole and its metabolite dehydro-aripiprazole in patients treated with LAI aripiprazole, and to personalize the dosing regimen of aripiprazole across different sub-groups of patients. This is a prospective study investigating the pharmacokinetics of LAI aripiprazole. A total of 93 patients were included, 21 for model development and 71 for external model evaluation. A one-compartment model with linear absorption and elimination adequately described both aripiprazole and dehydro-aripiprazole concentrations. The weight of the patients has been shown to be the factor that most influences the absorption. However, the metabolizing phenotype for CYP2D6 and the concomitant treatment with strong inhibitors of this cytochrome have been shown to be the covariates that most influence total drug exposure. This is the first popPK model developed for LAI aripiprazole that includes aripiprazole and its main active metabolite, dehydroaripiprazole. It provides a personalized dosage recommendation that maximizes the probability of achieving optimal therapeutic concentrations and minimizes the difficulties associated with trial-and-error therapeutic strategies carried out in clinical practice.