A multinomial mixed-effect markou-chain model for modeling sleep architecture:model performance and validation

I disturbi del sonno colpiscono all’incirca il 10% della popolazione mondiale, compromettendo significativamente la qualità della vita di chi ne soffre. Nella pratica clinica queste patologie vengono diagnosticate tramite polisonnografia, una strumentazione che consente di registrare simultaneamente le principali attività elettrofisiologiche legate a questo processo. Il sonno è caratterizzato dal susseguirsi durante la notte di diversi stati (veglia, REM, etc) ed il mantenimento di un’adeguata architettura del sonno è fondamentale. Un modello matematico basato su Markov-chains in un contesto di popolazione è stato sviluppato per descrivere l’architettura del sonno. Lo scopo di questa tesi è stato quello di validare tale modello. Per questo sono stati implementati dei metodi diagnostici basati su simulazione stocastica ed è stato sviluppato un nuovo metodo basato su simulazione stocastica + ri-stima. Il modello è stato validato

A Target-Mediated Drug Disposition model integrated with a T lymphocyte pharmacodynamic model for Otelixizumab.

Objectives: Otelixizumab is a monoclonal antibody currently being investigated in autoimmunity. It is directed against human CD3ε on T lymphocytes. Its pharmacological effects include 1) down modulation of the CD3/T cell receptor complex on T lymphocytes and 2) a decrease of T cells in blood. The aim of the present work was to integrate a mechanistic target-mediated drug disposition (TMDD) model [1] to a T lymphocyte pharmacodynamic (PD) model. Methods: Free drug in serum and CD4+ and CD8+ T lymphocytes counts were measured using immunoassay and flow cytometry, respectively. Free, bound and total receptors were then obtained for both CD4+ and CD8+ T lymphocytes [2]. A QSS-TMDD model accounting for Otelixizumab binding to receptors on both CD4+ and CD8+ cells was implemented [3]. Direct and indirect inhibition models were investigated to describe the observed T cell reduction in blood. Analyses were conducted using NONMEM version 7.2. FOCEI and IMP estimation methods were used and compared. Final models were selected based upon change in OFV, precision estimates, diagnostic plots and visual predictive checks (VPCs). Results: First, a simple one-compartment PK model with MM elimination was identified using available PK data. This PK model was used to drive a direct or an indirect lymphocyte PD model. Both sequential (IPP) and simultaneous PK-PD (T lymphocytes) analyses were implemented. Based on VPCs, the indirect model provided a slightly better description of lymphocyte time-course and variability. Then, our previous QSS-TMDD model [3] was improved including a ‘Study' covariate on linear elimination rate constant (K) with a consequent reduction of the estimated high BSV on K. This QSS-TMDD model was used as input for both lymphocyte PD models. Sequential and simultaneous TMDD-lymphocyte analyses were conducted. To overcome problems with OF minimization and covariance step failure with FOCEI the IMP method was used to achieve minimization with covariance step completion. Both TMDD+direct and TMDD+indirect models adequately described the lymphocyte data. Conclusions: A QSS-TMDD model integrated either to a direct or an indirect inhibitory model was proposed to describe Otelixizumab binding to CD3/TCR on T lymphocytes and subsequent decrease of T lymphocytes in blood. The IMP estimation method proved a useful alternative to FOCEI in case of such complex PK/PD models. Further strategies to improve lymphocytes model integration into TMDD are discussed. References: [1] Gibiansky L, Gibiansky E, Target-Mediated Drug Disposition Model for Drugs That Bind to More than One Target. J Pharmacokinet Pharmacodyn 2010;37:323-346. [2] Wiczling P, Rosenzweig M, Vaickus L, Jusko WJ. Pharmacokinetics and Pharmacodynamics of a Chimeric/Humanized Anti-CD3 Monoclonal Antibody, Otelixizumab (TRX4), in Subjects With Psoriasis and With Type 1 Diabetes Mellitus. J Clinical Pharmacol 2010;50(5):494-506. [3] PAGE 21 (2012) Abstr 2463 [www.page-meeting.org/?abstract=2463

Temporal pharmacokinetic/pharmacodynamic interaction between human CD3ε antigen-targeted monoclonal antibody otelixizumab and CD3ε binding and expression in human peripheral blood mononuclear cell static culture

