Today, many drug molecules exhibit poor aqueous solubility and bioavailability. There is a need for innovative formulation approaches to improve their performance in drug therapy. Smart drug delivery systems require advanced analytical technology to assure their quality and safety but also to predict the clinical outcomes at an early stage in drug development.
“Who controls the past controls the future: who controls the present controls the past.”
– George Orwell –
First outlined by Joseph M. Juran, the concept of quality-by-design suggests continuous learning and development, creating products that meet the customer’s need. In the area of medicines, the efficacy and safety of drug products are closely related to their clinical performance. Consequently, we combine novel formulation technologies with highly advanced drug release models to identify critical quality attributes of drug delivery systems and to predict the in vivo pharmacokinetics.
The performance of drug products depends on a wide variety of parameters such as the drug release or the physical stability of the delivery system. Our team develops novel performance assays. The dispersion releaser (DR) technology was one of our first inventions and has been commercialized by Pharma Test. Focusing on oral and injectable drug delivery systems, we predict the performance based on in vitro data. This is how we gain better control of the formulation properties during early development.
Drug molecules often escape from blood circulation or pass physiological barriers such as the gastrointestinal wall or the blood-brain barrier. They are responsible for the therapeutic and toxicological effects of nanomedicines. The transition of the drug from the bounded to the un-bounded state is captured in the blood concentration-time profile. To identify the impact of drug release and degradation on the bioavailability of drugs in animals or humans, we apply in silico modeling techniques and smart data analysis. By accessing the preclinical and clinical data using state-of-the-art analytical techniques, we learn from the experiences of the past.
Building bridges between the past and the future, we use in vitro performance testing to retrodict clinical performances. Establishing in vitro-in vivo relationships is a way of using model-based learning to improve drug therapy.