Excipient class screenings based on intermolecular interaction predictions – a scientific way to decide between amorphous solid dispersions, co‑amorphous, lipid‑based or sugar‑based formulations.
Characterize molecule with few measurements in the lab (e.g. solubility in organic solvents)
Adjust physical model parameters to understand net intermolecular interactions of the molecule
Evaluate amorphous solid dispersions, lipid-based, and more for optimized results.
Early‑stage development requires clear, scientific decisions while conserving limited API. By combining classical analytics with PC‑SAFT predictions, amofor identifies stabilizing excipients and ranks potential enabling platforms, such as amorphous solid dispersions (ASDs), co‑amorphous systems, lipid‑based and sugar‑based formulations.
Which type of enabling formulation platform is the most promising based on the predicted intermolecular interactions? A classical ASD may be optimal — yet alternatives like co‑amorphous, lipid‑based, or sugar‑based systems can prove superior depending on the compound.
We start with tradition: solid‑state analytics, DSC, XRPD, solubility testing. Predictions from PC‑SAFT complement this work, guiding the shortlist of excipient classes. Ranking is then performed to establish which class offers the best stabilization for the compound at hand.
The comparative ranking illustrates how excipient classes differ in stabilizing effect: