scholarly journals An Optimization-Based Framework to Define the Probabilistic Design Space of Pharmaceutical Processes with Model Uncertainty

Processes ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 96 ◽  
Author(s):  
Daniel Laky ◽  
Shu Xu ◽  
Jose Rodriguez  ◽  
Shankar Vaidyaraman  ◽  
Salvador García Muñoz  ◽  
...  
Keyword(s):  
Process Parameters ◽  
Model Uncertainty ◽  
Design Space ◽  
Probabilistic Design ◽  
Industrial Case Study ◽  
Simulation Based ◽  
Critical Process Parameters ◽  
Input Variables ◽  
Critical Process

To increase manufacturing flexibility and system understanding in pharmaceutical development, the FDA launched the quality by design (QbD) initiative. Within QbD, the design space is the multidimensional region (of the input variables and process parameters) where product quality is assured. Given the high cost of extensive experimentation, there is a need for computational methods to estimate the probabilistic design space that considers interactions between critical process parameters and critical quality attributes, as well as model uncertainty. In this paper we propose two algorithms that extend the flexibility test and flexibility index formulations to replace simulation-based analysis and identify the probabilistic design space more efficiently. The effectiveness and computational efficiency of these approaches is shown on a small example and an industrial case study.

scholarly journals Design Space and QbD Approach for Production of Drug Nanocrystals by Wet Media Milling Techniques

Pharmaceutics ◽  
2018 ◽  
Vol 10 (3) ◽  
pp. 104 ◽  
Author(s):  
Leena Peltonen
Keyword(s):  
Process Parameters ◽  
Design Space ◽  
Milling Process ◽  
Production Chain ◽  
Media Milling ◽  
Process Understanding ◽  
Poorly Soluble ◽  
Critical Process Parameters ◽  
Input Variables ◽  
Definition Of

Drug nanocrystals are nanosized solid drug particles, the most important application of which is the improvement of solubility properties of poorly soluble drug materials. Drug nanocrystals can be produced by many different techniques, but the mostly used are different kinds of media milling techniques; in milling, particle size of bulk sized drug material is decreased, with the aid of milling beads, to nanometer scale. Utilization of Quality by Design, QbD, approach in nanomilling improves the process-understanding of the system, and recently, the number of studies using the QbD approach in nanomilling has increased. In the QbD approach, the quality is built into the products and processes throughout the whole production chain. Definition of Critical Quality Attributes, CQAs, determines the targeted final product properties. CQAs are confirmed by setting Critical Process Parameters, CPPs, which include both process parameters but also input variables, like stabilizer amount or the solid state form of the drug. Finally, Design Space determines the limits in which CPPs should be in order to reach CQAs. This review discusses the milling process and process variables, CPPs, their impact on product properties, CQAs and challenges of the QbD approach in nanomilling studies.

scholarly journals A Data-Driven Framework to Predict Fused Filament Fabrication Part Properties Using Surrogate Models and Multi-Objective Optimisation

2021 ◽  
Author(s):  
Yongjie Zhang ◽  
Joon Phil Choi ◽  
Seung Ki Moon
Keyword(s):  
Process Parameters ◽  
Surrogate Models ◽  
Data Driven ◽  
Functional Requirements ◽  
Fused Filament Fabrication ◽  
Process Maps ◽  
Multi Objective ◽  
Critical Process Parameters ◽  
Critical Process

Abstract In additive manufacturing (AM), due to large number of process parameters and multiple responses of interest, it is hard for AM designers to attain optimal part performance without a systematic approach. In this research, a data-driven framework is proposed to achieve the desired AM part performance and quality by predicting part properties and optimizing AM process parameters effectively and efficiently. The proposed framework encompasses efficient sampling of design space and establishing the initial experiment points. Based on established empirical data, surrogate models, are used to characterise influence of critical process parameters on responses on interest. Further, process maps can be generated for enhancing understanding on the influence of process parameters on responses of interests and AM process characteristics. Subsequently, multi-objective optimisation coupled with a multi criteria decision making technique is applied to determine an optimal design point, which maximises the identified responses of interest to meet the part functional requirements. A case study is used to validate the proposed framework for optimising an ULTEM™ 9085 fused filament fabrication part to meet its functional requirements of surface roughness and mechanical strength. From the case study, results indicate that the proposed approach is able to achieve good predictive results for responses of interest with a relatively small dataset. Further, process maps generated from the surrogate model provide a visual representation of the influence between responses of interest and critical process parameters for FFF process, which traditionally requires multiple investigations to arrive at similar conclusions.

