We applied process analytical technologies to solve the problem of selectivity in the hydrogenation of 3-(2-chloroethyl)-9-hydroxy-2-methyl-4H-pyrido[1,2-a]pyrimidin-4-one monohydrochloride (1) to (±)3-(2-chloroethyl)-6,7,8,9-tetrahydro-9-hydroxy-2-methyl-4H-pyrido[1,2-a]pyrimidin-4-one monohydrochloride (2). We showed that both mid-IR and near-IR (NIR) were suitable for in-line analysis of the hydrogenation. We chose to use NIR in the production environment due to easier implementation. We developed a NIR model by correlation of NIR results with HPLC results for a laboratory-scale hydrogenation reactor, and we used production batch data to adjust and confirm this model.

In data-driven empirical or hybrid modeling, the experimental data influences the model parameters and thus also the model predictions. The experimental data has some variability due to measurement noise and due to the intrinsic stochastic nature of certain pharmaceutical processes such as aggregation or breakage. To use predictive models, it is imperative that the accuracy of the predictions is known. To this extent, various uncertainty propagation techniques applied to a predictive breakage population balance model are studied. Three uncertainty propagation techniques are studied: linearization, sigma point, and polynomial chaos. These are compared to the uncertainty obtained from Monte Carlo simulations. Linearization performs the worst in the given scenario, while sigma point and polynomial chaos methods have similar performance in terms of accuracy.

Air jet mills are ubiquitous breakage devices not only in the pharmaceutical industry, but also in food and the toner manufacturing industry. The popularity of air jet mills arises due to its self-classifying, non-contaminating, and non-degrading operation while also maintaining a narrow particle size distribution. A popular approach towards mathematically modelling comminution devices like the jet mill is the population balance model framework. Population balance model for breakage is a semi-empirical framework in which several parameters are estimated from the experimental data. In many cases the experimental data available is insufficient, or of bad quality to guarantee the estimation of unique parameters. Thus it is imperative to assess the identifiability of such models to ensure that the chosen model structure is identifiable, both structurally and practically. In this study, we analyse

Population balance models are routinely used for modeling particulate processes involving breakage, agglomeration, crystallisation, etc. In this study, a comparison between three different numerical solution strategies for breakage population balance models is presented. Results are obtained for the fixed pivot technique, moving pivot technique and the cell average technique. These techniques are first compared for models whose solutions are analytically available. The comparison shows that fixed pivot lacks the accuracy of both moving pivot and cell average at coarser grids. At finer grids, all the three solution strategies give similar errors. With increasing grid fineness, all the three methods converge to a grid independent solution. Moving pivot is computationally the most expensive methods, followed by the cell average and fixed pivot. These methods are then applied to a conical screen mill modelled by a continuous population balance equation. For all the discretizations considered, cell average computes a higher median particle size value than the fixed pivot and moving pivot.

&'%' Milling is an important step in pharmaceutical manufacturing as it not only determines the final formulation of the drug product, but also influences the bioavailability and dissolution rate of the active pharmaceutical ingredient (API). In this respect, the air jet mill (AJM) is most commonly used in the pharmaceutical industry as it is a non-contaminating and non-degrading self-classifying process capable of delivering narrow particle size distributions (PSD). Keeping the principles of Quality by Design in mind, the Critical Process Parameters (CPPs) of the AJM have been identified to be the pressures at the grinding nozzles, and the feed rate which affect the PSD, surface charge and the morphology of the product (i.e. the Critical Material Attributes (CMAs)). For the purpose of this research, the PSD is considered to be the only relevant CMA. A population balance based model is proposed to simulate the dynamics milling operation by utilizing the concept of breakage functions. This model agrees qualitatively with experimental observations of the air jet mill unit present at Janssen Pharmaceutica but further steps for model validation need to be carried out.