Accelerative Solid-State Oxidation Behaviour of Amorphous and Partially Crystalline Venetoclax.

There is a growing focus on solid-state degradation, especially for its relevance in understanding interactions with excipients. Performing a solid-state degradation of Venetoclax (VEN), we delve into VEN's stability in different solid-state oxidative stress conditions, utilizing Peroxydone™ complex and urea peroxide (UHP). The investigation extends beyond traditional forced degradation scenarios, providing insights into VEN's behavior over 32 h, considering temperature and crystallinity conditions. Distinct behaviors emerge in the cases of Peroxydone™ complex and UHP. The partially crystalline (PC-VEN) form proves more stable with Peroxydone™, while the amorphous form (A-VEN) shows enhanced stability with UHP. N-oxide VEN, a significant degradation product, varies between these cases, reflecting the impact of different oxidative stress conditions. Peroxydone™ complex demonstrates higher reproducibility and stability, making it a promising option for screening impurities in solid-state oxidative stress scenarios. This research not only contributes to the understanding of VEN's stability in solid-state but also aids formulators in anticipating excipient incompatibilities owing to presence of reactive impurities (peroxides) and oxidation in the final dosage form.

Theoretical and Experimental Investigation of Autoxidation Propensity of Selected Drugs in Solution State.

The C-H bond dissociation energy (BDE) of drug molecules is often used to estimate their relative propensities to undergo autoxidation. BDE calculations based on electronic structures provide a convenient means to estimate the risk for a given compound to degrade via autoxidation. This study aimed to verify the utility of calculated C-H BDEs of a range of drug molecules in predicting their autoxidation propensities, in the solution state. For the autoxidation study, 2,2'-azobis (2-methylpropionitrile) was employed as the solution state stressor, and the experimental reaction rate constants were determined employing ultraperformance liquid chromatographic (UPLC) methods. Reaction rates in the solution state were compared to the calculated C-H BDE values of the respective compounds. The results indicated a poor correlation for compounds in the solution state, and their relative stabilities could not be explained with C-H BDE. On the other hand, a favorable relationship was observed between the relative extent of ionization and the autoxidation rates of the selected compounds. In the solution state, factors such as the type and extent of drug ionization, degree and type of solvation have been shown to contribute to differences in reactivity. By applying the computational method involving the effect of H-atom abstraction and potential ionization sites in the molecule, the calculated C-H BDE should relate better to the experimental autoxidation rates.

Mechanoactivation as a Tool to Assess the Autoxidation Propensity of Amorphous Drugs.

Mechanoactivation has attracted considerable attention in the pharmaceutical sciences due to its ability to generate amorphous materials and solid-state synthetic products without the use of solvent. Although some studies have reported drug degradation during milling, no studies have systematically investigated the use of mechanoactivation in predicting drug degradation in the solid state. Thus, this work explores the autoxidation of drugs in the solid state by comilling amorphous mifepristone (MFP):polyvinylpyrrolidone vinyl acetate (PVPVA) and amorphous olanzapine (OLA):PVPVA. MFP was amorphized by ball milling and OLA by quench cooling techniques. Subsequently, comilling the amorphous drugs in the presence of a 10-fold weight ratio of PVPVA (the excipient containing reactive free radicals) was performed at several milling frequencies to identify the kinetics of mechano-autoxidation over milling durations. Overall, milling led to the degradation of up to 5% drug in the solid state. The autoxidation mechanism was confirmed by performing a stress study in the solution at 50 °C for 5 h, by using a 10 mM azo-bis(isobutyronitrile) (AIBN) as a stressing agent. By deconvoluting the effect of milling frequency and the energy on the extent and kinetics of milling-induced autoxidation of amorphous drugs, it was possible to fit an extended Arrhenius model that allowed extrapolation of mechanoactivated degradation rates (Km) to zero milling frequencies. Further, the autoxidation rates of drugs stored at high temperatures were observed to follow an Arrhenius behavior. A good degree of agreement was observed between the model predictions obtained by mechanoactivation (Km) to the reaction rates observed under accelerated temperatures. Additionally, the impact of adding an antioxidant (e.g., butylated hydroxytoluene) to the mixture during comilling was also examined. This study can be helpful in evaluating the stability of amorphous solids stored in accelerated (non-hermetic) conditions, in screening solid-state autoxidation propensity of drugs, and for the rational selection of antioxidants.

