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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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General scheme shows the Custom PD Step within the PD Units Chain. The figure shows how the Custom Step replaces a default PD Step. Each figure block can be equivalent to a single script containing one or more functions. The output function, Rxu1, from an upstream step “1” is considered as an input function to the PD Custom Step, Xu,custom, while the output from the custom step, Rxu,custom, is considered as an input function, Xu3, to a subsequent step “3”.
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psp412102-fig-0002: General scheme shows the Custom PD Step within the PD Units Chain. The figure shows how the Custom Step replaces a default PD Step. Each figure block can be equivalent to a single script containing one or more functions. The output function, Rxu1, from an upstream step “1” is considered as an input function to the PD Custom Step, Xu,custom, while the output from the custom step, Rxu,custom, is considered as an input function, Xu3, to a subsequent step “3”.

Mentions: Since a Simcyp PD model is linked onto the PBPK simulation model for a specific compound via a chain of response units and each unit comprises a number of built‐in steps in a data flow, this design gives an opportunity for replacing a step within a unit by a custom model (Figure2). In the same way as for a built‐in model, the custom model connects to its input and passes on its output. By this mechanism, the input of the custom model acts in the same manner as the input into the processing step it replaces, and the custom step output feeds back into the sequence of PD processing step in the same way that the output from the step it replaces would have done. Thus, the flow of the PD units is maintained in a sequential manner. The step replacement is represented by a Step function which substitutes a built‐in function with a user‐scripted function in the Simulator's C++ code. If the PD Custom step is on the first step occurrence in a chain of PD response steps (for example on PD Basic 1), the input to the PD Custom step can be a drug (total or free) concentration or amount in plasma, blood, effect compartment, or any other tissue in the PBPK model. It can be the total dose of the drug, if no PK model is assumed. If the PD Custom step is preceded by one or more PD steps, then the input to the PD Custom step is the output from the preceding step. The output response will be the response in the last step in the PD chain returned by the user, however when the codes contain ODEs, the output will also report all state variable profiles. More than one built‐in step can be replaced by a custom step allowing more than 20 places across the various compound types to be used, however replacing only one step can be enough, depending on the PBPKPD model settings.


A Tutorial on Pharmacodynamic Scripting Facility in   Simcyp
General scheme shows the Custom PD Step within the PD Units Chain. The figure shows how the Custom Step replaces a default PD Step. Each figure block can be equivalent to a single script containing one or more functions. The output function, Rxu1, from an upstream step “1” is considered as an input function to the PD Custom Step, Xu,custom, while the output from the custom step, Rxu,custom, is considered as an input function, Xu3, to a subsequent step “3”.
© Copyright Policy - creativeCommonsBy-nc
Related In: Results  -  Collection

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

psp412102-fig-0002: General scheme shows the Custom PD Step within the PD Units Chain. The figure shows how the Custom Step replaces a default PD Step. Each figure block can be equivalent to a single script containing one or more functions. The output function, Rxu1, from an upstream step “1” is considered as an input function to the PD Custom Step, Xu,custom, while the output from the custom step, Rxu,custom, is considered as an input function, Xu3, to a subsequent step “3”.
Mentions: Since a Simcyp PD model is linked onto the PBPK simulation model for a specific compound via a chain of response units and each unit comprises a number of built‐in steps in a data flow, this design gives an opportunity for replacing a step within a unit by a custom model (Figure2). In the same way as for a built‐in model, the custom model connects to its input and passes on its output. By this mechanism, the input of the custom model acts in the same manner as the input into the processing step it replaces, and the custom step output feeds back into the sequence of PD processing step in the same way that the output from the step it replaces would have done. Thus, the flow of the PD units is maintained in a sequential manner. The step replacement is represented by a Step function which substitutes a built‐in function with a user‐scripted function in the Simulator's C++ code. If the PD Custom step is on the first step occurrence in a chain of PD response steps (for example on PD Basic 1), the input to the PD Custom step can be a drug (total or free) concentration or amount in plasma, blood, effect compartment, or any other tissue in the PBPK model. It can be the total dose of the drug, if no PK model is assumed. If the PD Custom step is preceded by one or more PD steps, then the input to the PD Custom step is the output from the preceding step. The output response will be the response in the last step in the PD chain returned by the user, however when the codes contain ODEs, the output will also report all state variable profiles. More than one built‐in step can be replaced by a custom step allowing more than 20 places across the various compound types to be used, however replacing only one step can be enough, depending on the PBPKPD model settings.

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.