In Silico Dissolution
Integrate digital twins & computational physics for precise drug performance predictions, enhancing development and innovation.
Particle Intrinsic Dissolution
Significant resources are spent developing discriminatory in vitro methods for formulation development and quality assurance. These methods do not always translate to an accurate anticipation of in vivo bioavailability and do not account for the variability microstructure attributes can introduce. Our pixel-based approach uses the innate structures of drug substance and amorphous dispersion particles for discriminatory microstructure evaluation.
Disintegration and Water Uptake
Disintegration speed in tablets is driven by water uptake through porosity networks and the activity of disintegrants. When challenges in disintegration speed and consistency arise, these can be critical to study. With microstructure digital twins of the drug product, we apply computational fluid dynamics to evaluate water uptake phenomena. Our approach integrates microstructure CQAs and mass transfer simulations of permeability, tortuosity, and diffusivity through the tablet matrix.
Controlled and Long-acting Release Prediction
Long-acting drug products such as IUDs, microspheres, and implants are costly to develop. In vitro and in vivo evaluations are lengthy, and extend the time needed to optimize the formulation and manufacturing. Rather than wait for months and years of testing, we work with our partners to predict drug release in silico. Our patented image-based simulation approach integrates the drug product microstructures for an accurate prediction of the anticipated release duration. Our workflow supports a variety of polymer systems and release modes, including diffusion, bulk and surface polymer erosion, and core-sheath mechanisms.
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