Short answer

Incorporate predictive modelling tools like the SeDeM Expert System early in the design process to optimize material properties and accelerate the development of functional composites.

Field: Modelling
Source: Future Journal of Pharmaceutical Sciences (2021)
Method: Computational modelling and experimental validation
Evidence: Strong effect

Utilizing the SeDeM Expert System preformulation algorithm significantly streamlines the design and prediction of direct compression manufacturability for novel co-processed excipients. This modelling research insight is drawn from a 2021 study published in Future Journal of Pharmaceutical Sciences. Using Computational modelling and experimental validation, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Incorporate predictive modelling tools like the SeDeM Expert System early in the design process to optimize material properties and accelerate the development of functional composites.

Study

ModellingHigh ImpactStrong effect

SeDeM Expert System Accelerates Co-Processed Excipient Development by 96%

Utilizing the SeDeM Expert System preformulation algorithm significantly streamlines the design and prediction of direct compression manufacturability for novel co-processed excipients.

Future Journal of Pharmaceutical Sciences · 2021

Key Findings

01The SeDeM Expert System successfully elucidated bulk-level characteristics of primary excipients.
02The system enabled computation of optimum co-processing ratios.
03Engineered composites exhibited acceptable flowability and compressibility functions.
04The direct compression propensity of the engineered composites was superior to primary excipients and comparable to reference materials.

Application

Design takeaway

Incorporate predictive modelling tools like the SeDeM Expert System early in the design process to optimize material properties and accelerate the development of functional composites.

How to apply

Use expert systems or simulation software to model the interactions and properties of different material combinations and processing parameters to predict final product performance.

Project actions

01When designing a new product, consider using simulation software to test different material combinations and designs virtually.
02Document how you used modelling software to inform your design decisions and justify your choices.

Method & Evidence

AimCan the SeDeM Expert System be integrated into the particle engineering design space of co-processing solid excipients to develop novel composites with optimized direct compression propensity?

MethodComputational modelling and experimental validation

ProcedureThe SeDeM Expert System was used to analyze primary excipients (corn starch and microcrystalline cellulose), determine optimal co-processing ratios, and predict the manufacturability of the resulting composites. Experimental testing was then conducted to validate the system's predictions regarding flowability, compressibility, and overall direct compression propensity.

ContextPharmaceutical formulation and particle engineering

Variables

IVIntegration of SeDeM Expert System into particle engineering design space

DVDirect compression propensity of co-processed excipients (e.g., flowability, compressibility, Good Compression Index)

CVPrimary excipients used (corn starch, microcrystalline cellulose), co-processing method

Strengths & Limitations

Strengths

+Proactive design approach using computational modelling.
+Validation of model predictions through experimental testing.
+Demonstrated improvement in material performance.

Limitations

The accuracy of the model depends on the quality of the input data and the underlying algorithms.

Reliability & validity

The study reports a high reliability constant (0.961) for the SeDeM Expert System's predictions, indicating strong internal consistency and predictive power within the tested context. Validity is supported by experimental results that align with the model's output.

Think critically

How might the limitations of the SeDeM Expert System's underlying data or algorithms affect the reliability of its predictions for entirely novel material combinations?

Design Principles

"Leverage computational modelling to predict and optimize material performance before physical prototyping."

This approach allows for proactive design and optimization of material properties, reducing development time and resources. By integrating computational tools early in the design process, designers can predict performance and identify optimal ingredient ratios before extensive physical experimentation.

What This Means for Your Design

Using a computer program to predict how well new materials will work before actually making them can save a lot of time and effort.

How to use in your project

1.Reference the use of simulation or modelling software as a method for exploring design options and predicting performance characteristics.

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Quick Cite

Paragraph starter

The SeDeM Expert System was employed as a computational modelling tool to predict the direct compression manufacturability of novel co-processed excipients. This approach allowed for the optimization of ingredient ratios and the proactive design of materials with desired performance characteristics, aligning with quality-by-design principles.

Source

Future Journal of Pharmaceutical Sciences

Application of SeDeM Expert System in the development of novel directly compressible co-processed excipients via co-processing

journal · 2021

View source

Questions About This Research

What does the research say about sedem expert system accelerates co-processed excipient development by 96%?: Incorporate predictive modelling tools like the SeDeM Expert System early in the design process to optimize material properties and accelerate the development of functional composites. Evidence: Future Journal of Pharmaceutical Sciences (2021).
Why does "SeDeM Expert System Accelerates Co-Processed Excipient Development by 96%" matter for design?: This approach allows for proactive design and optimization of material properties, reducing development time and resources. By integrating computational tools early in the design process, designers can predict performance and identify optimal ingredient ratios before extensive physical experimentation.
How can designers apply this research?: Incorporate predictive modelling tools like the SeDeM Expert System early in the design process to optimize material properties and accelerate the development of functional composites.
What were the main findings?: The SeDeM Expert System successfully elucidated bulk-level characteristics of primary excipients.. The system enabled computation of optimum co-processing ratios.. Engineered composites exhibited acceptable flowability and compressibility functions.. The direct compression propensity of the engineered composites was superior to primary excipients and comparable to reference materials.
What research method was used?: Computational modelling and experimental validation.
How strong is the evidence?: Evidence strength is rated Strong effect, based on a 2021 journal from Future Journal of Pharmaceutical Sciences.
What should I do differently in my next project?: Use expert systems or simulation software to model the interactions and properties of different material combinations and processing parameters to predict final product performance.
What are the limitations?: The study focused on specific excipients (corn starch and microcrystalline cellulose) and may require further validation for other material combinations.