Otelixizumab is a monoclonal antibody (mAb) directed to human CD3ε, a protein forming part of the CD3/T-cell receptor (TCR) complex on T lymphocytes. This study investigated the temporal interaction between varying concentrations of otelixizumab, binding to human CD3 antigen, and expression of CD3/TCR complexes on lymphocytes in vitro, free from the confounding influence of changing lymphocyte frequencies observed in vivo. A static in vitro culture systemwas established in which primary human peripheral blood mononuclear cells (PBMCs) were incubated over an extended time course with titrated concentrations of otelixizumab. At each time point, free, bound, and total CD3/TCR expression on both CD41and CD81T cells and the amount of free otelixizumab antibody in the supernatant weremeasured. The pharmacokinetics of free otelixizumab in the culture supernatants was saturable, with a shorter apparent half-life at low concentration. Correspondingly, a rapid, otelixizumab concentration-, and time-dependent reduction in CD3/TCR expression was observed. These combined observations were consistent with the phenomenon known as target-mediated drug disposition (TMDD). A mechanistic, mathematical pharmacokinetic/pharmacodynamic (PK/PD) model was then used to characterize the free otelixizumab-CD3 expressiontime relationship. CD3/TCR modulation induced by otelixizumab was found to be relatively fast compared with the re-expression rate of CD3/TCR complexes following otelixizumab removal from supernatants. In summary, the CD3/TCR receptor has been shown to have a major role in determining otelixizumab disposition. A mechanistic PK/PD model successfully captured the PK and PD in vitro data, confirming TMDD by otelixizumab. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics

Temporal Pharmacokinetic/Pharmacodynamic Interaction between Human CD3« Antigen-Targeted Monoclonal Antibody Otelixizumab and CD3« Binding and Expression in Human Peripheral Blood Mononuclear Cell Static Culture s

ABSTRACT Otelixizumab is a monoclonal antibody (mAb) directed to human CD3«, a protein forming part of the CD3/T-cell receptor (TCR) complex on T lymphocytes. This study investigated the temporal interaction between varying concentrations of otelixizumab, binding to human CD3 antigen, and expression of CD3/TCR complexes on lymphocytes in vitro, free from the confounding influence of changing lymphocyte frequencies observed in vivo. A static in vitro culture system was established in which primary human peripheral blood mononuclear cells (PBMCs) were incubated over an extended time course with titrated concentrations of otelixizumab. At each time point, free, bound, and total CD3/TCR expression on both CD41 and CD81 T cells and the amount of free otelixizumab antibody in the supernatant were measured. The pharmacokinetics of free otelixizumab in the culture supernatants was saturable, with a shorter apparent half-life at low concentration. Correspondingly, a rapid, otelixizumab concentration-, and time-dependent reduction in CD3/TCR expression was observed. These combined observations were consistent with the phenomenon known as target-mediated drug disposition (TMDD). A mechanistic, mathematical pharmacokinetic/pharmacodynamic (PK/PD) model was then used to characterize the free otelixizumab-CD3 expressiontime relationship. CD3/TCR modulation induced by otelixizumab was found to be relatively fast compared with the re-expression rate of CD3/TCR complexes following otelixizumab removal from supernatants. In summary, the CD3/TCR receptor has been shown to have a major role in determining otelixizumab disposition. A mechanistic PK/PD model successfully captured the PK and PD in vitro data, confirming TMDD by otelixizumab

Multinomial Logistic Functions in Markov Chain Models of Sleep Architecture: Internal and External Validation and Covariate Analysis

Mixed-effect Markov chain models have been recently proposed to characterize the time course of transition probabilities between sleep stages in insomniac patients. The most recent one, based on multinomial logistic functions, was used as a base to develop a final model combining the strengths of the existing ones. This final model was validated on placebo data applying also new diagnostic methods and then used for the inclusion of potential age, gender, and BMI effects. Internal validation was performed through simplified posterior predictive check (sPPC), visual predictive check (VPC) for categorical data, and new visual methods based on stochastic simulation and estimation and called visual estimation check (VEC). External validation mainly relied on the evaluation of the objective function value and sPPC. Covariate effects were identified through stepwise covariate modeling within NONMEM VI. New model features were introduced in the model, providing significant sPPC improvements. Outcomes from VPC, VEC, and external validation were generally very good. Age, gender, and BMI were found to be statistically significant covariates, but their inclusion did not improve substantially the model’s predictive performance. In summary, an improved model for sleep internal architecture has been developed and suitably validated in insomniac patients treated with placebo. Thereafter, covariate effects have been included into the final model

Pharmacometrics Markup Language (PharmML): Opening New Perspectives for Model Exchange in Drug Development

The lack of a common exchange format for mathematical models in pharmacometrics has been a long-standing problem. Such a format has the potential to increase productivity and analysis quality, simplify the handling of complex workflows, ensure reproducibility of research, and facilitate the reuse of existing model resources. Pharmacometrics Markup Language (PharmML), currently under development by the Drug Disease Model Resources (DDMoRe) consortium, is intended to become an exchange standard in pharmacometrics by providing means to encode models, trial designs, and modeling steps