A micro-XRT image analysis and machine learning methodology for the characterisation of multi- particulate capsule formulations

The application of X-ray microtomography for quantitative structural analysis of pharmaceutical multi-particulate systems was demonstrated for commercial capsules, each containing approximately 300 formulated ibuprofen pellets. The implementation of a marker-supported watershed transformation enabled the reliable segmentation of the pellet population for the 3D analysis of individual pellets. Isolated translation- and rotation-invariant object cross-sections expanded the applicability to additional 2D image analysis techniques. The full structural characterisation gave access to over 200 features quantifying aspects of the pellets' size, shape, porosity, surface and orientation. The extracted features were assessed using a ReliefF feature selection method and a supervised Support Vector Machine learning algorithm to build a model for the detection of broken pellets within each capsule. Data of three features from distinct structure-related categories were used to build classification models with an accuracy of more than 99.55% and a minimum precision of 86.20% validated with a test dataset of 886 pellets. This approach to extract quantitative information on particle quality attributes combined with advanced data analysis strategies has clear potential to directly inform manufacturing processes, accelerating development and optimisation

XRT : Extraction of quantitative structural descriptors from solid pharmaceutical products

In this project we demonstrate the use of x-ray tomography for the quantification of structural descriptors from two selected solid pharmaceutical products: single formulated particles and a commercial Ibuprofen capsule. In particular, we demonstrate the application of image processing strategies for noise reduction, image segmentation and the extraction of quantitative structural descriptors. Information on the sample’s solid state properties can be used to evaluate the manufacturing process and allows a prediction of the solid performance for subsequent processing steps or after administration to the patient

Relating induction time and metastable zone width

© 2017 The Royal Society of Chemistry. A relation between induction time and metastable zone width in cooling crystallization has been developed based on the correlation between temperature and supersaturation with the induction time in the classical nucleation theory. By this relation, the nucleation times in linear cooling experiments and the induction times at constant temperature can be estimated from each other, i.e. estimating metastable zone widths from experimental induction times or interfacial energy and the pre-exponential factor from metastable zone widths. Ascorbic-water system, with 120 induction times and 192 metastable zone widths determined, and several systems reported in the literature, have been investigated to compare the estimated values of metastable zone width/induction time with experimental values, respectively. The estimated metastable zone widths are fairly consistent with the experimental values. The differences between experimental literature values of metastable zone widths and the estimated values using the literature induction times range from 0.1 K to 10 K with an average of 2.5 K. For two systems (paracetamol in ethanol and salicylic acid in ethyl acetate), estimated and experimental results are of very good consistency with an average uncertainty of only about 5%. More accurate extrapolations of the induction times from metastable zone widths have been investigated. The potential utilities of this approach in crystallization research and process understanding are discussed

Carbamazepine on a carbamazepine monolayer forms unique 1D supramolecular assemblies

High-resolution STM imaging of the structures formed by carbamazepine molecules adsorbed onto a pseudo-ordered carbamazepine monolayer on Au(111) shows the formation of previously unreported 1-dimensional supramolecular assemblies

Inkjet printing of oral dosage forms to solubilize BCS Class II drugs

Oral drug delivery remains the preferred method of administration but BCS Class II drugs are not ideally suited to this due to their inherent poor solubility. Although a number of methods to increase solubility already exist, there is a need for less damaging methods of production which are more flexible to the needs of the patient. The innovative formulation method of inkjet printing has been suggested for this purpose as it has the capacity to produce highly precise dosing in a continuous manner. The Optomec Aerosol Jet 200 Printer utilised in the current study has never been used in pharmaceutical research before and it is highly interesting as it functions in a manner akin to a miniaturised spray dryer. Due to the low dose content of a single layer, formulations can be easily tailored to the patient’s individual requirements by changing the size and speed of deposition, utilising different nozzle sizes and layering to increase the overall dose. Raman spectroscopy, scanning electron microscopy and powder x-ray diffraction suggest that printing the drug alone results in a crystalline product. However, in the presence of a polymer it seems to form a less crystalline product suggesting the polymer is promoting solid dispersion formation in a similar manner to a spray dryer. Completely amorphous formulations are achieved on application of a premixed "ink" with a polymer content of 75% or more, allowing up to 25% drug loading. Drug release increases 10-fold on printing relative to a comparable powder blend and thus inkjet printing can be considered to be a viable method of improving the overall performance of the drug. The next steps will be to utilize this established methodology to produce innovative controlled release on a small scale

