by Walter Strathy
Technical Consultant, Instigator
“Product development is more of an art than a science.”
“A formulation scientist is like a chef.”
These two phrases have been commonly heard in the past. But as pharmaceutical formulation scientists usher in a fresh era of quality metrics reporting and lean six-sigma quality improvement systems, we must embrace a paradigm shift. The days of empirically-led One Factor at a Time (OFAT) product and process development for drug delivery system development are over.
So much time, effort, and “good science” is spent on the discovery and development of a new active pharmaceutical ingredient (API). Then why is it when it comes time to formulate the API into a drug delivery system, more often than not science flies out the window?
The implementation of modern process engineering methods and the utilization of Quality by Design (QbD) tools ensure the development of a robust, repeatable, and reliable drug delivery system.
One of the most powerful tools at a formulation scientist’s disposal is “Design of Experiments” (DoE). When executed correctly, the product development scientist is able to relate multiple independent (input) variables to dependent (output) variables. Once a mathematical relationship is defined through the proper application of DoE, the relationship between process parameters and material attributes can be optimized in a given manufacturing space.
The term “garbage in, garbage out” was first coined in 1957 and is just as true now as it was then. When designing and developing a robust drug delivery system, one must understand the interactive relationships between all the input variables. In our heavily regulated environment out of specification results, quality assurance investigations and other adverse issues hurts our company’s bottom line.
It’s simple: good science is good business.