Suitability of the z-Factor for Dissolution Simulation of Solid Oral Dosage Forms: Potential Pitfalls and Refinements

Hofsäss, Martin A.; Dressman, Jennifer B.

doi:10.1016/j.xphs.2020.05.019

Cited by 16 publications

(6 citation statements)

References 16 publications

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“…This indicated that the correction factor determined from one set of experiments ( Figure 4 ) was relatively constant across experiments as long as the particle-surface-area-related differences were fully reflected in the information the model received from APSD data. Considering this, the correction factor should be less dependent on formulation attributes than the z-factor [ 35 ]. However, within our experimental setup, the correction factor was also adjusting for differences between the “true” accessible surface area of the drug particles and the surface area obtained from APSD measurements (see above).…”

Section: Discussionmentioning

confidence: 99%

Optimization of the Transwell® System for Assessing the Dissolution Behavior of Orally Inhaled Drug Products through In Vitro and In Silico Approaches

et al. 2021

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The aim of this study was to further evaluate and optimize the Transwell® system for assessing the dissolution behavior of orally inhaled drug products (OIDPs), using fluticasone propionate as a model drug. Sample preparation involved the collection of a relevant inhalable dose fraction through an anatomical mouth/throat model, resulting in a more uniform presentation of drug particles during the subsequent dissolution test. The method differed from previously published procedures by (1) using a 0.4 µm polycarbonate (PC) membrane, (2) stirring the receptor compartment, and (3) placing the drug-containing side of the filter paper face downwards, towards the PC membrane. A model developed in silico, paired with the results of in vitro studies, suggested that a dissolution medium providing a solubility of about 5 µg/mL would be a good starting point for the method’s development, resulting in mean transfer times that were about 10 times longer than those of a solution. Furthermore, the model suggested that larger donor/receptor and sampling volumes (3, 3.3 and 2 mL, respectively) will significantly reduce the so-called “mass effect”. The outcomes of this study shed further light on the impact of experimental conditions on the complex interplay of dissolution and diffusion within a volume-limited system, under non-sink conditions.

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Section: Discussionmentioning

confidence: 99%

Optimization of the Transwell® System for Assessing the Dissolution Behavior of Orally Inhaled Drug Products through In Vitro and In Silico Approaches

et al. 2021

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“…r cc,ini is the initial cocrystal particle radius. Equation 18 assumes monodisperse spherical particles and can be rearranged into the following form: where …”

Section: Theoreticalmentioning

confidence: 99%

“…The drug release rate due to cocrystal dissolution is modeled using the so-called “z-factor” equation, which is commonly used for pharmaceutical applications, including commercial software . It is adopted here for cocrystal dissolution as follows: r normald , dis = z w cc , ini 1 / 3 w cc 2 / 3 ( C d , s − C d , b ) where z is defined as z = 3 D d h d ρ cc r cc , ini where D d is the diffusion coefficient.…”

Section: Theoreticalmentioning

confidence: 99%

“…The objective of this work is to develop a predictive in vitro model for the dose-dependent DSP behavior of dissolving cocrystals when considering surface and bulk precipitation. The so-called “ z -factor” equation based on the Noyes–Whitney dissolution model is adopted to describe cocrystal dissolution. The drug precipitation is modeled using population balances with semiempirical relations for nucleation and growth.…”

Section: Introductionmentioning

confidence: 99%

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An In Vitro Model for Cocrystal Dissolution with Simultaneous Surface and Bulk Precipitation

