Amorphous Solid Dispersions

Amorphous Solid Dispersions

How confident are you in your ASD development strategy?

Amorphous solid dispersions play a pivotal role in the development of BCS Class II and IV drug candidates. These poorly soluble compounds require careful consideration in their design, both during the development of intermediates and the final dosage form. While traditional techniques are great for routine assessments, they are limited in the level of detail they can provide in a time and cost-effective manner. Furthermore, they don’t yield a quantitative picture of the interior and exterior microstructural characteristics of the ASD particles which can critically impact performance behavior. To address this, a new suite of tools is needed to optimize ASD development decisions and timelines. 


Lost time with uncertainty in formulation selection?

Trouble speeding up process development?

Need to troubleshoot unexpected dissolution performance?


Transform your ASD Development

Save Time

Reduce Capital

Build Knowledge

"By applying imaging as a quantitative and predictive tool, our image-based platform has transformed how scientists approach the development of poorly soluble therapeutics."

The DigiM Solution

Enhance understanding and build confidence in 
your ASD program via advanced CQA analysis

High-resolution 3D imaging of spray-dried particle powder using x-ray microscopy provides visualization of wall thickness and void spaces, critical parameters to compaction behavior. 

Formulation Development
and Design

Have you wondered how the ingredients in your tablet interact? Speculate no longer – with advanced imaging analytics, formulation design can be supported by a quantitative understanding of material interfaces at all stages, from spray-dried particles to the final dosage form. DigiM’s solutions for formulation design are supported by best-in-class x-ray microscopy, x-ray micro-CT, and mosaic SEM imaging

Accelerate Selection

Improve formulation decisions through an advanced understanding of ingredient interfaces
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Manufacturing Science
and Technology

Process and manufacturing development can be tricky, from a range of techniques and an even larger library of parameters. At DigiM we believe visualization and microstructure characterization play a fundamental role to accelerate manufacturing knowledge. With just a few milligrams of material, a suite of morphological properties can be quantified in a single experiment. 

Enhance Process Development

Evaluate technique and process parameters impact on compaction behavior and dissolution
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Microstructure imaging for spray drying process development used in an amorphous solid dispersion

Deep learning analytics is applied to classify particles (yellow), particle voids (red), and intra-particle air (green). Critical quality attributes like particle morphology, void space, wall thickness, and surface area can be computed and correlated to process and compaction performance. 

Visualization of connected porosity within tablets which had variation in dissolution time, formulated using SDDs from Lab and GMP batches. 3D imaging data can be used directly to simulate transport properties, providing unprecedented correlation of microstructures with performance.

Performance and
Mechanical Properties

An understanding of the microstructural arrangement of ingredients and porosity within the final dosage form are critical to optimizing dissolution, disintegration, and mechanical properties. 3D imaging analytics is, by design, the ideal tool to visualize and quantify these interactions. 

Understand and
Optimize Performance

Correlate intermediate and final dosage microstructures directly with performance
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Chemistry, Manufacturing,
and Controls

CMC is an integral component of pharmaceutical development, especially for the sensitive properties of amorphous solid dispersions. Whether it’s assessing spray-drying vendors, scaling from lab to GMP, or performing stability studies, we’ve encountered it all. Our microstructure analysis has played a critical role in saving capital and time in CMC assessments. 

Transform CMC Assessments

Evaluate form changes, mechanical failure, technology transfer, and scale-up
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Machine learning image analysis is applied to quantify the volume and distribution of recrystallized drug domains in an amorphous solid dispersion tablet. 

DigiM ASD Customers and Published Work*

*Use of logo does not indicate official company sponsorship or endorsement of DigiM’s services or technologies