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List of current projects
Sadowski Group
The bioavailability of an active pharmaceutical ingredient (API) is often limited by its poor water solubility, which is strongly influenced by pH and the presence of salts. This project develops an adequate model to predict the phase behavior of APIs in water and in (lipid-based) drug delivery systems.
Surfactants are used extensively in industrial and pharmaceutical applications, exploiting their effect on the aqueous solubility of hydrophobic compounds. This project aims at developing an aggregation model to be combined PC-SAFT allowing for predicting the formation of surfactant aggregates and their influence on the solubility of pharmaceutical ingredients.
Oil in water emulsions can effectively be used as delivery systems for poorly water soluble drugs. These emulsions are stabilized by surfactants. This project develops a suitable modeling approach for those systems utilizing an aggregation model and PC-SAFT. This will serve as a predictive method capable of describing the complex liquid-liquid phase equilibria in aqueous oil/surfactant solutions.
Many active pharmaceutical ingredients (APIs) suffer from low aqueous solubility, limiting their bioavailability. Bioavailability can be improved by dissolving the API in a polymer, yielding so-called amorphous solid dispersions (ASDs). This project aims at investigating the influence of coating materials, temperature and relative humidity (RH) on the stability of coated ASDs during storage.
The bioavailability of active pharmaceutical ingredients (API) is often limited by their low aqueous solubility. The API bioavailability can be improved by dissolving the API in a polymer matrix leading to so-called amorphous solid dispersions (ASDs). This project investigates ASDs using polymer salts as matrix formers. It is performed in close cooperation with the group of Lynne Taylor from Purdue University.
Brandenbusch group
When it comes to long-term stability of biopharmaceuticals, liquid dosage/storage forms occasionally reach their limits. Freeze-drying / Lyophilization is used to reduce the water content in the formulation. Within this project, we perform a thermodynamic characterization of the freeze-drying process and the investigate influence of additives on the stability and solubilization of the biopharmaceutical.
Process simulation plays a key role in improving or developing efficient and sustainable processes. Thermodynamic models (e.g. PC-SAFT, UNIQUAC) included in process simulators offer a detailed description of complex mixture properties. Within this project, we develop a predictive ML-approach to obtain required model parameters from data-driven methods of machine learning (ML).
Combining active pharmaceutical ingredients (API) and Polymers in amorphous solid dispersions (ASD) enhances aqueous solubility and release of new APIs. However, ASDs with higher drug load may release the API and Polymer incongruently related to amorphous-amorphous phase separation during dissolution. Ternary ASDs containing surfactants increase the drug load at which congruent release is achieved, the so-called ‘Limit of congruency’ (LoC).
Thermodynamic models are an essential part of today’s process development and optimization. Applications span across all fields and disciplines in the chemical, biotech and pharmaceutical industry. With the exception of ab-initio and purely predictive approaches, thermodynamic models in general require pure component and/or binary interaction parameters, fitted to experimental data.
Held group
The solvent and the type and amount of the catalyst strongly influence the equilibrium and kinetics of chemical reactions. The aim of this project is to predict the influence of strongly non-ideal solvent mixtures, the catalyst and the pH-value on the reaction equilibrium and kinetics of acid catalysed esterification reactions with ePC-SAFT.