Influence of PLGA End Groups on the Release Profile of Dexamethasone from Ocular Implants.

The present study deals with the development of dexamethasone (DM)-loaded implants using ester end-capped Resomer RG 502 poly(lactic acid-co-glycolic acid) (PLGA) (502), acid end-capped Resomer RG 502H PLGA (502H), and a 502H:502 mixture (3:1) via hot melt extrusion (HME). The prepared intravitreal implants (20 and 40% DM loaded in each PLGA) were thoroughly investigated to determine the effect of different end-capped PLGA and drug loading on the long-term release profile of DM. The implants were characterized for solid-state active pharmaceutical ingredient (APIs) using DSC and SWAXS, water uptake during stability study, the crystal size of API in the implant matrix using hot-stage polarized light microscopy, and in vitro release profile. The kinetics of PLGA release was thoroughly investigated using quantitative 1H NMR spectroscopy. The polymorph of DM crystal was found to remain unchanged after the extrusion and stability study. However, around 3 times reduction in API particle size was observed after the HME process. The morphology and content uniformity of the RT-stored samples were found to be comparable to the initial implant samples. Interestingly, the samples (mainly 502H) stored at 40 °C and 75% RH for 30 d demonstrated marked deformation and a change in content uniformity. The rate of DM release was higher in the case of 502H samples with a higher drug loading (40% w/w). Furthermore, a simple digital in vitro DM release profile derived for the formulation containing a 3:1 ratio of 502H and 502 was comparable with the experimental release profile of the respective polymer mixture formulation. The temporal development of pores and/or voids in the course of drug dissolution, evaluated using µCT, was found to be a precursor for the PLGA release. Overall, the release profile of DM was found to be dependent on the PLGA type (independent of subtle changes in the formulation mass and diameter). However, the extent of release was found to be dependent on DM loading. Thus, the present investigation led to a thorough understanding of the physicochemical properties of different end-capped PLGAs and the underlying formulation microstructure on the release profile of a crystalline water-insoluble drug, DM, from the PLGA-based implant.

Impact of Different Saccharides on the In-Process Stability of a Protein Drug During Evaporative Drying: From Sessile Droplet Drying to Lab-Scale Spray Drying.

OBJECTIVES: Solid biopharmaceutical products can circumvent lower temperature storage and transport and increase remote access with lower carbon emissions and energy consumption. Saccharides are known stabilizers in a solid protein produced via lyophilization and spray drying (SD). Thus, it is essential to understand the interactions between saccharides and proteins and the stabilization mechanism. METHODS: A miniaturized single droplet drying (MD) method was developed to understand how different saccharides stabilize proteins during drying. We applied our MD to different aqueous saccharide-protein systems and transferred our findings to SD. RESULTS: The poly- and oligosaccharides tend to destabilize the protein during drying. The oligosaccharide, Hydroxypropyl ß-cyclodextrin (HPßCD) shows high aggregation at a high saccharide-to-protein molar ratio (S/P ratio) during MD, and the finding is supported by nanoDSF results. The polysaccharide, Dextran (DEX) leads to larger particles, whereas HPBCD leads to smaller particles. Furthermore, DEX is not able to stabilize the protein at higher S/P ratios either. In contrast, the disaccharide Trehalose Dihydrate (TD) does not increase or induce protein aggregation during the drying of the formulation. It can preserve the protein's secondary structure during drying, already at low concentrations. CONCLUSION: During the drying of S/P formulations containing the saccharides TD and DEX, the MD approach could anticipate the in-process (in) stability of protein X at laboratory-scale SD. In contrast, for the systems with HPßCD, the results obtained by SD were contradictory to MD. This underlines that depending on the drying operation, careful consideration needs to be applied to the selection of saccharides and their ratios.

