Automated Scale Reduction of Nonlinear <scp>QSP</scp> Models With an Illustrative Application to a Bone Biology System

Hasegawa, Chihiro; Duffull, Stephen B.

doi:10.1002/psp4.12324

Cited by 12 publications

(17 citation statements)

References 32 publications

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“…The improved performance of the reduced model for alendronate was consistent with the extrapolation result originally shown in denosumab . In both cases, we believe this is related to the presence of osteoclasts as part of the compartmental structure, which are the target (input state) of interest for alendronate in the structure of the reduced model.…”

Section: Parameter Estimates From Reduced and Empirical Models When Usupporting

confidence: 86%

“…This model has been used subsequently in both regulatory and model‐based decisions . In our previous work, we reduced the 28‐compartment full model into a simpler 8‐compartment model using proper lumping coupled to a linearization process . Lumping is a process in which two or more compartments are pooled together into a single compartment while retaining the mechanistic processes relating to mass balance and mass action of the overall pooled (lumped) compartment.…”

Section: Parameter Estimates From Reduced and Empirical Models When Umentioning

confidence: 99%

See 1 more Smart Citation

Reusing Smaller Versions of Large Models: A Case Example of Reuse of a Simplified Bone Model

Hasegawa

Duffull

2019

Clin Pharma and Therapeutics

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Quantitative systems pharmacology (QSP) models are becoming increasingly used to understand the influence of drugs on complicated systems. Techniques have been developed to simplify these models to enable their use for data analysis. These simpler (yet mechanistic) models have been criticized as being specific for a particular drug input and response relationship. We explored the generality of the recently reported reduced bone biology model when applied to a drug affecting a different target.We recently reported a reduced version of the systems bone biology model, which focused on the input effect of denosumab (a RANKL inhibitor) to the system. The original bone biology model was developed and published by Peterson and Riggs 1 and consisted of 28 compartments (differential equations). This model has been used subsequently in both regulatory and model-based decisions. 2 In our previous work, we reduced the 28-compartment full model into a simpler 8-compartment model using proper lumping coupled to a linearization process. 3 Lumping is a process in which two or more compartments are pooled together into a single compartment while retaining the mechanistic processes relating to mass balance and mass action of the overall pooled (lumped) compartment. The purpose of reducing the systems model was to yield a smaller more agile model that can be used for estimation purposes in relation to drug development of denosumab or molecules that target the same mechanism and, similarly, to provide a basis for simulations in clinical practice.The reduced model, consisting of eight compartments in total, included a separate compartment for the output of interest (osteoblast and osteoclast) and an unlumped compartment relating to the denosumab target (RANK-RANKL complex), as per the original systems model. The reduced model was then used as is for estimation purposes. In this setting, the reduced model was trained (i.e., parameter values were estimated) using 1 year of lumbar spine bone mineral density (BMD) data and then used to predict into the following 4 years of BMD data. In addition, two standard pharmacokineticpharmacodynamic (PD) models were developed empirically based on the 1 year data and then were used to predict into the following 4 years of data. The reduced model performed better than either empirical model when extrapolating into the data from 12−48 months.These simpler reduced models, which contain the necessary mechanistic elements, have been criticized as being specific for a particular drug input and response relationship and, hence, need to be re-created each time from the original QSP model in order to explore new targets. That is the somewhat technical process of lumping, or other model simplification technique, which needs to be performed from the full model for every new application. This study aims to explore the generality of the same reduced model when applied to a drug used to prevent and treat osteoporosis that has a different target mechanism. In this case, we used alendronate (a bisphosphonate that s...

