| 1. |
- Deng, Chenhui, et al.
(author)
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Approaches for modeling within subject variability in pharmacometric count data analysis : dynamic inter-occasion variability and stochastic differential equations
- 2016
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In: Journal of Pharmacokinetics and Pharmacodynamics. - : Springer Science and Business Media LLC. - 1567-567X .- 1573-8744. ; 43:3, s. 305-314
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Journal article (peer-reviewed)abstract
- Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.
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| 2. |
- Ji, S., et al.
(author)
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Brief Questionnaire Derived from PANSS Using a General Probability Model to Assess and Monitor the Clinical Features of Schizophrenia
- 2016
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In: Pharmacopsychiatry. - : Georg Thieme Verlag KG. - 0176-3679 .- 1439-0795. ; 49:3, s. 117-123
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Journal article (peer-reviewed)abstract
- Aim: Patients with schizophrenia require continuous treatment much longer than the duration of their hospitalization, which makes their family members essential in their medical care. However, the evaluation of the disease state could only be done by professionals. This prompted us to seek potent indicators of disease states that are understandable and easy to use for the patients' family.Method: Specific items were firstly extracted from the total PANSS scale. Then 3 096 PANSS scores were analyzed using a nonlinear mixed-effects model (NONMEM). A questionnaire was subsequently developed for family members to assess and monitor the overall severity of schizophrenia. Finally this questionnaire was validated in 33 patients.Results: 2 items (P1 and N4) were extracted from the 8 effective remission items according to the correlation coefficients between the total PANSS score and different combinations of items. P1N4 was defined as the sum of these 2 items. A model was then developed to describe the probability of PANSS >= 60, with P1N4 as indicators. The results indicated that P1N4 could make a good predictor of the overall probability of PANSS >= 60, which was independent of treatment. A brief questionnaire with 7 questions was developed based on the results. External validation results indicated the questionnaire's suitability for a good assessment.Conclusion: Questionnaire developed based on P1 and N4 may facilitate the patients' family members to better understand the disease state and help to prevent relapse.
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| 3. |
- Ji, Shuangmin, et al.
(author)
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Population pharmacokinetic-pharmacodynamic (PopPK/PD) modeling of risperidone and its active metabolite in Chinese schizophrenia patients
- 2016
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In: International journal of clinical pharmacology and therapeutics. - 0946-1965. ; 54:5, s. 378-389
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Journal article (peer-reviewed)abstract
- Purpose: Risperidone is a second-generation antipsychotic agent commonly used in the treatment of 31.1% of schizophrenia patients in China, it is the most commonly-prescribed antipsychotic agent. Despite the abundant use of risperidone, population pharmacokinetic-pharmacodynamic models of risperidone have not been performed in Chinese schizophrenia patients. The objective of this study was to develop a population pharmacokinetic-pharmacodynamic (PopPK/PD) model to describe the PK behavior and efficacy of risperidone and 9-hydroxy-risperidone (active metabolite) in Chinese patients. Methods: Plasma concentration data (702 measurements from 131 patients) and positive and negative syndrome scale (PANSS) scores (258 observations from 56 patients) were analyzed using a nonlinear mixed-effects modeling (NONMEM) approach with first-order conditional estimation with interaction (FOCEI). The influence of potential covariates was evaluated. Model robustness was assessed using external validation, nounalized prediction distribution error, nonparametric bootstrap, and visual predictive check approaches. Results: Risperidone concentration data were well described by a one-compartmental model incorporating an additional compartment that refers to the concentration profiles of 9-hydroxy-risperidone. A complex absorption procedure was incorporated into the model to describe the metabolism of risperidone to 9-hydroxy-risperidone in the gastrointestinal (GI) tract. A binomial distribution in the estimated clearance (CL) of risperidone has been identified in our model. Decrease in PANSS score along with total AUC (AUC(total)) of risperidone and 9-hydroxy-risperidone was best characterized by an E-max model with 3 transit compartments describing the delay of drug effect. Conclusions: Considerable differences in PK behavior and drug effect of risperidone have been identified among Chinese extensive metabolizing (EM) and poor metabolizing (PM) patients. This PopPK/PD model may fulfill individualized treatment in clinical practice and may potentially be transferred to other antipsychotic therapies.
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