Development of a Workflow to Engineer Tailored Microparticles Via Inkjet Printing.

PURPOSE: New drug development and delivery approaches result in an ever-increasing demand for tailored microparticles with defined sizes and structures. Inkjet printing technologies could be promising new processes to engineer particles with defined characteristics, as they are created to precisely deliver liquid droplets with high uniformity. METHODS: D-mannitol was used as a model compound alone or co-processed with the pore former agent ammonium bicarbonate, and the polymer polyethylene glycol 200. Firstly, a drop shape analyzer was used to characterize and understand ink/substrate interactions, evaporation, and solidification kinetics. Consequently, the process was transferred to a laboratory-scale inkjet printer and the resulting particles collected, characterized and compared to others obtained via an industrial standard technique. RESULTS: The droplet shape analysis allowed to understand how 3D structures are formed and helped define the formulation and process parameters for inkjet printing. By adjusting the drop number and process waveform, spherical particles with a mean size of approximately 100 µm were obtained. The addition of pore former and polymer allowed to tailor the crystallization kinetics, resulting in particles with a different surface (i.e., spike-like surface) and bulk (e.g. porous and non-porous) structure. CONCLUSION: The workflow described enabled the production of 3D structures via inkjet printing, demonstrating that this technique can be a promising approach to engineer microparticles.

Influence of Crystal Disorder on the Forced Oxidative Degradation of Vortioxetine HBr.

The present study investigates the impact of the solid-state disorder of vortioxetine hydrobromide (HBr) on oxidative degradation under accelerated conditions. A range of solid-state disorders was generated via cryogenic ball milling. The solid-state properties were evaluated by calorimetry, infrared-, and Raman spectroscopies. While salt disproportionation occurred upon milling, no chemical degradation occurred by milling. The amorphous fraction remained physically intact under ambient storage conditions. Subsequently, samples with representative disordered fractions were mixed with a solid oxidative stressor (PVP-H2O2 complex) and were compressed to compacts. The compacts were exposed to 40°C/75% RH for up to 6 h. The sample was periodically withdrawn and analyzed for the physical transformations and degradation. Two oxidative degradation products (DPs) were found to be formed, for which dissimilar relations to the degree of disorder and kinetics of formation were observed. The degradation rate of the major DP formation obtained by fitting the exponential model to the experimental data was found to increase up to a certain degree of disorder and decrease with a further increase in the disordered fraction. In contrast, the minor DP formation kinetics was found to increase monotonically with the increase in the disorder content. For the similar crystallinity level, the degradation trend (rate and extent) differed between the single-phase disorder generated by milling and physically mixed two-phase systems. Overall, the study demonstrates the importance of evaluating the physical and chemical (in)stabilities of the disordered solid state of a salt form of a drug substance, generated through mechano-activation.

Machine Learning-Enabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly Accessible Data.

An increasingly large dataset of pharmaceutics disciplines is frequently challenging to comprehend. Since machine learning needs high-quality data sets, the open-source dataset can be a place to start. This work presents a systematic method to choose representative subsamples from the existing research, along with an extensive set of quality measures and a visualization strategy. The preceding article (Muthudoss et al.. in AAPS PharmSciTech 23, 2022) describes a workflow for leveraging near infrared (NIR) spectroscopy to obtain reliable and robust data on pharmaceutical samples. This study describes the systematic and structured procedure for selecting subsamples from the historical data. We offer a wide range of in-depth quality measures, diagnostic tools, and visualization techniques. A real-world, well-researched NIR dataset was employed to demonstrate this approach. This open-source tablet dataset ( http://www.models.life.ku.dk/Tablets ) consists of different doses in milligrams, different shapes, and sizes of dosage forms, slots in tablets, three different manufacturing scales (lab, pilot, production), coating differences (coated vs uncoated), etc. This sample is appropriate; that is, the model was developed on one scale (in this research, the lab scale), and it can be great to investigate how well the top models are transferable when tested on new data like pilot-scale or production (full) scale. A literature review indicated that the PLS regression models outperform artificial neural network-multilayer perceptron (ANN-MLP). This work demonstrates the selection of appropriate hyperparameters and their impact on ANN-MLP model performance. The hyperparameter tuning approaches and performance with available references are discussed for the data under investigation. Model extension from lab-scale to pilot-scale/production scale is demonstrated. HIGHLIGHTS: • We present a comprehensive quality metrics and visualization strategy in selecting subsamples from the existing studies • A comprehensive assessment and workflow are demonstrated using historical real-world near-infrared (NIR) data sets • Selection of appropriate hyperparameters and their impact on artificial neural network-multilayer perceptron (ANN-MLP) model performance • The choice of hyperparameter tuning approaches and performance with available references are discussed for the data under investigation • Model extension from lab-scale to pilot-scale successfully demonstrated.

