A framework for simplification of quantitative systems pharmacology models in clinical pharmacology

Derbalah, Abdallah; Al‐Sallami, Hesham S.; Hasegawa, Chihiro; Gulati, Abhishek; Duffull, Stephen B.

doi:10.1111/bcp.14451

Cited by 20 publications

(22 citation statements)

References 57 publications

(127 reference statements)

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“…A purpose of creating virtual populations is to explore the influence of between-subject and within-subject variabilities in the system. Because we contend that this may be difficult to realize effectively by reviewing profiles of state variables for plausibility, depending on the aims of the analysis, one suggestion is to consider a model-order reduction method 8 approach to render the full systems model into a smaller mechanistic input-output model that can be used to estimate the between-subject variances in the parameters based on the available data and thereby avoid the issues associated with generating virtual patients.…”

Section: Inferencementioning

confidence: 99%

Potential Issues With Virtual Populations When Applied to Nonlinear Quantitative Systems Pharmacology Models

Duffull

Gulati

2020

CPT Pharmacom & Syst Pharma

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Section: Inferencementioning

confidence: 99%

Potential Issues With Virtual Populations When Applied to Nonlinear Quantitative Systems Pharmacology Models

Duffull

Gulati

2020

CPT Pharmacom & Syst Pharma

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“…Nonetheless, there are still barriers to QSP. Among them is the complexity of the models, and hence simplification via model reduction is recommended ( Derbalah et al, 2022 ). Others include the cost and time of model development due to the large amount of datasets ( Garcia et al, 2021 ).…”

Section: Quantitative Systems Pharmacologymentioning

confidence: 99%

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing

Yow

Govindaraju

Lim³

et al. 2022

Front. Pharmacol.

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In the era of “Bad Bugs, No Drugs,” optimizing antibiotic therapy against multi-drug resistant (MDR) pathogens is crucial. Mathematical modelling has been employed to further optimize dosing regimens. These models include mechanism-based PK/PD models, systems-based models, quantitative systems pharmacology (QSP) and population PK models. Quantitative systems pharmacology has significant potential in precision antimicrobial chemotherapy in the clinic. Population PK models have been employed in model-informed precision dosing (MIPD). Several antibiotics require close monitoring and dose adjustments in order to ensure optimal outcomes in patients with infectious diseases. Success or failure of antibiotic therapy is dependent on the patient, antibiotic and bacterium. For some drugs, treatment responses vary greatly between individuals due to genotype and disease characteristics. Thus, for these drugs, tailored dosing is required for successful therapy. With antibiotics, inappropriate dosing such as insufficient dosing may put patients at risk of therapeutic failure which could lead to mortality. Conversely, doses that are too high could lead to toxicities. Hence, precision dosing which customizes doses to individual patients is crucial for antibiotics especially those with a narrow therapeutic index. In this review, we discuss the various strategies in optimizing antimicrobial therapy to address the challenges in the management of infectious diseases and delivering personalized therapy.

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“…1) QSP methodology toolboxes (Cheng et al, 2017;Ribba et al, 2017;Ermakov et al, 2019;Kirouac et al, 2019;Chae, 2020;Derbalah et al, 2020;Hosseini et al, 2020;Gong et al, 2021) 2) QSP applications (Rieger and Musante, 2016;Stein and Looby, 2018) 3) QSP applications (Bai et al, 2014;Gadkar et al, 2014;Gadkar et al, 2015;Lu et al, 2015;Allen et al, 2016;Rieger and Musante, 2016) 4) Translational aspects of mathematical models (Foteinou et al, 2009;Foteinou et al, 2011) 5) Boolean (Putnins and Androulakis, 2019;Putnins and Androulakis, 2021;Putnins et al, 2022) and agent-based (Dong et al, 2010;Nguyen et al, 2013) modeling.…”

Section: Suggested Literaturementioning

confidence: 99%

“…QSP methodology toolboxes ( Cheng et al, 2017 ; Ribba et al, 2017 ; Ermakov et al, 2019 ; Kirouac et al, 2019 ; Chae, 2020 ; Derbalah et al, 2020 ; Hosseini et al, 2020 ; Gong et al, 2021 )…”

Section: One Approach To Teaching Computational Systems Biology With ...unclassified

Teaching computational systems biology with an eye on quantitative systems pharmacology at the undergraduate level: Why do it, who would take it, and what should we teach?

Androulakis

2022

Front. Syst. Biol.

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Computational systems biology (CSB) is a field that emerged primarily as the product of research activities. As such, it grew in several directions in a distributed and uncoordinated manner making the area appealing and fascinating. The idea of not having to follow a specific path but instead creating one fueled innovation. As the field matured, several interdisciplinary graduate programs emerged attempting to educate future generations of computational systems biologists. These educational initiatives coordinated the dissemination of information across student populations that had already decided to specialize in this field. However, we are now entering an era where CSB, having established itself as a valuable research discipline, is attempting the next major step: Entering undergraduate curricula. As interesting as this endeavor may sound, it has several difficulties, mainly because the field is not uniformly defined. In this manuscript, we argue that this diversity is a significant advantage and that several incarnations of an undergraduate-level CSB biology course could, and should, be developed tailored to programmatic needs. In this manuscript, we share our experiences creating a course as part of a Biomedical Engineering program.

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A framework for simplification of quantitative systems pharmacology models in clinical pharmacology

Cited by 20 publications

References 57 publications

Potential Issues With Virtual Populations When Applied to Nonlinear Quantitative Systems Pharmacology Models

Potential Issues With Virtual Populations When Applied to Nonlinear Quantitative Systems Pharmacology Models

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing

Teaching computational systems biology with an eye on quantitative systems pharmacology at the undergraduate level: Why do it, who would take it, and what should we teach?

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