A number of developments with powder processing services point to ways of reducing variability and improving merchandise quality in the pharmaceutical industry, it has been reported.
In a piece for PharmaManufacturing.com,
the online hub for Pharmaceutical Manufacturing Magazine, its contributing editor Dr Angelo DePalma talked about predictive models, PAT, and continuous processing could all help to drive standards in the sector.
He explained that dry powder blending is one of the least understood parts of pharma development, despite its widespread use.
"The uniqueness of each individual drug composition assures that no two blending processes can ever be identical," Dr DePalma said.
He explained how the unpredictable nature of powder blending has led engineers to try and explain in quantitative terms a platform that is often described empirically.
A team at Rutgers University, New Jersey, US, has found that agitating a mixture longer and faster will not always result in a homogeneous blend.
"Blending that appears uniform may degrade into turbulence, causing ingredients to separate into layers," Dr DePalma said of the study.
Led by engineering professors Benjamin Glasser and Troy Shinbrot, the team found that fine glass beads of differing sizes blended uniformly when on low mixing speeds, but formed into distinct layers as speed progressed.
"The researchers were able to identify patterns of granular motion that promoted layer formation and interfered with uniform mixing," Dr DePalma noted.
This pattern has been observed in the field of pollution control and meteorology but it is not as yet fully known how it will impact on powder mixing.
"We do not have predictable equations of transport or mixing that span the range of granular behaviours from load-bearing and solid-like to flowing and fluid-like," Professor Shinbrot was quoted as saying.
In powder blending, there are a range of factors, such as rule of thumb, particle sizes and experimentation that must be taken into account when developing modelling.
"If we could predict which regime would occur, we could design equipment and control blending processes with much more robustness and much less variability in outcome due to environmental factors like humidity, and material properties like particle size and cohesivity," Prof Shinbrot added.