Assessment of Resonant Acoustic Mixing for Low-Dose Pharmaceutical Powder Blends.

Obtaining a homogeneous low-dose pharmaceutical powder blend without multi-step processing remains a challenge. One promising technology to address this risk is resonant acoustic mixing (RAM). In this study, the performance of a laboratory resonant acoustic mixer (LabRAM) was studied at low active pharmaceutical ingredient (API) concentrations (0.1-0.5% w/w), using three commercial grades of a model API (Acetaminophen) and diluents with varying physical properties. The performance was assessed by evaluating blend uniformity (BU) and capsule content uniformity (CU) as a function of mixing time. Overall, the LabRAM achieved acceptable BU in a single step even at 0.1% w/w drug loading. A reduction in API primary particle size led to improved mixing efficiency and uniformity. Moreover, the presence of surface cavities in the diluents used appeared to have led to improved uniformity. The results demonstrated that RAM could achieve uniform powder blends without multi-step processing, for low-dose formulations.

Structure and optoelectronic properties of helical pyridine-furan, pyridine-pyrrole and pyridine-thiophene oligomers.

Density functional theory based calculations have been carried out to systematically investigate the structural and optoelectronic properties of pyridine-furan, pyridine-pyrrole and pyridine-thiophene oligomers. Comparison of results obtained at B3LYP/6-31G(d) and B3LYP-D3/6-31G(d) levels of theories reveals that the inclusion of dispersion correction with the B3LYP functional has a major impact on ground state structures and stabilities of the most stable conformers, which are helical for our studied systems. Calculation of stabilization energies, gained due to non-bonding interaction between adjacent helical turns, shows that stabilities of helical oligomers increase with an increase in the chain length. Ground state dipole moment values of these helical oligomers fluctuate between a certain range and these values depend on the number of repeating units (n) and the number of repeating units needed to complete one helical turn (u) of a helix. To obtain vertical excitation energies, oscillator strengths and absorption spectra of each oligomer, time dependent density functional theory single point calculations were carried out at the B3LYP-D3/6-31G(d) level using optimized geometries obtained at the same level. The absorption spectrum of a helical oligomer is composed of multiple electronic transitions having significant oscillator strengths and the transition with the largest oscillator strength is blue shifted with an increase in the size of the oligomer. Furthermore, for the most important electronic transition (S0→ Sm) of oligomers with n > u, m increases with increasing n. For these helices, excitations involving molecular orbitals other than frontier molecular orbitals significantly contribute to major electronic transitions.

A new class of teraryl-based AIEgen for highly selective imaging of intracellular lipid droplets and its detection in advanced-stage human cervical cancer tissues.

Lipid droplets (LDs) have drawn much attention in recent years. They serve as the energy reservoir of cells and also play an important role in numerous physiological processes. Furthermore, LDs are found to be associated with several pathological conditions, including cancer and diabetes mellitus. Herein, we report a new class of teraryl-based donor-acceptor-appended aggregation-induced emission luminogen (AIEgen), 6a, for selective staining of intracellular LDs in in vitro live 3T3-L1 preadipocytes and the HeLa cancer cell line. In addition, AIEgen 6a was found to be capable of staining and quantifying the LD accumulation in the tissue sections of advanced-stage human cervical cancer patients. Unlike commercial LD staining dyes Nile Red, BODIPY and LipidTOX, AIEgen 6a showed a high Stokes shift (195 nm), a good fluorescence lifetime decay of 12.7 ns, and LD staining persisting for nearly two weeks.

SEM/EDX and Raman chemical imaging of pharmaceutical tablets: A comparison of tablet surface preparation and analysis methods.

