ArticleBiomedicines2023
Application of I-Optimal Design for Modeling and Optimizing the Operational Parameters of Ibuprofen Granules in Continuous Twin-Screw Wet Granulation.
Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- From Screening to Optimization: Strategic Implementation of Design of Experiments (DOE) for Robust Nanoparticle Formulation.Polymers · 2026Review
- DSD-Guided Ultrasound-Assisted Protein Recovery From Chlamydomonas reinhardtii: Modeling, Optimization, and Enzyme Inhibitory Activity Assessment.Journal of food science · 2026Article
- A Material-Process-Equipment Integrated Design Method for Accelerating the Process Development of Twin-Screw Wet Granulation.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Developing Active Modified Starch-Based Films Incorporated with Ultrasound-Assisted Muña (Polymers · 2025Article
- Solid-state fermentation of pristinamycin by Streptomyces pristinaespiralis NRRL ISP-5338 using D-optimal design.Bioprocess and biosystems engineering · 2025Article
- Development of a Rapid Method for Residence Time Distribution Measurement in Twin-Screw Wet Granulation Based on Image Processing with Lab Color Space.Pharmaceutics · 2025Article
- D-optimal design model and biosynthetic pathway for gentamicin production by Micromonospora purpureochromogenes NRRL B-16094.BMC microbiology · 2025Article
- Deciphering hygromycin B biosynthetic pathway and D-optimal design for production optimization.World journal of microbiology & biotechnology · 2025Article
- Evaluation of Process Parameters for Continuous Manufacturing of Quetiapine Fumarate Immediate Release Tablets Using Twin Screw Wet Granulation.Pharmaceutical research · 2025Article
- Fabrication and Optimization of a Silodosin In Situ-Forming PLGA Implants for the Treatment of Benign Prostatic Hyperplasia: In Vitro and In Vivo Study.Pharmaceutics · 2024Article
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3 authors.
Funding
Abstract
The continuous twin-screw wet granulation (TSWG) process was investigated and optimized with prediction-oriented I-optimal designs. The I-optimal designs can not only obtain a precise estimation of the parameters that describe the effect of five input process parameters, including the screw speed, liquid-to-solid (L/S) ratio, TSWG feed rate, and numbers of the 30° and 60° mixing elements, on the granule quality in a TSWG process, but it can also provide a prediction of the response to determine the optimum operating conditions. Based on the constraints of the desired granule properties, a design space for the TSWG was determined, and the ranges of the operating parameters were defined. An acceptable degree of prediction was confirmed through validation experiments, demonstrating the reliability and effectiveness of using the I-optimal design method to study the TSWG process. The I-optimal design method can accelerate the screening and optimization of the TSWG process.
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