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Section: Parameter Estimates From Reduced and Empirical Models When Usupporting

confidence: 86%

Section: Parameter Estimates From Reduced and Empirical Models When Umentioning

confidence: 99%

Reusing Smaller Versions of Large Models: A Case Example of Reuse of a Simplified Bone Model

Hasegawa

Duffull

2019

Clin Pharma and Therapeutics

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“…Of the 10 MATLAB‐based models, the packages provided by Hasegawa and Duffull , Kadidi et al . and Gadkar et al .…”

Section: Model Analysesmentioning

confidence: 99%

“…Of the 10 MATLAB-based models, the packages provided by Hasegawa and Duffull, 13 Kadidi et al, 14 and Gadkar et al 15 all contained "readme" text files describing the code and a single "run" script that loaded multiple files, executed simulations, and generated pharmacokinetic/pharmacodynamic time course figures from the associated manuscripts ( Figures S1-S3). The model of chemotherapy-induced gastrointestinal damage by Shankaran et al 16 purported such in the code annotation, but the supplement did not contain a critical Excel file required to execute the simulation.…”

Section: Model Reproducibilitymentioning

confidence: 99%

Reproducibility of Quantitative Systems Pharmacology Models: Current Challenges and Future Opportunities

Kirouac

Cicali

Schmidt

2019

CPT Pharmacom & Syst Pharma

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The provision of model code is required for publication in CPT: Pharmacometrics & Systems Pharmacology , enabling quantitative systems pharmacology (QSP) model availability. A searchable repository of published QSP models would enhance model accessibility. We assess the feasibility of establishing such a resource based on 18 QSP models published in this journal. However, because of the diversity of software platforms (nine), file formats, and functionality, such a resource is premature. We evaluated 12 of the models (those coded in R, PK ‐Sim/ MoBi, and MATLAB) for functionality. Of the 12, only 4 were executable in that figures from the associated manuscript could be generated via a “run” script. Many researchers are aware of the challenges involved in repurposing published models. We offer some ideas to enable model sharing going forward, including annotation guidelines, standardized formats, and the inclusion of “run” scripts. If practitioners can agree to some minimum standards for the provision of model code, model reuse and extension would be accelerated.

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“…The reduced states, after proper lumping, maintain their physical meaning as in the original system, as do the associated parameters. Recently, a proper lumping technique has been used for the simplification of a large-scale systems pharmacological model for a coagulation network and [9, 10].…”

Section: Introductionmentioning

confidence: 99%

Automated proper lumping for simplification of linear physiologically based pharmacokinetic systems

Pan

Duffull

2019

J Pharmacokinet Pharmacodyn

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Physiologically based pharmacokinetic (PBPK) models are an important type of systems model used commonly in drug development before commencement of first-in-human studies. Due to structural complexity, these models are not easily utilised for future data-driven population pharmacokinetic (PK) analyses that require simpler models. In the current study we aimed to explore and automate methods of simplifying PBPK models using a proper lumping technique. A linear 17-state PBPK model for fentanyl was identified from the literature. Four methods were developed to search the optimal lumped model, including full enumeration (the reference method), non-adaptive random search (NARS), scree plot plus NARS, and simulated annealing (SA). For exploratory purposes, it was required that the total area under the fentanyl arterial concentration–time curve (AUC) between the lumped and original models differ by 0.002% at maximum. In full enumeration, a 4-state lumped model satisfying the exploratory criterion was found. In NARS, a lumped model with the same number of lumped states was found, requiring a large number of random samples. The scree plot provided a starting lumped model to NARS and the search completed within a short time. In SA, a 4-state lumped model was consistently delivered. In simplify an existing linear fentanyl PBPK model, SA was found to be robust and the most efficient and may be suitable for general application to other larger-scale linear systems. Ultimately, simplified PBPK systems with fundamental mechanisms may be readily used for data-driven PK analyses. Electronic supplementary material The online version of this article (10.1007/s10928-019-09644-5) contains supplementary material, which is available to authorized users.

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Automated Scale Reduction of Nonlinear QSP Models With an Illustrative Application to a Bone Biology System

Cited by 12 publications

References 32 publications

Reusing Smaller Versions of Large Models: A Case Example of Reuse of a Simplified Bone Model

Reusing Smaller Versions of Large Models: A Case Example of Reuse of a Simplified Bone Model

Reproducibility of Quantitative Systems Pharmacology Models: Current Challenges and Future Opportunities

Automated proper lumping for simplification of linear physiologically based pharmacokinetic systems

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