Machine Learning-Enabled NIR Spectroscopy. Part 3: Hyperparameter by Design (HyD) Based ANN-MLP Optimization, Model Generalizability, and Model Transferability.

Data variations, library changes, and poorly tuned hyperparameters can cause failures in data-driven modelling. In such scenarios, model drift, a gradual shift in model performance, can lead to inaccurate predictions. Monitoring and mitigating drift are vital to maintain model effectiveness. USFDA and ICH regulate pharmaceutical variation with scientific risk-based approaches. In this study, the hyperparameter optimization for the Artificial Neural Network Multilayer Perceptron (ANN-MLP) was investigated using open-source data. The design of experiments (DoE) approach in combination with target drift prediction and statistical process control (SPC) was employed to achieve this objective. First, pre-screening and optimization DoEs were conducted on lab-scale data, serving as internal validation data, to identify the design space and control space. The regression performance metrics were carefully monitored to ensure the right set of hyperparameters was selected, optimizing the modelling time and storage requirements. Before extending the analysis to external validation data, a drift analysis on the target variable was performed. This aimed to determine if the external data fell within the studied range or required retraining of the model. Although a drift was observed, the external data remained well within the range of the internal validation data. Subsequently, trend analysis and process monitoring for the mean absolute error of the active content were conducted. The combined use of DoE, drift analysis, and SPC enabled trend analysis, ensuring that both current and external validation data met acceptance criteria. Out-of-specification and process control limits were determined, providing valuable insights into the model's performance and overall reliability. This comprehensive approach allowed for robust hyperparameter optimization and effective management of model lifecycle, crucial in achieving accurate and dependable predictions in various real-world applications.

Assessment of Tribo-charging and Continuous Feeding Performance of Direct Compression Grades of Isomalt and Mannitol Powders.

Tribo-charging is often a root cause of mass flow deviations and powder adhesion during continuous feeding. Thus, it may critically impact product quality. In this study, we characterized the volumetric (split- and pre-blend) feeding behavior and process-induced charge of two direct compression grades of polyols, galenIQ™ 721 (G721) for isomalt and PEARLITOL® 200SD (P200SD) for mannitol, under different processing conditions. The feeding mass flow range and variability, hopper end fill level, and powder adhesion were profiled. The feeding-induced tribo-charging was measured using a Faraday cup. Both materials were comprehensively characterized for relevant powder properties, and their tribo-charging was investigated for its dependence on particle size and relative humidity. During split-feeding experiments, G721 showed a comparable feeding performance to P200SD with lower tribo-charging and adhesion to the screw outlet of the feeder. Depending on the processing condition, the charge density of G721 ranged from -0.01 up to -0.39 nC/g, and for P200SD from -3.19 up to -5.99 nC/g. Rather than differences in the particle size distribution of the two materials, their distinct surface and structural characteristics were found as the main factors affecting their tribo-charging. The good feeding performance of both polyol grades was also maintained during pre-blend feeding, where reduced tribo-charging and adhesion propensity was observed for P200SD (decreasing from -5.27 to -0.17 nC/g under the same feeding settings). Here, it is proposed that the mitigation of tribo-charging occurs due to a particle size-driven mechanism.

Insights into the Impact of Nanostructural Properties on Powder Tribocharging: The Case of Milled Salbutamol Sulfate.

The impact of the crystallinity of organic solid materials on their tribocharging propensity is well reported. However, no unequivocal explanation about the potential underlying mechanism(s) could be found so far in the literature. This study reports the effect that different degrees of crystalline disorder has on the tribocharging propensity of a small molecular organic material, salbutamol sulfate (SS). Ball-milling was used to induce structural transformations in the crystalline structure of SS. Particles with different nanostructures were produced and analyzed for their solid-state, particle properties, and tribocharging. It was found that differences in the amorphous content among the processed particles and related moisture levels had an impact on powder tribocharging. A correlation between the latter and the nanostructural properties of the particles was also established. The presence of interfaces between nanodomains of different densities and shorter average lengths within the phases seems to lead to a mitigation of charge. This suggests that undetected, subtle nanostructural differences of materials can affect powder handling and processability by altering their tribocharging. The present findings demonstrate the nanostructural implications of powder triboelectrification, which can help toward the rational design of a wide variety of organic solids.

Forced Solid-State Oxidation Studies of Nifedipine-PVP Amorphous Solid Dispersion.

In the present study, the oxidative degradation behavior of nifedipine (NIF) in amorphous solid dispersions (ASDs) prepared with poly(vinyl pyrrolidone) (PVP) with a short (K30) and a long (K90) chain length was investigated. The ASDs were prepared via dry ball-milling and analyzed using Fourier transform infrared (IR) spectroscopy, X-ray scattering, and differential scanning calorimetry. The ASDs were exposed to accelerated thermal-oxidative conditions using a pressurized oxygen headspace (120 °C for 1 day) and high temperatures at atmospheric pressure (60-120 °C for a period of 42 days). Additionally, solution-state oxidative degradation studies showed that pure NIF degrades to a greater extent than in the presence of PVP. Electronic structure calculations were performed to understand the impact of drug-polymer intermolecular interactions on the autoxidation of drugs. While no drug degradation was observed in freshly prepared ASD samples, alkyl free radicals were detected via electron paramagnetic resonance (EPR) spectroscopy. The free radicals were found to be consumed to a greater extent by PVP K30- than PVP K90-based ASDs upon exposure to high oxygen pressures. This was consistent with the greater solid-state oxidative degradation of NIF observed in ASDs with PVP K30 than with PVP K90. As no drug recrystallization occurred during this study period, the lower glass-transition temperature and presumed greater molecular mobility of PVP K30 and its ASD as compared to the PVP K90 system appear to contribute to the greater drug degradation in PVP-K30-based ASDs. The extent and the rate of oxidative degradation were higher in the case of PVP-K30-based ASD as compared to that in PVP-K90-based ASD, and the overall degradation increased with an increase in temperature. IR spectral analysis of drug-polymer interactions supports the electronic calculations of the oxidation process. We infer that, apart from the initial free radical content, the difference in the extent of drug-polymer intermolecular interactions in ASDs and amorphous stabilization during the forced oxidation experiments contribute to the observed differences in the autoxidative reactivity of the drug in ASDs with different PVP chain lengths. Overall, the chemical degradation of NIF in ASDs with two PVP chain lengths obtained from accelerated solid-state oxidation studies was in qualitative agreement with that obtained from long-term (3 years) storage under ambient conditions. The study highlights the ability of accelerated processes to determine the oxidative degradation behavior of polymeric ASDs and suggests that the polymer chain length could factor into chemical as well as physical stability considerations.

Phase Behavior of Drug-Lipid-Surfactant Ternary Systems toward Understanding the Annealing-Induced Change.

