Integrating Elastic Tensor and PC-SAFT Modeling with Systems-Based Pharma 4.0 Simulation, to Predict Process Operations and Product Specifications of Ternary Nanocrystalline Suspensions

Abstract

Comminution of BCS II APIs below the 1 μm threshold followed by solidification of the obtained nanosuspensions improves their dissolution properties. The breakage process reveals new crystal faces, thus creating altered crystal habits of improved wettability, facilitated by the adsorption of stabilizing polymers. However, process-induced transformations remain unpredictable, mirroring the current limitations of our atomistic level of understanding. Moreover, conventional equations of estimating dissolution, such as Noyes–Whitney and Nernst–Brunner, are not suitable to quantify the solubility enhancement due to the nanoparticle formation; hence, neither the complex stabilizer contribution nor the adsorption influence on the interfacial tension occurring between the water and APIs is accounted for. For such ternary mixtures, no numeric method exists to correlate the mechanical properties with the interfacial energy, capable of informing the key process parameters and the thermodynamic stability assessment of nanosuspensions. In this work, an elastic tensor analysis was performed to quantify the API stability during process implementation. Moreover, a novel thermodynamic model, described by the stabilizer-coated nanoparticle Gibbs energy anisotropic minimization, was structured to predict the material’s system solubility quantified by the application of PC-SAFT modeling. Comprehensively merging elastic tensor and PC-SAFT analysis into the systems-based Pharma 4.0 algorithm provided a validated, multi-level, built-in method capable of predicting the critical material quality attributes and corresponding key process parameters.

Pharma 4.0-Artificially Intelligent Digital Twins for Solidified Nanosuspensions

“…The contours below describe the final moisture content of the product decrease as the air’s temperature and/or its volumetric flow rate increases for the given initial dry humidity (g g −1 ). The air water capacity threshold rises proportionally with temperature when the temperature increases the air’s given humidity (g g −1 ) covering a lower proportion of the moisture threshold and its relative humidity decreases, allowing humidity absorption [ 7 ].…”

“…In our digital twin, the spray drying process is described as a multi-parametric block, since the final temperature and moisture content of the product depend on the drying air’s temperature, pressure, and capacity as far as the initial product’s flow, temperature, and droplet size distribution. Therefore, it can predict the drying efficiency given the air temperature specification, hence apart from the convergent mass and energy balances it exploits psychrometric calculations to determine the air’s relative humidity and its moisture capacity threshold [ 7 ], thus being advantageous in delivering realistic analysis reports.…”

“…In detail, the stabilizer’s addition generates a semi-solid interface that adds to the dissolution’s Gibbs energy decrease by GEE (J mol −1 ), according to Equations (1)–(3) [ 7 ]. …”

“…The obtained, coated, liquid crystals are further stabilized by spray drying solidification to allow for further processability. Taking into account the proven reliability and scalability of this method, we introduced novel thermodynamic models to calculate such composite material solubility by assessing the obtained stabilizer-coated nanoparticle Gibbs energy anisotropic minimization, quantified by the implementation of PC-SAFT interrogations coupled with elastic tensor analysis [ 7 ].…”

mRNA Therapeutic Modalities Design, Formulation and Manufacturing under Pharma 4.0 Principles

“…To this end Pharma 4.0 enabling tools of digital design such as spatial and charge arrangement formulation analysis, machine learning and systems-based simulations are empowering smart biomanufacturing strategies that pertain to unparalleled plant-wide quality assurance policies [ 43 ]. In addition, the thermodynamic stability and product performance of nanosuspensions may be predicted towards the assessment of solubility, predicting critical drug quality attributes linked to corresponding key process parameters also measured in real time by process analytical technology (PAT) [ 44 ].…”