In the current study, we demonstrate a structured approach to downstream process development for spray dried amorphous solid dispersions. Direct compression is generally not suitable due to typically poor flow of spray dried powders in tablets. Roller compaction (RC) is therefore the method of choice to enable spray dried dispersion downstream processing. Here, a structured experimental design of RC process parameters was used. The objective was to identify process conditions that lead to improved powder flow without compromising tablet robustness. Ten blends were compacted using different process parameters, and subsequently compressed into tablets. The impact of process parameters on granules and tablet properties was analyzed. We demonstrate that compaction force, gap and mesh aperture have major impact on RC outcomes. A combination of large gap and low force was identified as optimum combination of RC process parameters leading to powder flow improvement that could guarantee low tablet weight variation and at the same prevented loss of blend compressibility.

The identification of feasible operating conditions during the early stages of bioprocess development is implemented frequently through High Throughput (HT) studies. These typically employ techniques based on regression analysis, such as Design of Experiments. In this work, an alternative approach, based on a previously developed variant of the Simplex algorithm, is compared to the conventional regression-based method for three experimental systems involving polishing chromatography and protein refolding. This Simplex algorithm variant was found to be more effective in identifying superior operating conditions, and in fact it reached the global optimum in most cases involving multiple optima. By contrast, the regression-based method often failed to reach the global optimum, and in many cases reached poor operating conditions. The Simplex-based method is further shown to be robust in dealing with noisy experimental data, and requires fewer experiments than regression-based methods to reach favorable operating conditions. The Simplex-variant also lends itself to the use of HT analytical methods, when they are available, which can assist in avoiding analytical bottlenecks. It is suggested that this Simplex-variant is ideally suited to rapid optimization in early-phase process development. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:404-419, 2016.