The present study systematically investigates the effect of annealing conditions and the Kolliphor P 407 content on the physicochemical and structural properties of Compritol (glyceryl behenate) and ternary systems prepared via melt cooling (Kolliphor P 407, Compritol, and a hydrophilic API) representing solid-lipid formulations. The physical properties of Compritol and the ternary systems with varying ratios of Compritol and Kolliphor P 407 were characterized using differential scanning calorimetry (DSC), small- and wide-angle X-ray scattering (SWAXS) and infrared (IR) spectroscopy, and hot-stage microscopy (HSM), before and after annealing. The change in the chemical profiles of different Compritol components as a function of annealing was evaluated using 1H NMR spectroscopy. While no change in the polymorphic form of API and Kolliphor P 407 occurred during annealing, a systematic conversion of the α- to ß-form was observed in the case of Compritol. Furthermore, the polymorphic transformation of Compritol was found to be dependent on the Kolliphor P 407 content. As per the Flory-Huggins mixing theory, higher miscibility was observed in the case of monobehenin-Kolliphor P 407, monobehenin-dibehenin, and dibehenin-tribehenin binary mixtures. The miscibility of Kolliphor P 407 with monobehenin and 1,2-dibehenin was confirmed by 1H NMR analysis. The observed higher miscibility of Kolliphor P 407 with monobehenin and 1,2-dibehenin is proposed as the trigger for the physical separation from the 1,3-diglyceride and triglycerides during melt solidification of the formulations. The phase separation is postulated as the mechanism underlying the formation of a stable ß-polymorphic form (a native form of 1,3-diglyceride) of Compritol upon annealing. This finding is expected to have an important implication for developing stable solid-lipid-surfactant-based drug formulations.

Impact of Extractables/Leachables from Filter Materials on the Stability of Protein-Based Pharmaceutical Products.

The manufacturing of biopharmaceutical drug solutions can involve close contact with various polymeric components, including common filter membranes. Potential leachable substances from filters may interact with the protein and thereby increase the structural damage and aggregation. The main aim of the study deals with the assessment of extractable and leachable (E/L) from different filters and the potential effect of E/Ls on protein (human granulocyte-colony stimulating factor (rh-GCSF) stability. The present study examines the E/L profile of five different polymeric filter membranes using various chromatographic techniques including LC-MS and GC-MS. In order to investigate their effect on protein stability, G-CSF (human granulocyte colony-stimulating factor) formulations were spiked with filter leachable stock solutions at two different pH levels. The spiked formulations were further analyzed with respect to their aggregation behavior. The results demonstrated a higher E/L content in the case of polyamide (PA), polycarbonate (PC), and polyethersulfone (PES) filters as compared to the polytetrafluoroethylene (PTFE) and regenerative cellulose (RC) filter materials. The E/L from RC and PES was found surface-active, whereas E/L from PA and RC significantly altered the particle size/structure resulting in the aggregation of proteins. Furthermore, bisphenol A was found to be one of the E/L substances from PC filters and can impose significant health problems when administered along with pharmaceutical products. The present study reports a qualitative rank ordering of the filter membranes in terms of their propensity to generate E/Ls and thus can be helpful in selecting a suitable membrane filter.

Continuous Processing of Micropellets via Hot-Melt Extrusion.

Microparticulate drug delivery systems, e.g., micropellets (MPs), are used in a variety of pharmaceutical formulations such as suspensions, injectable systems, and capsules. MPs are currently manufactured mainly via batch, solvent-based processes, e.g., spray-drying and solvent evaporation-extraction. In this paper, we present a novel, solvent-free, continuous hot-melt extrusion-based approach with an inline cold pelletization step and the potential of unprecedented on-the-fly formulation changes, aiming at producing the smallest particles usable for injectable applications. A biodegradable, crystalline dispersion consisting of poly(DL-lactic acid) (PLA) filled with metformin as the model drug was chosen on purpose to elucidate the broad applicability of the process also to formulations with limited stretchability and complex pelletizability. Next to optical/statistical particle analyses and in-line high-speed camera investigations providing insights into the pelletization process, the injectability of the most promising micropellets was compared to that of one marketed formulation. Fast extrudate haul-off speeds and high numbers of pelletizer knives resulted in particles with a narrow and small particle size distribution with a d50 below 270 µm and aspect ratios close to 1. To omit protruding drug particles to ensure sufficient extrudate stretchability and allow for the smallest MPs, it was found that the d90 of the embedded drug must be significantly below the extrudate diameter. Upon adapting the syringe diameter, the produced micropellets revealed similar injectability parameters to the marketed formulation, showcasing the potential that the proposed setup has for the manufacturing of novel microparticulate formulations.

