We are passionate about high-quality science and engineering in our drug delivery research. We also believe that empirical approaches to drug delivery problems can increase the risk of process or product failure and often require additional API. That is why we use our deep understanding of science and engineering fundamentals to deliver formulations that minimize risk and resource requirements for our clients by focusing on the commercial approach from the start. We apply this strategic approach across the breadth of our offerings in formulation, process development, and scale-up to advance our clients’ best medicines to the clinic and to the patient.
Our model-based approach to formulation and experience in having formulated over 500 compounds enables us to select the best technology for our clients’ compounds at the beginning. We can deliver the appropriate, enabling formulation with as little as 100 milligrams of API in less than a few weeks time. We also know the importance of ensuring our technological concepts will transition into a robust, well-defined pharmaceutical formulation for manufacturing processes. As a result, we apply process development and optimization tools such as models, experimental protocols, knowledge of key control volumes, and associated physical situations to ensure our clients’ formulations can be commercialized.
Through our scientific approach to problem solving, we are able to save our clients’ time, money, and API and quickly advance best new medicines to the clinic, and ultimately to the patient. Contact us to discuss how we can partner to advance your best medicines and for more information on our approach, please see the following publications:
- Vodak, D.T., D.E. Dobry, D.T. Friesen, M.D. Reed, A.P. Gigliotti, P.J. Kuehl, and D.K. Lyon, “Dextran-Based Materials as Excipients in Engineered Particle Formulations: Tailoring Physical Properties to Optimize Performance, Manufacturability, and Safety,” RDD Europe 2011, Vol. 1, R.N. Dalby, P.R. Byron, J. Peart, J.D. Suman, and P.M. Young (eds). Virginia Commonwealth University, Richmond, Virginia (2011)125-134.
- Falk, R.F., I. Marizano, E. Kougoulos, and K. Girard, “Prediction of Agglomerate Type during Scale-Up of a Batch Crystallization Using Computational Fluid Dynamics Models,” Org. Proc. Res. Dev., 15:6(2011)1977-1304.
- Morgen, M.M. , C.J. Bloom, R.A. Beyerinck, A. Bello, W. Song, K. Wilkinson, R. Steenwyk, and S. Shamblin, “Polymeric Nanoparticles for Increased Oral Bioavailability and Rapid Absorption Using Celecoxib as a Model of a Low-Solubility, High-Permeability Drug,” Pharm. Res.29:2(2012)427-40.