Crystal structure of the co-crystal butylparaben– isonicotinamide (1/1)

The title 1:1 co-crystal, C11H14O3·C6H6N2O [systematic name: butyl 4-hy­droxy­benzoate–isonicotinamide (1/1)], crystallizes with one mol­ecule of butyl­paraben (BPN) and one mol­ecule of isonicotinamide (ISN) in the asymmetric unit. In the crystal, BPN and ISN mol­ecules form hydrogen-bonded (O—H⋯N and N—H⋯O) dimers of paired BPN and ISN mol­ecules. These dimers are further connected to each other via N—H⋯O=C hydrogen bonds, creating ribbons in [011] which further stack along the a axis to form a layered structure with short C⋯C contacts of 3.285 (3) Å. Packing inter­actions within the crystal structure were assessed using PIXEL calculations

Inkjet printing oral dosage forms

The current study aims to establish an innovative method of effectively solubilising Biopharmaceutical Classification System Class II drugs using inkjet printing. Dosage forms have been produced using an Optomec AJ200 3D Inkjet printer. Printing with an appropriate polymer seems to result in an amorphous product, which will hopefully have a greater overall solubility

Prediction of powder flow of pharmaceutical materials from physical particle properties using machine learning

Understanding powder flow and how it affects pharmaceutical manufacturing process performance remains a significant challenge for industry. This work aims to improve decision making for manufacturing route selection, achieving the key goal of digital design within Industry 4.0 of being able to better predict properties whilst minimizing the amount of material required and time to inform process selection during early-stage development. A Machine Learning model approach is proposed to predict the flow properties of new materials from their physical properties. The model’s implementation will enhance manufacturing quality by taking advantage of the data generated throughout the manufacturing process

A predicted dimer-based polymorph of 10,11-dihydrocarbamazepine (Form IV)

A novel polymorph of 10,11-dihydrocarbamazepine (form IV), which had been predicted to be thermodynamically feasible, was obtained from the vapour phase and displays an R22(8) hydrogen bonded dimer motif in contrast to the catemeric motifs in forms I–III

Establishment of a continuous sonocrystallization process for lactose in an oscillatory baffled crystallizer

Crystallization at production scale (>10 kg) is typically a poorly understood unit operation with limited application of first-principles understanding of crystallization to routine design, optimization, and control. In this study, a systematic approach has been established to transfer an existing batch process enabling the implementation of a continuous process in an oscillatory baffled crystallizer (OBC) using ultrasound. Process analytical technology (PAT) was used to understand and monitor the process. Kinetic and thermodynamic parameters have been investigated for lactose sonocrystallization using focused beam reflectance measurement (FBRM) (Mettler Toledo) and mid-infrared spectroscopy (mid-IR) (ABB) in a multiorifice batch oscillatory baffled crystallizer (Batch-OBC). This platform provides an ideal mimic of the mixing, hydrodynamics and operating conditions of the continuous oscillatory flow crystallizer (COBC) while requiring only limited material. Full characterization of the hydrodynamics of the COBC was carried out to identify conditions that deliver plug-flow behavior with residence times of 1–5 h. The results show that continuous crystallization offers significant advantages in terms of process outcomes and operability, including particle size distribution (mean particle size <1500 μm) of alpha lactose monohydrate (ALM), as well as reduced cycle time (4 h compared to the 13–20 h in a batch process). Continuous sonocrystallization was performed for the first time at a throughput of 356 g·h–1 for 12–16 h. During the run at near plug flow, with supersaturation and controlled nucleation using sonication, no issues with fouling or agglomeration were observed. This approach has demonstrated the capability to provide close control of particle attributes at an industrially relevant scale