A better understanding of a pharmaceutical tablet's microstructure has the potential to unlock the black box between material attributes, process parameters and the critical quality attributes. Microstructure determination requires measuring the spatial-, particle size-distributions (absolute and relative) of the ingredients, and the void space, which is the overt goal of chemical Imaging (CI). Reliable quantitative results can be obtained by imaging multiple layers per tablet, with each layer having a minimal surface roughness. This study utilized scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDX) and Raman chemical imaging (RCI) to provide a comparative discussion of results obtained when determining the microstructure of commercial zinc sulfate tablets, using three methods of tablet surface preparation: scoring & hand-fracturing, microtoming, and grating. A description of the working principles of the measurement and surface preparation methods is followed by a comparison of microstructure (particle size distribution and homogeneity of distribution) using chemical images. A comparison of the general advantages and disadvantages of SEM/EDX and RCI and the common errors in analyzing microstructure are also discussed. The results indicate that in addition to selecting the correct tablet surface preparation method, chemical imaging method, and the subsequent microstructural analyses method, correct problem formulation is also critical.

Multi-layer Raman chemical mapping to investigate the effect of API particle size and blending shear rate on API domain sizes in pharmaceutical tablets.

While macromixing (gross uniformity) has received a lot of attention in pharmaceutical powder blending, micromixing (particularly, particle-level aggregation) has been significantly less studied. This study investigated the impact of active pharmaceutical ingredient (API) particle size (D50: 11, 28, and 70 µm) and blending shear rate (low and high) that was caused by tumbling blending (specifically, a V-blender) on micro-mixing. The effect on micro-mixing (API domain sizes) was assessed in direct compression tablets using high-resolution Raman chemical mapping. Analyses of multiple layers within tablets enabled a more reliable understanding of the variability in API domain sizes with respect to the independent variables. The relationship between API domain sizes and the manufactured tablets' content uniformity (CU) was also investigated using near-infrared transmission spectroscopy. Generally, at low shear, as the API particle size decreased, the frequency and size of API agglomerates increased, resulting in poor CU. However, in all cases, API domain sizes drastically reduced at high shear, resulting in an acceptable CU. The results of this work clearly demonstrated the utility of a multi-layer, multi-tablet, and high-resolution Raman chemical mapping as an off-line process analytical technology (PAT) system, to enable quality-by-design driven formulation and process development.

Performance assessment of linear iterative optimization technology (IOT) for Raman chemical mapping of pharmaceutical tablets.

Raman chemical mapping is an inherently slow analysis tool. Accurate and robust multivariate analysis algorithms, which require least amount of time and effort in method development are desirable. Calibration-free regression and resolution approaches such as classical least squares (CLS) and multivariate curve resolution using alternating least squares (MCR-ALS), respectively, help in reducing the resources required for method development. However, conventional CLS does not consider appropriate constraints, which may result in negative and/or greater than 100 % Raman concentration scores, while MCR-ALS may not always be as accurate as regression-based algorithms. Linear iterative optimization technology (IOT) is another calibration-free algorithm, which with appropriate constraints has previously shown promise in online and offline pharmaceutical mixture composition determination. This paper aims to evaluate the performance of the linear IOT algorithm for Raman chemical mapping of the active pharmaceutical ingredient (API), diluent, and lubricant in pharmaceutical tablets. Two pre-processing strategies were applied to the raw Raman mapping spectra. The results were compared with CLS (current reference method) and MCR-ALS. Special emphasis was given to mapping at low Raman exposure times to enable feasible total acquisition times (< 5 h). The quality of IOT/CLS/MCR-ALS estimated Raman concentration predictions were assessed by calculating a correlation factor between the spectrum corresponding to the maximum predicted concentration (or resolved spectra) of a component for IOT/CLS (or MCR-ALS) and the pure powder component spectrum. The Raman chemical maps were visualized, and the average Raman concentrations scores were compared. The results demonstrated the utility of IOT in Raman chemical mapping of pharmaceutical tablets. The diluent (lactose) and API (semi-fine APAP) used in this study were reliably estimated by IOT at relatively short Raman exposure times. On the other hand, as expected, the lubricant (magnesium stearate) could not be detected in any of the cases investigated here, irrespective of the algorithm used. Overall, for the API and diluent used in this formulation as well as the chemical mapping conditions, linear IOT seemed to better estimate the pure spectrum intensities and the average Raman scores (closer to CLS) in comparison to MCR-ALS. Moreover, application of appropriate constraints in linear IOT avoided the presence of negative and/or greater than 100 % Raman concentration scores, as observed in CLS-based Raman chemical maps.

