Digital process design to define and deliver pharmaceutical particle attributes

<p>A digital-first approach to produce quality particles of an active pharmaceutical ingredient across crystallisation, washing and drying is presented, minimising material requirements and experimental burden during development. To demonstrate current predictive modelling capabilities, the production of two particle sizes (D₉₀ = 42 and 120 µm) <em>via</em> crystallisation was targeted to deliver a predicted, measurable difference in <em>in vitro</em> dissolution performance. A parameterised population balance model considering primary nucleation, secondary nucleation, and crystal growth was used to select the modes of production for the different particle size batches. Solubility prediction aided solvent selection steps which also considered manufacturability and safety selection criteria. A wet milling model was parameterised and used to successfully produce a 90 g product batch with a particle size D₉₀ of 49.3 µm, which was then used as the seeds for cooling crystallisation. A rigorous approach to minimising physical phenomena observed experimentally was implemented, successfully predicted the required conditions to produce material satisfying the particle size design objective of D₉₀ of 120 µm in a seeded cooling crystallisation using a 5-stage MSMPR cascade. Product material was isolated using the filtration and washing processes designed, producing 71.2 g of agglomerated product with a primary particle D₉₀ of 128 µm. Based on experimental observations, the population balance model was reparametrised to increase accuracy by inclusion of an agglomeration terms for the continuous cooling crystallisation. The dissolution performance for the two crystallised products is also demonstrated, and after 45 minutes 104.0 mg of the D₉₀ of 49.3 µm material had dissolved, compared with 90.5 mg of the agglomerated material with D₉₀ of 128 µm. Overall, 1513 g of the model compound was used to develop and demonstrate two laboratory scale manufacturing processes with specific particle size targets. This work highlights the challenges associated with a digitalfirst approach and limitations in current first-principles models are discussed that include dealing <em>ab initio</em> with encrustation, fouling or factors that affect dissolution other than particle size. </p>