UNIVERSITY PARK, Pa. – Enrique del Castillo has been awarded $270,568 by the National Science Foundation to develop statistical methods that will improve the formulation and manufacturing of drugs used to treat some of the world’s deadliest diseases.
Del Castillo, distinguished professor of industrial engineering and professor of statistics, received the funds as part of his three-year research project titled, “High Dimensional Statistical Inference in Flexible Response Surface Models for Product Formulation.”
Over the last few decades, multicomponent drugs have proved beneficial in the treatment of some of the most severe of diseases, including various cancers and HIV/AIDS. Formulating these complex drugs requires research to determine not only the component proportions and their amounts (or doses), but also the manufacturing process conditions needed for the production of such formulas.
With the introduction of new regulations by the U.S. Food and Drug Administration, drug manufacturers seeking approval of a new product or process must provide a “design space” for that product; in other words, a set of specifications regarding formulation and process operating conditions that guarantees quality. How to determine such design space poses several challenges to the pharmaceutical industry.
In order to address these challenges, del Castillo is working to create new statistical methodology for determining optimal drug formulation and manufacturing conditions that maximize drug effectiveness. This research will be conducted in collaboration with statisticians at some of the largest pharmaceutical companies in the United States.
Beyond the pharmaceutical applications of this research, the new methods will be useful in the area of animal nutrition and evolutionary biology, given that diets have the same multicomponent form as a complex drug. They may also have implications for human nutrition and longevity studies. Del Castillo will collaborate with evolutionary biologists in the United Kingdom in this broader application of the statistical methods to be developed.