Estimators and confidence intervals of f2 using bootstrap methodology for the comparison of dissolution profiles

Background and objectives: The most widely used method to compare dissolution profiles is the similarity factor f2. When this method is not applicable, the confidence interval of using bootstrap methodology has been recommended instead. As neither details of the estimator nor the types of confidence intervals are described in the guidelines, the suitability of five estimators and fourteen types of confidence intervals were investigated in this study by simulation. Methods: One million individual dissolution profiles were simulated for the reference and test populations with predefined target population values, where random samples of different sizes were drawn without replacement. From each pair of random samples, five estimators were calculated, and fourteen types of confidence intervals were obtained using 5000 bootstrap samples. The whole process was repeated 10000 times and the percentage of the similarity conclusions was measured. In addition, the uncertainty associated with the current practice of using point estimate alone for the statistical inference was evaluated

A multilevel object-oriented modelling methodology for physiologically-based pharmacokinetics (PBPK): Evaluation with a semi-mechanistic pharmacokinetic model.

The aims of this study are (i) to assess the predictive reliability of the physiologically based software PhysPK versus the well-known population approach software NONMEM for the cited semi-mechanistic PK model, (ii) to determine whether these modelling approaches are interchangeable and (iii) to compare acausal with causal modelling approaches in the framework of semi-mechanistic PK models

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

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

Mechanistic modelling of immuno-modulators in oncology drug development

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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

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 (p0.05)), 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

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.Pharmacolog