Samuel Kyeremateng
AbbVie Deutschland GmbH & Co. KG, Germany
Title: Optimizing early phase development of amorphous solid dispersion formulation thorough application of modeling tools
Biography
Biography: Samuel Kyeremateng
Abstract
Statement of the Problem: Amorphous Solid Dispersion (ASD) is an established formulation technique for improving the
bioavailability of poorly water-soluble Active Pharmaceutical Ingredients (APIs) by increasing solubility, wettability and
dissolution rate. Successful manufacturing of ASD formulation by Hot Melt Extrusion (HME) requires selection of e.g. the
right API load, excipients, and processing temperature. API load is also crucial in determining important quality attributes of
the drug product such as long term physical stability to ensure consistent product performance during its self-life. Identifying
the possible maximum drug load limit and excipients for HME feasibility and risk assessment, and long-term physical stability
of the manufactured ASD can be quite challenging whereby several extrusion trials are required in addition to prolonged
stability studies. Exploring the optimal design space during early phase of formulation development by this approach requires
significant amount of resources including API which may be limitedly available during this phase.
Methodology & Theoretical Orientation: As an API-sparing approach, novel empirical model and the rigorous thermodynamic
Perturbed Chain Statistically Associating Fluid Theory (PC-SAFT) were applied to model ASD phase diagram of several
formulations to effectively and quickly explore the design space to optimize formulation development. These were followed up
with HME manufacturing and long-term stability studies (up to 18 months) of the formulations under ICH conditions to verify
the model-predicted results. Several APIs and polymeric excipients including Soluplus, Copovidone, PVP, and HPMCAS were
used in the studies.
Findings: The modeling tools were found to be very suitable in estimating extrusion temperature required for generating
crystal-free ASD formulations as well as predicting their physical stability under different storage conditions, i.e., temperature
and relative humidity.
Conclusion & Significance: Recent advances in predictive ASD phase diagram modeling proved to be reliable tools for
excipient selection, HME temperature prediction, and designing ASD formulations for maximum drug load and physical
stability. Applying these tools enables successful ASD formulation optimization using less resources and materials.