Mechanistic Modeling of Wet Stirred Media Milling for Production of Drug Nanosuspensions

2020 ◽  
Vol 22 (1) ◽  
Author(s):  
E. Bilgili ◽  
G. Guner
Keyword(s):  
Mechanistic Modeling ◽  
Media Milling

scholarly journals An Integrated Approach of Mechanistic-Modeling and Machine-Learning for Thickness Optimization of Frozen Microwaveable Foods

Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 763
Author(s):  
Ran Yang ◽  
Zhenbo Wang ◽  
Jiajia Chen
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Food Product ◽  
Integrated Approach ◽  
Mechanistic Modeling ◽  
Bayesian Optimization ◽  
Initial Training ◽  
Thickness Optimization ◽  
Heating Uniformity ◽  
Food Design

Mechanistic-modeling has been a useful tool to help food scientists in understanding complicated microwave-food interactions, but it cannot be directly used by the food developers for food design due to its resource-intensive characteristic. This study developed and validated an integrated approach that coupled mechanistic-modeling and machine-learning to achieve efficient food product design (thickness optimization) with better heating uniformity. The mechanistic-modeling that incorporated electromagnetics and heat transfer was previously developed and validated extensively and was used directly in this study. A Bayesian optimization machine-learning algorithm was developed and integrated with the mechanistic-modeling. The integrated approach was validated by comparing the optimization performance with a parametric sweep approach, which is solely based on mechanistic-modeling. The results showed that the integrated approach had the capability and robustness to optimize the thickness of different-shape products using different initial training datasets with higher efficiency (45.9% to 62.1% improvement) than the parametric sweep approach. Three rectangular-shape trays with one optimized thickness (1.56 cm) and two non-optimized thicknesses (1.20 and 2.00 cm) were 3-D printed and used in microwave heating experiments, which confirmed the feasibility of the integrated approach in thickness optimization. The integrated approach can be further developed and extended as a platform to efficiently design complicated microwavable foods with multiple-parameter optimization.

scholarly journals Combining Mechanistic Modeling and Raman Spectroscopy for Monitoring Antibody Chromatographic Purification

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 683 ◽  
Author(s):  
Feidl ◽  
Garbellini ◽  
Luna ◽  
Vogg ◽  
Souquet ◽  
...  
Keyword(s):  
Experimental Data ◽  
Raman Spectroscopy ◽  
Estimation Procedure ◽  
Mechanistic Modeling ◽  
Spectroscopic Techniques ◽  
Chromatographic Purification ◽  
On Line ◽  
Filter Approach ◽  
Underlying Mechanisms ◽  
Combining Information

Chromatography is widely used in biotherapeutics manufacturing, and the corresponding underlying mechanisms are well understood. To enable process control and automation, spectroscopic techniques are very convenient as on-line sensors, but their application is often limited by their sensitivity. In this work, we investigate the implementation of Raman spectroscopy to monitor monoclonal antibody (mAb) breakthrough (BT) curves in chromatographic operations with a low titer harvest. A state estimation procedure is developed by combining information coming from a lumped kinetic model (LKM) and a Raman analyzer in the frame of an extended Kalman filter approach (EKF). A comparison with suitable experimental data shows that this approach allows for the obtainment of reliable estimates of antibody concentrations with reduced noise and increased robustness.

scholarly journals Accelerated Repurposing and Drug Development of Pulmonary Hypertension Therapies for COVID-19 Treatment Using an AI-Integrated Biosimulation Platform

Molecules ◽  
2021 ◽  
Vol 26 (7) ◽  
pp. 1912
Author(s):  
Kaushik Chakravarty ◽  
Victor G. Antontsev ◽  
Maksim Khotimchenko ◽  
Nilesh Gupta ◽  
Aditya Jagarapu ◽  
...  
Keyword(s):  
Pulmonary Hypertension ◽  
Renin Angiotensin System ◽  
Mechanistic Modeling ◽  
Channel Blockers ◽  
Angiotensin System ◽  
In Silico Modeling ◽  
Site Of Action ◽  
Line Of Therapy

The COVID-19 pandemic has reached over 100 million worldwide. Due to the multi-targeted nature of the virus, it is clear that drugs providing anti-COVID-19 effects need to be developed at an accelerated rate, and a combinatorial approach may stand to be more successful than a single drug therapy. Among several targets and pathways that are under investigation, the renin-angiotensin system (RAS) and specifically angiotensin-converting enzyme (ACE), and Ca2+-mediated SARS-CoV-2 cellular entry and replication are noteworthy. A combination of ACE inhibitors and calcium channel blockers (CCBs), a critical line of therapy for pulmonary hypertension, has shown therapeutic relevance in COVID-19 when investigated independently. To that end, we conducted in silico modeling using BIOiSIM, an AI-integrated mechanistic modeling platform by utilizing known preclinical in vitro and in vivo datasets to accurately simulate systemic therapy disposition and site-of-action penetration of the CCBs and ACEi compounds to tissues implicated in COVID-19 pathogenesis.

