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A Tutorial on Pharmacodynamic Scripting Facility in   Simcyp

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The Simcyp Simulator provides a framework for mechanistic Physiologically‐Based Pharmacokinetic/Pharmacodynamic modeling of potentially interacting drugs... Examples incorporating differential equations and including inter‐individual variability on parameters are presented... To incorporate inter‐individual variability, the Simcyp Simulator generates virtual populations of individuals from models incorporating structural correlation of multiple factors (including demographics, genetic and disease status) generating an individual subject with its own set of parameters. 1 A more mechanistic simulation approach can incorporate model components that account for and predict individual covariates... These models can represent a kinetic receptor binding model and be transduced to a stimulus response model in a subsequent PD Basic unit... The PD Link unit includes transform link models, which are simple transforms to convert response to a probability or event count rate, and parameterised link models which include indirect response models6 and survival models. 7 The PD Link unit does not include the effect compartment or kinetic receptor binding links as these models are available in the PD Basic unit... sc:setParameter(1,VKORC1) We have coded here a covariate that was found to affect IC50... Such sc:set functions store values at the same scoping level as the function within which they occur ( The sc:get functions try the same level and if the parameter information is not found, go to the next higher scoping level to find the information... sc:setIIVDistribution(3, sc.NORMAL_SD, 45, 0) – Emax sc:setIIVDistribution(4, sc.NORMAL_SD, 0.1, 0) – effect of age EMAX = P[3] * (1+ P[5]) AGEF = P[4]*(sc:getIndivAge ‐ 45) – effect of age on baseline response Furthermore, a freely available R library package has recently been developed to enable a user to run Simcyp directly from the R environment, commonly used for statistical scripting (a similar interfacing facility has been developed for the Matlab environment). 15 This will allow further manipulation of Simcyp parameters from these computing platforms and so could potentially be used for fitting Lua‐coded models as well... A scripting facility for customising PD response models within the Simcyp Simulator has been developed, whereby a user can replace the built‐in model for a given PD step with a script using a dedicated editor.

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Simcyp PD response unit structure and interconnections enabling various combinations of PD units up to three layers.
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psp412102-fig-0001: Simcyp PD response unit structure and interconnections enabling various combinations of PD units up to three layers.

Mentions: Briefly, the architecture of the Simcyp PD module presents a number of different model‐building blocks called PD Response Units (Figure1). Such units can be linked together to develop more complex responses via certain “transduction” options offered by the platform (for the basics of transduction see4). There are two types of PD Response unit; a PD Basic unit and a PD Link unit.1 The PD Basic unit offers the most commonly used simple response models that include, linear, exponential and sigmoidal/Hill,5 providing an option to link them to an effect compartment. These models can represent a kinetic receptor binding model and be transduced to a stimulus response model in a subsequent PD Basic unit. The PD Link unit includes transform link models, which are simple transforms to convert response to a probability or event count rate, and parameterised link models which include indirect response models6 and survival models.7 The PD Link unit does not include the effect compartment or kinetic receptor binding links as these models are available in the PD Basic unit. PD Response units are subdivided into a sequence of steps with associated model choices from unit input to unit output. Each step calculates values according to a chosen model for that step and passes its result to the next step in the sequence. Applications of linking PBPK and these PD models to predict the impact of genotypic variability, formulation differences, differences in target binding capacity and target site drug concentrations on drug responses and variability have been described previously.8


A Tutorial on Pharmacodynamic Scripting Facility in   Simcyp
Simcyp PD response unit structure and interconnections enabling various combinations of PD units up to three layers.
© Copyright Policy - creativeCommonsBy-nc
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036420&req=5

psp412102-fig-0001: Simcyp PD response unit structure and interconnections enabling various combinations of PD units up to three layers.
Mentions: Briefly, the architecture of the Simcyp PD module presents a number of different model‐building blocks called PD Response Units (Figure1). Such units can be linked together to develop more complex responses via certain “transduction” options offered by the platform (for the basics of transduction see4). There are two types of PD Response unit; a PD Basic unit and a PD Link unit.1 The PD Basic unit offers the most commonly used simple response models that include, linear, exponential and sigmoidal/Hill,5 providing an option to link them to an effect compartment. These models can represent a kinetic receptor binding model and be transduced to a stimulus response model in a subsequent PD Basic unit. The PD Link unit includes transform link models, which are simple transforms to convert response to a probability or event count rate, and parameterised link models which include indirect response models6 and survival models.7 The PD Link unit does not include the effect compartment or kinetic receptor binding links as these models are available in the PD Basic unit. PD Response units are subdivided into a sequence of steps with associated model choices from unit input to unit output. Each step calculates values according to a chosen model for that step and passes its result to the next step in the sequence. Applications of linking PBPK and these PD models to predict the impact of genotypic variability, formulation differences, differences in target binding capacity and target site drug concentrations on drug responses and variability have been described previously.8

View Article: PubMed Central - PubMed

AUTOMATICALLY GENERATED EXCERPT
Please rate it.

The Simcyp Simulator provides a framework for mechanistic Physiologically‐Based Pharmacokinetic/Pharmacodynamic modeling of potentially interacting drugs... Examples incorporating differential equations and including inter‐individual variability on parameters are presented... To incorporate inter‐individual variability, the Simcyp Simulator generates virtual populations of individuals from models incorporating structural correlation of multiple factors (including demographics, genetic and disease status) generating an individual subject with its own set of parameters. 1 A more mechanistic simulation approach can incorporate model components that account for and predict individual covariates... These models can represent a kinetic receptor binding model and be transduced to a stimulus response model in a subsequent PD Basic unit... The PD Link unit includes transform link models, which are simple transforms to convert response to a probability or event count rate, and parameterised link models which include indirect response models6 and survival models. 7 The PD Link unit does not include the effect compartment or kinetic receptor binding links as these models are available in the PD Basic unit... sc:setParameter(1,VKORC1) We have coded here a covariate that was found to affect IC50... Such sc:set functions store values at the same scoping level as the function within which they occur ( The sc:get functions try the same level and if the parameter information is not found, go to the next higher scoping level to find the information... sc:setIIVDistribution(3, sc.NORMAL_SD, 45, 0) – Emax sc:setIIVDistribution(4, sc.NORMAL_SD, 0.1, 0) – effect of age EMAX = P[3] * (1+ P[5]) AGEF = P[4]*(sc:getIndivAge ‐ 45) – effect of age on baseline response Furthermore, a freely available R library package has recently been developed to enable a user to run Simcyp directly from the R environment, commonly used for statistical scripting (a similar interfacing facility has been developed for the Matlab environment). 15 This will allow further manipulation of Simcyp parameters from these computing platforms and so could potentially be used for fitting Lua‐coded models as well... A scripting facility for customising PD response models within the Simcyp Simulator has been developed, whereby a user can replace the built‐in model for a given PD step with a script using a dedicated editor.

No MeSH data available.