Mendis,

Lakerveld

2023

Mol. Pharmaceutics

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Cocrystals can be promising means of overcoming the poor aqueous solubility of many drugs. However, precipitation of the stable drug at the cocrystal surface or in the bulk medium is often provoked during cocrystal dissolution due to high drug supersaturation, which prevents sustaining high drug concentrations for enhanced bioavailability. There is a need for predictive in vitro models that can accurately describe this cocrystal dissolution−supersaturation−precipitation (DSP) process to aid drug development and formulation design. Consideration of surface precipitation is often essential for such models given the strong impact of surface precipitation on the drug concentration during cocrystal dissolution. However, DSP models that can explicitly account for the effect of surface precipitation are currently lacking. This work presents a population balance-based model to describe in vitro cocrystal DSP behavior, which accounts for cocrystal dissolution, surface precipitation, and bulk precipitation. Dissolution experiments with carbamazepine−succinic acid cocrystals are conducted for model development and validation. The developed model captures all of the principal experimental trends and predicts the dose-dependent DSP behavior outside the regression data set with reasonable accuracy. The results show that surface precipitation is an essential component of the model. Finally, the new model is integrated with numerical optimization to illustrate how it can be used to identify an optimal dose, particle size, and amount of predissolved coformer.

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“…On the other hand, current dissolution models are not considered fully mechanistic, and their applicability needs to be assessed on a case-by-case basis. For example, the Takano model using the z-factor can be appropriate for drugs/dosage forms, where the initial dissolution rate is critical but may be less appropriate for other drugs/dosage form combinations. , Nevertheless, it has to be noted that such input (i.e., z-factor) is often obtained from in vitro dissolution in aqueous media that does not adequately reflect the luminal contents of the GI tract. Pepin et al have proposed the use of fitted particle size distribution (PSD) to simulate in vivo dissolution in cases where the absorption is dissolution limited .…”

Section: Knowledge Gaps Challenges and Limitationsmentioning

confidence: 99%

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Support Waivers of In Vivo Clinical Studies: Current Status, Challenges, and Opportunities

Loisios-Konstantinidis

Dressman

2020

Mol. Pharmaceutics

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Physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling has been extensively applied to quantitatively translate in vitro data, predict the in vivo performance, and ultimately support waivers of in vivo clinical studies. In the area of biopharmaceutics and within the context of model-informed drug discovery and development (MID3), there is a rapidly growing interest in applying verified and validated mechanistic PBPK models to waive in vivo clinical studies. However, the regulatory acceptance of PBPK analyses for biopharmaceutics and oral drug absorption applications, which is also referred to variously as “PBPK absorption modeling” [CPT: Pharmacometrics Syst. Pharmacol.20176492], “physiologically based absorption modeling”, or “physiologically based biopharmaceutics modeling” (PBBM), remains rather low [J. Pharm. Sci.20161052723] [AAPS J.20192129]. Despite considerable progress in the understanding of gastrointestinal (GI) physiology, in vitro biopharmaceutic and in silico tools, PBPK models for oral absorption often suffer from an incomplete understanding of the physiology, overparameterization, and insufficient model validation and/or platform verification, all of which can represent limitations to their translatability and predictive performance. The complex interactions of drug substances and (bioenabling) formulations with the highly dynamic and heterogeneous environment of the GI tract in different age, ethnic, and genetic groups as well as disease states have not been yet fully elucidated, and they deserve further research. Along with advancements in the understanding of GI physiology and refinement of current or development of fully mechanistic in silico tools, we strongly believe that harmonization, interdisciplinary interaction, and enhancement of the translational link between in vitro, in silico, and in vivo will determine the future of PBBM. This Perspective provides an overview of the current status of PBBM, reflects on challenges and knowledge gaps, and discusses future opportunities around PBPK/PD models for oral absorption of small and large molecules to waive in vivo clinical studies

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Suitability of the z-Factor for Dissolution Simulation of Solid Oral Dosage Forms: Potential Pitfalls and Refinements

Cited by 16 publications

References 16 publications

Optimization of the Transwell® System for Assessing the Dissolution Behavior of Orally Inhaled Drug Products through In Vitro and In Silico Approaches

Optimization of the Transwell® System for Assessing the Dissolution Behavior of Orally Inhaled Drug Products through In Vitro and In Silico Approaches

An In Vitro Model for Cocrystal Dissolution with Simultaneous Surface and Bulk Precipitation

Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling to Support Waivers of In Vivo Clinical Studies: Current Status, Challenges, and Opportunities

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