Mechanistic Modeling of the Ball End Milling Process for Multi-Axis Machining of Free-Form Surfaces

2000 ◽  
Vol 123 (3) ◽  
pp. 369-379 ◽  
Author(s):  
Rixin Zhu ◽  
Shiv G. Kapoor ◽  
Richard E. DeVor
Keyword(s):  
End Milling ◽  
Chip Thickness ◽  
Mechanistic Modeling ◽  
Free Form ◽  
Surface Geometry ◽  
Workpiece Surface ◽  
Ball End Milling ◽  
Modeling Approach ◽  
Free Form Surfaces ◽  
Cutting Point

A mechanistic modeling approach to predicting cutting forces is developed for multi-axis ball end milling of free-form surfaces. The workpiece surface is represented by discretized point vectors. The modeling approach employs the cutting edge profile in either analytical or measured form. The engaged cut geometry is determined by classification of the elemental cutting point positions with respect to the workpiece surface. The chip load model determines the undeformed chip thickness distribution along the cutting edges with consideration of various process faults. Given a 5-axis tool path in a cutter location file, shape driving profiles are generated and piecewise ruled surfaces are used to construct the tool swept envelope. The tool swept envelope is then used to update the workpiece surface geometry employing the Z-map method. A series of 3-axis and 5-axis surface machining tests on Ti6A14V were conducted to validate the model. The model shows good computational efficiency, and the force predictions are found in good agreement with the measured data.

scholarly journals Mechanistic Modeling Identifies Drug-Uptake History as Predictor of Tumor Drug Resistance and Nano-Carrier-Mediated Response

ACS Nano ◽  
2013 ◽  
Vol 7 (12) ◽  
pp. 11174-11182 ◽  
Author(s):  
Jennifer Pascal ◽  
Carlee E. Ashley ◽  
Zhihui Wang ◽  
Terisse A. Brocato ◽  
Joseph D. Butner ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Mechanistic Modeling ◽  
Drug Uptake ◽  
Tumor Drug Resistance

Effect of water nanoconfinement on the dynamic properties of paramagnetic colloidal complexes

2021 ◽  
Author(s):  
Luca Bergamasco ◽  
Matteo Morciano ◽  
Matteo Fasano
Keyword(s):  
Molecular Dynamics ◽  
Dynamic Properties ◽  
Mechanistic Modeling ◽  
Paramagnetic Complex ◽  
Local Enhancement ◽  
Relaxation Properties ◽  
Effect Of Water ◽  
Tumbling Motion

We analyze the tumbling motion of a solvated paramagnetic complex close to confining particles. Molecular dynamics data is interpreted via mechanistic modeling, towards design of improved nanovectors for local enhancement of relaxation properties.

Optimization of Performance Variables of Exemestane Nanosuspension Using Box-Behnken Design to Improve Dissolution and Oral Bioavailability

2021 ◽  
Vol 18 ◽  
Author(s):  
Komal Parmar ◽  
Jay Shah
Keyword(s):  
Oral Bioavailability ◽  
In Vitro Dissolution ◽  
Pharmacokinetic Parameters ◽  
Average Particle ◽  
Stability Studies ◽  
Box Behnken Design ◽  
Media Milling ◽  
Dissolution Properties ◽  
Accelerated Stability

Purpose: Present investigation was aimed to fabricate nanocrystal of exemestane, an anticancer drug with poor dissolution properties and oral bioavailability. Methods: Influence of various process parameters on the formulation of exemestane nanosuspension using media milling technique were investigated in the trial batches. Box-Behnken design was applied with independent variables identified in the preliminary studies, viz. X1-Milling time, X2-Amount of stabilizer and X3-Amount of milling agent. In vitro dissolution and in vivo studies were carried out. Solid state characterization (PXRD, SEM, and DSC) studies demonstrated physical changes in drug due to nano-crystallization. Accelerated stability studies of optimized formulation were carried out. Results: Individual process attributes exhibited significant effect on the average particle size of exemestane nanosuspension. Dissolution studies revealed enhancement in drug release rate as compared to pure exemestane powder. The in vivo pharmacokinetic parameters of exemestane nanosuspension showed significant improvement in Cmax and AUC0-t, about 283.85% and 271.63% respectively suggesting amelioration in oral bioavailability by 2.7-fold as compared to pure exemestane. Accelerated stability studies of the optimized formulation suggested stability of the nanocrystals for at least sixmonth period. Conclusion: Nanocrystals prepared by media milling technique were successful in improving the poor dissolution properties and oral bioavailability of exemestane.

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