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Teamwork, communication, and trust are as important as the technology.
October is a month of travels, from CPhI in Paris in the first week through the American Association of Pharmaceutical Scientists' (AAPS) annual meeting in San Antonio at its end. For today though, we're thinking about lessons learned during last month's suitcase-lugging. In particular, two talks, delivered almost back-to-back at September's AAPS conference, "Real World Applications of Process Analytical Technology and Quality by Design in Drug Process Development and Approval" (Arlington, VA, Sept. 11–12), seemed to define the new face of CGMPs.
One presentation showed how sophisticated mathematical tools and scientific rigor can speed process development, scale-up, and transfer. The other showed the importance of direct, open communication and trust.
Together, they're a potent mix.
Into the matrix
Students of physics learn to think not of objects and events but of vectors and transformations. The agent of the transformation is the tensor, the matrix multiplier, acting on a vector of state. When I first encountered this approach in Physics 10, I thought, "This is real beauty. This is what science should be."
Sadly for my esthetic sense, the real world is fiendishly complicated. That's probably why we learn from experience, rather than arriving in this world pre-programmed to figure out everything from first principles.
In his AAPS talk, "Using Mathematical Models to Optimize Consumer Products and Pharmaceuticals," chemical engineer and process modeler Michael L. Thompson, PhD, described how Procter & Gamble (West Chester, OH) has made the concepts of the vector of state and the transformation matrix actually work in the often disorderly world of consumer and pharmaceutical products manufacturing.
For example, an operation that mixes an active ingredient in aqueous solution with an organic polymer by combined agitation and stirring becomes a series of transformations: homogenization/emulsification, work, thickening, and so on.
Thompson described how his group develops mathematical models for real-world transformations. The method requires methodical experimental probing of the design space, a sort of extreme design of experiments, to correlate all of the process variables with the key process attributed.
Thompson described mathematical and computational approaches (from principal component analysis with varimax through Buckingham's pi theorem) that resolve the experimental data in to a matrix of dimensionless operators. This matrix, in turn, transforms the input state vector into an output vector that completely describes the effects of the unit process.
Though the effort required to build the models is substantial, Thompson described significant time- and money-saving advantages in transferring processes from pilot to commercial scale, and in moving processes from one production site to another.
In her following talk, "US FDA Experience Reviewing PAT Applications," Rebecca Rodriguez, an FDA Office or Regulatory Affairs national expert investigator, showed the other side of the future: the human elements are at least as important as finite elements in making science-based manufacturing work.
She described the experiences of one of FDA's first cross-department PAT teams as it evaluated a PAT application proposed as a change in an (unnamed) product already approved and manufactured.
Her report made concrete what FDA officials have said repeatedly (see "Re-Inventing FDA—A Mid-Course Report" in our August issue): Teamwork, communication, and trust are as important as the technology in making science-based manufacturing succeed.
Douglas McCormick is editor in chief of Pharmaceutical Technology, email@example.com