Machine Learning-Enabled NIR Spectroscopy in Assessing Powder Blend Uniformity: Clear-Up Disparities and Biases Induced by Physical Artefacts.

NIR spectroscopy is a non-destructive characterization tool for the blend uniformity (BU) assessment. However, NIR spectra of powder blends often contain overlapping physical and chemical information of the samples. Deconvoluting the information related to chemical properties from that associated with the physical effects is one of the major objectives of this work. We achieve this aim in two ways. Firstly, we identified various sources of variability that might affect the BU results. Secondly, we leverage the machine learning-based sophisticated data analytics processes. To accomplish the aforementioned objectives, calibration samples of amlodipine as an active pharmaceutical ingredient (API) with the concentrations ranging between 67 and 133% w/w (dose ~ 3.6% w/w), in powder blends containing excipients, were prepared using a gravimetric approach and assessed using NIR spectroscopic analysis, followed by HPLC measurements. The bias in NIR results was investigated by employing data quality metrics (DQM) and bias-variance decomposition (BVD). To overcome the bias, the clustered regression (non-parametric and linear) was applied. We assessed the model's performance by employing the hold-out and k-fold internal cross-validation (CV). NIR-based blend homogeneity with low mean absolute error and an interval estimates of 0.674 (mean) ± 0.218 (standard deviation) w/w was established. Additionally, bootstrapping-based CV was leveraged as part of the NIR method lifecycle management that demonstrated the mean absolute error (MAE) of BU ± 3.5% w/w and BU ± 1.5% w/w for model generalizability and model transferability, respectively. A workflow integrating machine learning to NIR spectral analysis was established and implemented. Impact of various data learning approaches on NIR spectral data.

Analytical and Computational Methods for the Determination of Drug-Polymer Solubility and Miscibility.

In the pharmaceutical industry, poorly water-soluble drugs require enabling technologies to increase apparent solubility in the biological environment. Amorphous solid dispersion (ASD) has emerged as an attractive strategy that has been used to market more than 20 oral pharmaceutical products. The amorphous form is inherently unstable and exhibits phase separation and crystallization during shelf life storage. Polymers stabilize the amorphous drug by antiplasticization, reducing molecular mobility, reducing chemical potential of drug, and increasing glass transition temperature in ASD. Here, drug-polymer miscibility is an important contributor to the physical stability of ASDs. The current Review discusses the basics of drug-polymer interactions with the major focus on the methods for the evaluation of solubility and miscibility of the drug in the polymer. Methods for the evaluation of drug-polymer solubility and miscibility have been classified as thermal, spectroscopic, microscopic, solid-liquid equilibrium-based, rheological, and computational methods. Thermal methods have been commonly used to determine the solubility of the drug in the polymer, while other methods provide qualitative information about drug-polymer miscibility. Despite advancements, the majority of these methods are still inadequate to provide the value of drug-polymer miscibility at room temperature. There is still a need for methods that can accurately determine drug-polymer miscibility at pharmaceutically relevant temperatures.

Interplay of Aging and Lot-to-Lot Variability on the Physical and Chemical Properties of Excipients: A Case Study of Mono- and Diglycerides.

The present study investigates the chemical composition governing the physical properties of mono- and diglycerides (MDGs) at the microstructural level, as a function of aging and lot-to-lot variability. The physical structure of the MDG plays a vital role in ameliorating the emulsion stability and is widely explored in diverse research horizons related to the pharmaceutical, cosmetic, and food industries. In an effort to understand the mechanism of emulsion stabilization, physical properties were extensively evaluated in selective commercial lots to determine if there is a correlation between the chemical composition of MDG and physical properties. The solid state of the MDG samples with different aging profiles was characterized using X-ray scattering, differential scanning calorimetry, attenuated total reflection-Fourier transform infrared spectroscopy, and NMR relaxometry. Moreover, the kinetic aspect of solid-state transformation was also evaluated via treating MDG samples with a heat-cool cycle. The chemical composition of MDGs was quantified using a quantitative NMR (qNMR) method. Interestingly, the X-ray scattering results demonstrated a change in the MDG polymorphic form and an increase in the %ß content as a function of aging. The increase in the %ß content led to the formation of rigid crystal structures of MDG, as evident from the NMR relaxometry. Chemical quantification of isomeric composition revealed chemical composition change as a potentially critical factor responsible for the altered physical structures of MDG with respect to aging and lot-to-lot variability. The findings correlated the solid-state transformation with the change in the chemical composition of the MDG as a combined effect of aging and lot-to-lot variability. This work serves as a basis to better understand the interdependency of the physicochemical properties of MDG. Furthermore, the present work can also be used as guidance for setting up the specifications of MDG, as per the required polymorphic form for a multitude of applications.

