Preventing Crystal Agglomeration of Pharmaceutical Crystals Using Temperature Cycling and a Novel Membrane Crystallization Procedure for Seed Crystal Generation
In this work, a novel membrane crystallization system was used to crystallize micro-sized seeds of piroxicam monohydrate by reverse antisolvent addition. Membrane crystallization seeds were compared with seeds produced by conventional antisolvent addition and polymorphic transformation of a fine powdered sample of piroxicam form I in water. The membrane crystallization process allowed for a consistent production of pure monohydrate crystals with narrow size distribution and without significant agglomeration. The seeds were grown in 350 g of 20:80 w/w acetone-water mixture. Different seeding loads were tested and temperature cycling was applied in order to avoid agglomeration of the growing crystals during the process. Focused beam reflectance measurement (FBRM); and particle vision and measurement (PVM) were used to monitor crystal growth; nucleation and agglomeration during the seeded experiments. Furthermore; Raman spectroscopy was used to monitor solute concentration and estimate the overall yield of the process. Membrane crystallization was proved to be the most convenient and consistent method to produce seeds of highly agglomerating compounds; which can be grown via cooling crystallization and temperature cycling.
Effects of operating conditions on agglomeration and habit of paracetamol crystals in anti-solvent crystallization
Abstract Effects of agitation speed and feeding rate on agglomeration and habit of paracetamol crystals in anti-solvent crystallization from water–acetone mixture are reported. Water is used as anti-solvent and is added in a semi-batch manner to a baffled 1-l crystallizer equipped with a marine-type impeller. A simple new method to characterize agglomeration degree has been proposed. Results show that agglomeration degree of crystals depends on particle size and elevated agitation reduces agglomeration degree of big particles. Particle mean size exhibits a maximum with increasing agitation intensity in the range of 200–600 rpm, which is explained from the perspective of anti-solvent dispersion and crystal agglomeration/disruption. Agglomeration degree of products deteriorates with increasing feeding rate ranging from 1 to 20 g/min due to enhanced nucleation. Crystal habit changes when feeding rate is altered, mainly in the faces of [0 0 1] and [1 1 0]. Focused beam reflectance measurement (FBRM) was used to monitor indirectly the particle size distribution in situ. The data demonstrated that FBRM may potentially be used as a tool to control crystallization process.
Uncertainties and error propagation in kinetic hard-modelling of spectroscopic data
A novel method is presented for the rigorous propagation of uncertainties in initial concentrations and in dosing rates into the errors in the rate constants fitted by multivariate kinetic hard-modelling of spectroscopic data using the Newton–Gauss–Levenberg/Marquardt optimisation algorithm. The method was successfully validated by Monte-Carlo sampling. The impact of the uncertainties in initial concentrations and in the dosing rate was quantified for simulated spectroscopic data based on a second and a formal third order rate law under batch and semi-batch conditions respectively. An important consequence of this study regarding optimum experimental design is the fact that the propagated error in a second order rate constant is minimal under exact stoichiometric conditions or when the reactant with the lowest associated uncertainty in its initial concentration is in a reasonable excess (pseudo first order conditions). As an experimental example, the reaction of benzophenone with phenylhydrazine in THF was investigated repeatedly (17 individual experiments) by UV–vis and mid-IR spectroscopy under the same semi-batch conditions, dosing the catalyst acetic acid. For all experiments and spectroscopic signals, reproducible formal third order rate constants were determined. Applying the proposed method of error propagation to any single experiment, it was possible to predict 80% (UV–vis) and 40% (mid-IR) of the observed standard deviation in the rate constants obtained from all experiments. The largest contribution to this predicted error in the rate constant could be assigned to the dosing rate. The proposed method of error propagation is flexible and can straightforwardly be extended to propagate other possible sources of error.