Using residence time distribution in pharmaceutical solid dose manufacturing - A critical review.

While continuous manufacturing (CM) of pharmaceutical solid-based drug products has been shown to be advantageous for improving the product quality and process efficiency in alignment with FDA's support of the quality-by-design paradigm (Lee, 2015; Ierapetritou et al., 2016; Plumb, 2005; Schaber, 2011), it is critical to enable full utilization of CM technology for robust production and commercialization (Schaber, 2011; Byrn, 2015). To do so, an important prerequisite is to obtain a detailed understanding of overall process characteristics to develop cost-effective and accurate predictive models for unit operations and process flowsheets. These models are utilized to predict product quality and maintain desired manufacturing efficiency (Ierapetritou et al., 2016). Residence time distribution (RTD) has been a widely used tool to characterize the extent of mixing in pharmaceutical unit operations (Vanhoorne, 2020; Rogers and Ierapetritou, 2015; Tezyk et al., 2015) and manufacturing lines and develop computationally cheap predictive models. These models developed using RTD have been demonstrated to be crucial for various flowsheet applications (Kruisz, 2017; Martinetz, 2018; Tian, 2021). Though extensively used in the literature (Gao et al., 2012), the implementation, execution, evaluation, and assessment of RTD studies has not been standardized by regulatory agencies and can thus lead to ambiguity regarding their accurate implementation. To address this issue and subsequently prevent unforeseen errors in RTD implementation, the presented article aims to aid in developing standardized guidelines through a detailed review and critical discussion of RTD studies in the pharmaceutical manufacturing literature. The review article is divided into two main sections - 1) determination of RTD including different steps for RTD evaluation including experimental approach, data acquisition and pre-treatment, RTD modeling, and RTD metrics and, 2) applications of RTD for solid dose manufacturing. Critical considerations, pertaining to the limitations of RTDs for solid dose manufacturing, are also examined along with a perspective discussion of future avenues of improvement.

Development of low dose micro-tablets by high shear wet granulation process.

Low dose micro-tablets with acceptable quality attributes, specifically content uniformity (CU), would not only enhance the dose flexibility in the clinic, but also decrease excipient burden in pediatric population. Considering the CU challenges associated with directly compressed low dose micro-tablets, in this study, high shear wet granulation (HSWG) process was evaluated to manufacture micro-tablets with reduced CU variability. The impact of active pharmaceutical ingredient (API) particle size (D90 - 18-180 µm) and loading (0.67-16.67% w/w) on the critical quality attributes of micro-tablets (1.2 and 1.5 mm) like weight variability, CU, and dissolution were evaluated. Experimental results showed that final blends with flow function coefficient (ffc) ≥ 5.4 or Hausner ratio (HR) ≤ 1.43 facilitated robust compression of micro-tablets. With enhanced weight control, all the batches except the 1.2 mm micro-tablets and 2.0 mm micro-tablets with 0.67% w/w API loading and coarse API particle size (D90 - 180 µm) resulted in CU variability that meets the USP <905> CU acceptance criteria for individual micro-tablets. Apart from the above mentioned 1.2 mm micro-tablets, all the batches meet the USP <905> CU acceptance criteria for composites of 10 or more micro-tablets. Precise delivery of micro-tablets manufactured in the current study would allow dose titration in the increments of 11 mcg. The API particle size and loading impacted the in-vitro dissolution performance of micro-tablets with smaller API particle size and lower loading resulting in faster release profiles. This study provides a framework for developing low dose micro-tablets with acceptable quality attributes using HSWG process for micro-dosing, enhanced dose flexibility, and decreased excipient burden.