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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.

No MeSH data available.


Simcyp datastores for persistence of script variables at the different scoping levels, together with the Setup, Step, and Simcyp library (sc:) functions and Lua code that can access or modify them. Higher level stores can provide default parameters for lower level access when a requested value is not available at the same level as the get call. The set functions typically set store values at the same level as the function call. sc:sampleIIVDistribution generates individual values from the parameter distribution stored at the next higher level.
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psp412102-fig-0004: Simcyp datastores for persistence of script variables at the different scoping levels, together with the Setup, Step, and Simcyp library (sc:) functions and Lua code that can access or modify them. Higher level stores can provide default parameters for lower level access when a requested value is not available at the same level as the get call. The set functions typically set store values at the same level as the function call. sc:sampleIIVDistribution generates individual values from the parameter distribution stored at the next higher level.

Mentions: Generally, Setup functions map onto execution of simulation contexts and called once a certain simulation context is reached, where Simcyp Library set and get functions can be used to manipulate data stores (see Figure4). In order to control the information passage, the Simcyp data store provides four types of storage space to support PD custom scripting, namely: stores for values scoped at the simulation‐population, compound, individual, and individual‐compound data levels with one Setup function corresponding to each scoping level (Figure4).


A Tutorial on Pharmacodynamic Scripting Facility in   Simcyp
Simcyp datastores for persistence of script variables at the different scoping levels, together with the Setup, Step, and Simcyp library (sc:) functions and Lua code that can access or modify them. Higher level stores can provide default parameters for lower level access when a requested value is not available at the same level as the get call. The set functions typically set store values at the same level as the function call. sc:sampleIIVDistribution generates individual values from the parameter distribution stored at the next higher level.
© Copyright Policy - creativeCommonsBy-nc
Related In: Results  -  Collection

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

psp412102-fig-0004: Simcyp datastores for persistence of script variables at the different scoping levels, together with the Setup, Step, and Simcyp library (sc:) functions and Lua code that can access or modify them. Higher level stores can provide default parameters for lower level access when a requested value is not available at the same level as the get call. The set functions typically set store values at the same level as the function call. sc:sampleIIVDistribution generates individual values from the parameter distribution stored at the next higher level.
Mentions: Generally, Setup functions map onto execution of simulation contexts and called once a certain simulation context is reached, where Simcyp Library set and get functions can be used to manipulate data stores (see Figure4). In order to control the information passage, the Simcyp data store provides four types of storage space to support PD custom scripting, namely: stores for values scoped at the simulation‐population, compound, individual, and individual‐compound data levels with one Setup function corresponding to each scoping level (Figure4).

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.