scholarly journals Designing ultra-small nanostructured lipid carriers: critical process parameters

2020 ◽  
Author(s):  
Maria Mendes ◽  
João Basso ◽  
João Sousa ◽  
Alberto Pais ◽  
Carla Vitorino
Keyword(s):  
Process Parameters ◽  
Nanostructured Lipid Carriers ◽  
Critical Process Parameters ◽  
Critical Process

scholarly journals Application of Statistical Design to Assess the Critical Process Parameters of Ethanol Injection Method for the Preparation of Liposomes

2019 ◽  
Vol 18 (1) ◽  
pp. 103-111 ◽  
Author(s):  
Sayani Bhattacharyya ◽  
Bharani S Sogali
Keyword(s):  
Particle Size ◽  
Process Parameters ◽  
Particle Size Analysis ◽  
Polydispersity Index ◽  
Size Analysis ◽  
Ethanol Injection ◽  
Injection Method ◽  
Critical Process Parameters ◽  
Critical Process ◽  
Ethanol Injection Method

In the present study custom screening design was employed to observe the effect of four critical process parameters on particle size and polydispersity index of the liposomal formulation made by ethanol injection method. The four process parameters selected were lipid ratio, rate of injection, phase volume ratio and rotational speed of magnetic stirring. Eight different liposomal formulations were prepared using the design. The formulations were subjected to particle size analysis. The analysis was done at a significance level p<0.05 and found that the process parameters had significant effect on the particle size and polydispersity index of the formulations. The design was optimized for the individual responses with an overall desirability of more than 50%. Three batches of liposomes were formulated at optimized process parameters which matched the target as predicted by the design. Therefore, it can be concluded that the design was effective in production of nano sized stable monodisperse liposomes by ethanol injection method. Dhaka Univ. J. Pharm. Sci. 18(1): 103-111, 2019 (June)

scholarly journals Informing the design of courtyard street blocks using solar energy models: a case study of a university campus in Singapore

2021 ◽  
Vol 2042 (1) ◽  
pp. 012050
Author(s):  
Ekaterina Vititneva ◽  
Zhongming Shi ◽  
Pieter Herthogs ◽  
Reinhard König ◽  
Aurel von Richthofen ◽  
...  
Keyword(s):  
Solar Energy ◽  
Urban Form ◽  
Energy Performance ◽  
University Campus ◽  
Quasi Monte Carlo ◽  
Energy Models ◽  
Simulation Based ◽  
Input Variables ◽  
The City

Abstract This study discusses the interplays between urban form and energy performance using a case study in Singapore. We investigate educational urban quarters in the tropical climate of Singapore using simulation-based parametric geometric modelling. Three input variables of urban form were examined: street network orientation, street canyon width, and building depth. In total, 280 scenarios were generated using a quasi-Monte Carlo Saltelli sampler and Grasshopper. For each scenario, the City Energy Analyst, an open-source urban building energy simulation program, calculated solar energy penetration. To assess the variables’ importance, we applied Sobol’ sensitivity analysis. Results suggest that the street width and building depth were the most influential parameters.

scholarly journals Aeration and Shear Stress Are Critical Process Parameters for the Production of Oncolytic Measles Virus

2019 ◽  
Vol 7 ◽  
Author(s):  
Tanja A. Grein ◽  
Daniel Loewe ◽  
Hauke Dieken ◽  
Tobias Weidner ◽  
Denise Salzig ◽  
...  
Keyword(s):  
Shear Stress ◽  
Process Parameters ◽  
Measles Virus ◽  
Critical Process Parameters ◽  
Critical Process
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