Opening a debate on open‐source modeling tools: Pouring fuel on fire versus extinguishing the flare of a healthy debate

Rostami‐Hodjegan, Amin

doi:10.1002/psp4.12615

Cited by 15 publications

(26 citation statements)

References 21 publications

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“…As MIDD enters mainstream use during drug development by many pharmaceutical companies, community assessment of various models applied to a certain problem and settling on some selected models that can be used repeatedly by a mass of users with assurance on reproducibly of results become inevitable. This is distinct from the somewhat academic research-oriented use (78).…”

Section: Discussionmentioning

confidence: 88%

“…There are plenty of evidence to suggest this has become an integral part of modern drug development by leading pharmaceutical companies (72,73) and all the signs are in place from the top regulatory agencies that MIDD is seen not only acceptable approach in many cases but also an encouraged path in certain circumstances (74)(75)(76)(77). Therefore, the pharmaceutical industry is arriving at a conjuncture where ability to incorporate the MIDD paradigm into widespread practice is not just an internal scientific decision; it is rather a management strategy issue (78). As with many other management tasks this requires careful assessment of implementation (if MIDD nucleus is not in place) and scaling regarding many other elements (personnel, tools, environment and processes).…”

Section: Discussionmentioning

confidence: 99%

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In Vitro to In Vivo Extrapolation Linked to Physiologically Based Pharmacokinetic Models for Assessing the Brain Drug Disposition

Murata

Rostami‐Hodjegan

Takita

et al. 2022

AAPS J

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Drug development for the central nervous system (CNS) is a complex endeavour with low success rates, as the structural complexity of the brain and specifically the blood-brain barrier (BBB) poses tremendous challenges. Several in vitro brain systems have been evaluated, but the ultimate use of these data in terms of translation to human brain concentration profiles remains to be fully developed. Thus, linking up in vitro-to-in vivo extrapolation (IVIVE) strategies to physiologically based pharmacokinetic (PBPK) models of brain is a useful effort that allows better prediction of drug concentrations in CNS components. Such models may overcome some known aspects of inter-species differences in CNS drug disposition. Required physiological (i.e. systems) parameters in the model are derived from quantitative values in each organ. However, due to the inability to directly measure brain concentrations in humans, compound-specific (drug) parameters are often obtained from in silico or in vitro studies. Such data are translated through IVIVE which could be also applied to preclinical in vivo observations. In such exercises, the limitations of the assays and inter-species differences should be adequately understood in order to verify these predictions with the observed concentration data. This report summarizes the state of IVIVE-PBPK-linked models and discusses shortcomings and areas of further research for better prediction of CNS drug disposition.

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Section: Discussionmentioning

confidence: 88%

Section: Discussionmentioning

confidence: 99%

In Vitro to In Vivo Extrapolation Linked to Physiologically Based Pharmacokinetic Models for Assessing the Brain Drug Disposition

Murata

Rostami‐Hodjegan

Takita

et al. 2022

AAPS J

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show abstract

“…Of the drug development applications, all of them used commercial packages that offer more comprehensive verification of the models as demanded by regulators. 27 Although commercial software was also dominant for the clinical and model development application, there was more use of general modeling tools such as MATLAB. This is probably because of the fact that the user has more control over the model code.…”

Section: Conclusion/discussionmentioning

confidence: 99%

Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations

Johnson

Small

Yeo

2022

CPT Pharmacom & Syst Pharma

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There has been a significant increase in the use of physiologically based pharmacokinetic (PBPK) models during the past 20 years, especially for pediatrics.The aim of this study was to give a detailed overview of the growth and areas of application of pediatric PBPK (P-PBPK) models. A total of 181 publications and publicly available regulatory reviews were identified and categorized according to year, author affiliation, platform, and primary application of the P-PBPK model (in clinical settings, drug development or to advance pediatric model development in general). Secondary application areas, including dose selection, biologics, and drug interactions, were also assessed. The growth rate for P-PBPK modeling increased 33-fold between 2005 and 2020; this was mainly attributed to growth in clinical and drug development applications. For primary applications, 50% of articles were classified under clinical, 18% under drug development, and 33% under model development. The most common secondary applications were dose selection (75% drug development), pharmacokinetic prediction and covariate identification (47% clinical), and model parameter identification (68% model development), respectively. Although population PK modeling remains the mainstay of approaches supporting pediatric drug development, the data presented here demonstrate the widespread application of P-PBPK models in both drug development and clinical settings. Although applications for pharmacokinetic and drug-drug interaction predictions in pediatrics is advocated, this approach remains underused in areas such as assessment of pediatric formulations, toxicology, and trial design. The increasing number of publications supporting the development and refinement of the pediatric model parameters can only serve to enhance optimal use of P-PBPK models.

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“…The use of such methods may in fact lead to results that are uninterpretable, or, even worse, open to misinterpretation by non-expert GSA users. Certain applications of PBPK M&S require reliable, robust, well-characterised and tested models [ 45 ]. We believe that these requirements should apply for GSA methods and algorithms as well.…”

Section: Discussionmentioning

confidence: 99%

A latent variable approach to account for correlated inputs in global sensitivity analysis

Melillo

Darwich

2021

J Pharmacokinet Pharmacodyn

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In drug development decision-making is often supported through model-based methods, such as physiologically-based pharmacokinetics (PBPK). Global sensitivity analysis (GSA) is gaining use for quality assessment of model-informed inference. However, the inclusion and interpretation of correlated factors in GSA has proven an issue. Here we developed and evaluated a latent variable approach for dealing with correlated factors in GSA. An approach was developed that describes the correlation between two model inputs through the causal relationship of three independent factors: the latent variable and the unique variances of the two correlated parameters. The latent variable approach was applied to a set of algebraic models and a case from PBPK. Then, this method was compared to Sobol’s GSA assuming no correlations, Sobol’s GSA with groups and the Kucherenko approach. For the latent variable approach, GSA was performed with Sobol’s method. By using the latent variable approach, it is possible to devise a unique and easy interpretation of the sensitivity indices while maintaining the correlation between the factors. Compared methods either consider the parameters independent, group the dependent variables into one unique factor or present difficulties in the interpretation of the sensitivity indices. In situations where GSA is called upon to support model-informed decision-making, the latent variable approach offers a practical method, in terms of ease of implementation and interpretability, for applying GSA to models with correlated inputs that does not violate the independence assumption. Prerequisites and limitations of the approach are discussed.

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Opening a debate on open‐source modeling tools: Pouring fuel on fire versus extinguishing the flare of a healthy debate

Abstract: This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Cited by 15 publications

References 21 publications

In Vitro to In Vivo Extrapolation Linked to Physiologically Based Pharmacokinetic Models for Assessing the Brain Drug Disposition

In Vitro to In Vivo Extrapolation Linked to Physiologically Based Pharmacokinetic Models for Assessing the Brain Drug Disposition

Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations

A latent variable approach to account for correlated inputs in global sensitivity analysis

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