Research paperApplying surface energy derived cohesive–adhesive balance model in predicting the mixing, flow and compaction behaviour of interactive mixtures
Graphical abstract
Introduction
Flowability and compactibility are essential material attributes for efficient tablet manufacturing [1], [2], [3], [4]. However, the majority of APIs lack the flow and/or compactibility needed for direct tablet manufacturing [5]. Excipients (binders and flow additives) are incorporated to improve the compactibility and flow. Therefore, the success of tablet formulation critically depends on these excipients [6], [7].
Both flowability and compactibility depend on inter-particle forces [8]. In practice, flow additives improve flow by reducing inter-particle forces [9], while binders improve compactibility by increasing inter-particle forces [10]. Thus, from a fundamental perspective, flow additives and binders have opposite impacts on powder blends and would be expected to conflict with each other’s performance.
The concept of interactive mixing involves the adhesion of small particles (typically <10 μm) to larger particles resulting in formation of a homogeneous and segregation resistant powder mix [11]. The formation of interactive mixture depends on the magnitude of forces acting between the small and large particles. Efficient de-agglomeration and preferential adhesion of small particles to large particles is energetically favoured when the forces of adhesion acting between small and large particles are stronger than the forces of cohesion acting between the small particles [12], [13]. This concept is known as the cohesive–adhesive balance (CAB) [12], [13].
Glidants/flow additives are nanometric in size and improve the flow of cohesive particles by adhering to them consequently forming interactive mixtures [14], [15], [16]. However, due to their small size, most flow additives are highly cohesive in nature. Low shear mixing is unable to efficiently de-agglomerate these cohesive structures resulting in non-homogeneous mixtures and consequently poor flow [10], [17], [18], [19]. High shear mixing facilitates de-agglomeration and the formation of a more homogeneous interactive mixture, and consequently optimum flow improvement [15], [20], [21]. This suggests that the interactive mixing behaviour of small excipient particles affects the flow performance of the resulting interactive mixtures.
Theoretically, a monolayer of binder particles facilitates optimum gain in tensile strength [22], [23]. This is supported by percolation theory, which predicts that a three-dimensional continuous bonding network of the excipient must be present in order for the tablet to achieve optimal tensile strength [24], [25]. It has been demonstrated that small binder particles with the ability to form efficient interactive mixtures also express an efficient binder action [26]. This suggests that the cohesive adhesive balance of small excipient particles also affects the compaction behaviour of the resulting mixtures.
Clearly, both flow and compaction behaviour of blends depend on the dispersibility of small excipient particles. In this study, we used the cohesive–adhesive balance (CAB) model with surface energy-derived cohesion and adhesion data to predict the dispersibility and therefore the interactive mixing behaviour of small excipient particles with paracetamol. In addition, the applicability of CAB to predict the flow and compaction behaviour of the resultant blends was investigated. Small, micron-sized excipients (PVP spray-dried with l-leucine) were compacted into tablets whose tensile strengths were determined. Paracetamol was selected as a poorly compressible cohesive API model [27]. The surface energies of spray-dried excipients and paracetamol were determined using an inverse gas chromatography (IGC), and the cohesion–adhesion balance was derived from these surface energy data [28], [29]. The applicability of the CAB model to predict the dispersibility and therefore the interactive mixing behaviour of small excipient particles were then qualified by inspection of the API/excipient blends under a scanning electron microscope. Powder blends were then characterised for their tabletting behaviour and flow performance.
Section snippets
Materials and methods
In this study, we used previously prepared PVP (molecular weight ∼10 kDa, as per supplier’s specifications) and l-leucine spray-dried formulations [30]. The mean particle diameter (D50) of various spray-dried formulations was in the range of 2–3 μm with narrow particle size distributions. Paracetamol of analytical grade was procured from Sigma–Aldrich (St. Louis, MO, USA). The particle diameters of paracetamol were D10: 3.7 ± 0.1 μm, D50: 21.4 ± 0.3 μm, and D90: 151.5 ± 5.0 μm.
Compactibility – excipients
The compactibility of the spray-dried excipients was determined by compacting them alone and testing the tensile strength of the resulting tablets. PVP spray-dried with no l-leucine showed the highest tensile strength (Fig. 1). Incorporation of l-leucine reduced the tablet tensile strength indicating that l-leucine compromised the compactibility of the PVP. This may be attributed to the coating of PVP with l-leucine. l-Leucine is known as a low-bonding lubricant material [40]. The detrimental
Discussion
The concept of interactive mixtures has been shown to be effective in achieving uniform mixing of small dose APIs in powder blends where small particles adhere to the surface of large particles [49]. In addition, the gold standard flow additive silica has been shown to improve flow by adhering to large particles and forming interactive mixtures [10]. Thus, interactive mixing finds significant application in pharmaceutical tablet formulations. We have shown that a small binder particle excipient
Conclusion
In conclusion, the surface energy derived cohesive–adhesive balance (CAB) model can effectively predict the interactive mixing behaviour of small particles. This data could also effectively predict the compactibility and flow behaviour of resultant interactive mixtures at certain excipient proportions. Overall, this knowledge may help provide significant insight into the mixing, flow and compaction behaviour of interactive mixture, and thus create optimum interactive powder mixtures for tablet
Acknowledgements
Sharad Mangal is thankful to Monash Institute of Graduate Research (MIGR) for providing Monash Graduate Scholarship (MGS), Monash International Postgraduate Research Scholarship (MIPRS) and Postgraduate Publication Award for financial support. Authors would like to acknowledge Dr. Shyamal Das from University of Otago for his help.
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