Spray-Congealing and Wet-Sieving as Alternative Processes for Engineering of Inhalation Carrier Particles: Comparison of Surface Properties, Blending and In Vitro Performance.

PURPOSE: Traditionally, α-lactose monohydrate is the carrier of choice in dry powder inhaler (DPI) formulations. Nonetheless, other sugars, such as D-mannitol, have emerged as potential alternatives. Herein, we explored different particle engineering processes to produce D-mannitol carriers for inhaled delivery. METHODS: Wet-sieving and spray-congealing were employed as innovative techniques to evaluate the impact of engineering on the particle properties of D-mannitol. To that end, the resulting powders were characterized concerning their solid-state, micromeritics and flowability. Afterwards, the engineered carrier particles were blended with inhalable size beclomethasone dipropionate to form low dose (1 wt%) DPI formulations. The in vitro aerosolization performance was evaluated using the NEXThaler®, a reservoir multi-dose device. RESULTS: Wet-sieving generated D-mannitol particles with a narrow particle size distribution and spray-congealing free-flowing spherical particles. The more uniform pumice particles with deep voids and clefts of wet-sieved D-mannitol (Pearl300_WS) were beneficial to drug aerosolization, only when used in combination with a ternary agent (10 wt% of 'Preblend'). When compared to the starting material, the spray-congealed D-mannitol has shown to be promising in terms of the relative increase of the fine particle fraction of the drug (around 100%), when used without the addition of ternary agents. CONCLUSIONS: The wet-sieving process and the related aerosolization performance are strongly dependent on the topography and structure of the starting material. Spray-congealing, has shown to be a potential process for generating smooth spherical particles of D-mannitol that enhance the in vitro aerosolization performance in binary blends of the carrier with a low drug dose.

Development and Validation of a Stability-Indicating UPLC Method for the Determination of Hexoprenaline in Injectable Dosage Form Using AQbD Principles.

A novel and efficient stability-indicating, reverse phase ultra-performance liquid chromatographic (UPLC®) analytical method was developed and validated for the determination of hexoprenaline in an injectable dosage form. The development of the method was performed using analytical quality by design (AQbD) principles, which are aligned with the future requirements from the regulatory agencies using AQbD principles. The method was developed by assessing the impact of ion pairing, the chromatographic column, pH and gradient elution. The development was achieved with a Waters Acquity HSS T3 (50 × 2.1 mm i.d., 1.8 µm) column at ambient temperature, using sodium dihydrogen phosphate 5 mM + octane-1-sulphonic acid sodium salt 10 mM buffer pH 3.0 (Solution A) and acetonitrile (Solution B) as mobile phases in gradient elution (t = 0 min, 5% B; t = 1 min, 5% B; t = 5 min, 50% B; t = 7 min, 5% B; t = 10 min, 5% B) at a flow rate of 0.5 mL/min and UV detection of 280 nm. The linearity was proven for hexoprenaline over a concentration range of 3.50-6.50 µg/mL (R2 = 0.9998). Forced degradation studies were performed by subjecting the samples to hydrolytic (acid and base), oxidative, and thermal stress conditions. Standard solution stability was also performed. The proposed validated method was successfully used for the quantitative analysis of bulk, stability and injectable dosage form samples of the desired drug product. Using the AQbD principles, it is possible to generate methodologies with enhanced knowledge, which can eventually lead to a reduced regulatory risk, high quality data and lower operational costs.