Computational Research in Dziubla Group:

Physicochemical modeling of dissolution and stability of drug loaded soluble polymeric films

Biopharmaceutical Classification System (BCS) Class-II and Class-IV drugs (active pharmaceutical ingredients, APIs) have low aqueous solubility and potentially low bioavailability. To overcome the limitations, soluble polymeric drug dispersion is emerging as a feasible technique, where lab-scale tablet can be made by 3D printing. Film based solid dispersion of drug formulation can side-step and replace current legacy-based process design through iterative trial-and-error in pharmaceutical industries and facilitate a step-by-step highly scalable and rapidly implementable predictive physicochemical modeling based on drug release, storage stability and mechanical structure of the film. However, product design requirements need to be transformed to mathematical design instructions (dosage, release, stability, aesthetics, multiple APIs) for optimized tuning of the drug release rate, stabilization and dosage flexibility with continuous manufacturing to be predicted in advance. Predictive modeling is greatly simplified for a film-based approach that provide dimensional control by regulating transport and phase behavior to a 1D layer, thus streamlining manufacturing and scaling process. A mathematical modeling framework for the design and parameter optimization during the formulation of hydrophobic API-loaded soluble polymeric film formulations was implemented for the foundation for customer specific drug design in terms of dosage, release rate, storage stability (self-life) and mechanical properties (bending/cutting). Overall optimization initially involves two components: dissolution and stability models, which have to be solved simultaneously for targeted design requirements in terms of thickness, geometry, order, composition and number of layers.

PI: Thomas D Dziubla

Postdoc: M. Arif Khan

Student: Kelley Weigman

Collaborators:

Dr. J. Zach Hilt (Chemical and Materials Engineering),

Dr. J. Patrick Marsac (Pharmaceutical Sciences)

Software:

Matlab/Octave
FORTRAN
Python (Pyomo)

Funding: Eli Lilly

Publications:

Grants:

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