In Silico Simulation of Dissolution Profiles for Development of Extended-Release Doxazosin Tablets

Duque, Marcelo Dutra; Issa, Michele Georges; Silva, Daniela Amaral; Barbosa, Eduardo José; Löbenberg, Raimar; Ferraz, Humberto Gomes

doi:10.14227/dt250418p14

Cited by 5 publications

(5 citation statements)

References 27 publications

(30 reference statements)

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“…In silico modeling and simulation methods can complement formulation development, increasing the probability of formulation success and bioequivalence and bioavailability studies [ 29 ]. Therefore, assessing the relationship between solubility, particle size, dissolution, and formulation characteristics is essential to reach the rational development of a discriminative dissolution method that can be practically evaluated in silico modeling using DDDPlus™ [ 5 ].…”

Section: Resultsmentioning

confidence: 99%

“…Additionally, the combination of statistical experimental design and modeling & simulation tools has been demonstrated as an exciting approach to formulation development [ 5 , 6 ] that can also be used for dissolution method assessment.…”

Section: Introductionmentioning

confidence: 99%

“…Computer simulations are very useful tools that, in addition to providing reliable and fast results, help reduce the number of in vitro assays. For example, computer software DDDPlus™ (Simulations Plus, Lancaster, CA, USA) can simulate dissolution assays of drug-containing formulations based on data such as molecule physicochemical properties, excipients used, and dissolution apparatus [ 5 , 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

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Development of a Discriminative Dissolution Method, Using In-Silico Tool for Hydrochlorothiazide and Valsartan Tablets

et al. 2023

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Hydrochlorothiazide (HTZ) and Valsartan (VAL) are poorly soluble drugs in BCS classes IV and II. This study aimed to develop a method to assess the dissolution profile of tablets containing HTZ (12.5 mg) and VAL (160 mg) as a fixed-dose combination, using in silico tools to evaluate products marketed in Brazil and Peru. Firstly, in vitro dissolution tests were performed using a fractional factorial design 33−1. Then, DDDPlus™ was used to carry out experimental design assays of a complete factorial design 33. Data from the first stage were used to obtain calibration constants for in silico simulations. The factors used in both designs were formulation, sinker use, and rotation speed. Finally, effects and factor interaction assessment was evaluated based on a statistical analysis of the dissolution efficiency (DE) obtained from simulations. Thus, the established final conditions of the dissolution method were 900 mL of phosphate buffer pH 6.8, 75 rpm of rotation speed, and sinker use to prevent formulation floating. The reference product stood out because of its higher DE than other formulations. It was concluded that the proposed method, in addition to ensuring total HTZ and VAL release from formulations, has adequate discriminative power.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development of a Discriminative Dissolution Method, Using In-Silico Tool for Hydrochlorothiazide and Valsartan Tablets

et al. 2023

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“…Duque et al prepared and optimized the extended-release formulations of doxazosin using DDDPlus (Simulations Plus Inc.) along with the design of experiments (58). Initially, drug dissolution profiles were predicted in the software using the system-generated constituents of the extended-release formulations and compared with the experimental values obtained in the United States Pharmacopeia (USP) apparatus 2.…”

Section: Plethora Of Simulationsmentioning

confidence: 99%

Physiologically Based Pharmacokinetic (PBPK) Modelling for In Vitro-In Vivo Extrapolation: Emphasis on the Use of Dissolution Data

Ghate¹,

Chaudhari²,

Lewis

2019

Dissolution Technol.

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Recently the pharmaceutical sector has witnessed a drastic rise in the advancement and incorporation of computerbased technology into several unit operations. Drug dissolution profiling is an important consideration for the successful development of immediate and extended orally delivered formulations. Physiologically based pharmacokinetic (PBPK) modelling has gained a lot of attention when compared to the one-and two-compartmental modelling in establishing a relationship between the in vitro and in vivo parameters. Moreover, the influence of various factors like food, disease, population variations, transporters, and gastric emptying play a significant part in the in vivo outcome of the dosage form. In silico techniques are capable of addressing these limitations by incorporation of near-to-life replica of the in vivo conditions and are able to provide newer interpretations of conventional dissolution data that cannot be concluded by the generation of pharmacokinetic descriptors alone. This review focuses on the various in silico tools including the theory and studies conducted with dissolution data in recent years.

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“…Many conferences have included sessions that focus on the in silico prediction of ADME properties and toxicity, highlighting the interest in moving these approaches to a point at which they can be used routinely in the drug-discovery process [ 11 – 13 ]. The application of in silico modelling and simulation within drug development is rapidly increasing in the R&D sector of the pharmaceutical industry [ 14 ]. The in silico approach can be used from ADMET property predication to clinical trial simulation.…”

Section: Introductionmentioning

confidence: 99%

In vitro investigation of metabolic fate of α-mangostin and gartanin via skin permeation by LC-MS/MS and in silico evaluation of the metabolites by ADMET predictor™

Rukthong

Sereesongsang

Kulsirirat

et al. 2020

BMC Complement Med Ther

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Background Mangosteen, Garciniam angostana L., is a juicy fruit commonly found in Thailand. The rinds of Garciniam angostana L.have been used as a traditional medicine for the treatment of trauma, diarrhea and skin infection. It is also used in dermatological product such as in cosmetics. The mangosteen pericarp can be used to extract valuable bioactive xanthone compounds such as α-mangostin and gartanin. This study is aimed to predict the metabolism of α-mangostin and gartanin using in silico and in vitro skin permeation strategies. Methods Based on their 2D molecular structures, metabolites of those compounds were predicted in silico using ADMET Predictor™. The Km and Vmax, for 5 important recombinant CYP isozymes 1A2, 2C9, 2C19, 2D6 and 3A4 were predicted. Moreover, the in vitro investigation of metabolites produced during skin permeation using human epidermal keratinocyte cells, neonatal (HEKn cells) was performed by LC-MS/MS. Results It was found that the results derived from in silico were in excellent alignment with those obtained from in vitro studies for both compounds. The prediction referred that gartanin and α-mangostin were the substrate of CYP1A2, 2C9, 2C19 and 3A. In the investigation of α-mangostin metabolites by LC-MS/MS system, the MW of the parent compound was increased from 411.200 to 459.185 Da. Therefore, α-mangostin might be metabolized via tri-oxidation process. The increased molecular weight of parent compound (397.200 to 477.157 Da) illustrated that gartanin might be conjugated to sulfated derivatives. Conclusions In all the studies, α-mangostin and gartanin were predicted to be. metabolized via phase I and phase II metabolism (sulfation), respectively.

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In Silico Simulation of Dissolution Profiles for Development of Extended-Release Doxazosin Tablets

Cited by 5 publications

References 27 publications

Development of a Discriminative Dissolution Method, Using In-Silico Tool for Hydrochlorothiazide and Valsartan Tablets

Development of a Discriminative Dissolution Method, Using In-Silico Tool for Hydrochlorothiazide and Valsartan Tablets

Physiologically Based Pharmacokinetic (PBPK) Modelling for In Vitro-In Vivo Extrapolation: Emphasis on the Use of Dissolution Data

In vitro investigation of metabolic fate of α-mangostin and gartanin via skin permeation by LC-MS/MS and in silico evaluation of the metabolites by ADMET predictor™

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