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 The compacts were exposed to 40°C/75% RH for up to 6 h. The sample was periodically withdrawn and analyzed for the physical transformations and degradation.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 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.

Investigation of the Impact of Saccharides on the Relative Activity of Trypsin and Catalase after Droplet and Spray Drying

While using saccharides as stabilizers for therapeutic protein drying is common, the mechanisms underlying the stabilization during drying remain largely unexplored. Herein, we investigated the effect of different saccharides, trehalose dihydrate (TD), dextran (DEX), and hydroxypropyl β-cyclodextrins (low substitution-HP and high substitution-HPB), on the relative activities of the enzymes trypsin and catalase during miniaturized drying (MD) or spray drying (SD). For trypsin, the presence of saccharides, especially HP, was beneficial, as it significantly improved the enzyme activity following MD. The HPB preserved trypsin's activity during MD and SD. Adding saccharides during MD did not show a notable improvement in catalase activities. Increasing TD was beneficial during the SD of catalase, as indicated by significantly increased activity. Molecular docking and molecular dynamics simulations oftrypsin with HP or HPB revealed the influence of their substitution on the binding affinity for the enzyme. A higher affinity of HP to bind trypsin and itself was observed during simulations. Experimentally, activity reduction was mainly observed during MD, attributable to the higher droplet temperature during MD than during SD. The activities from the experiments and aggregation propensity from molecular modeling helped elucidate the impact of the size of protein and saccharides on preserving the activity during drying.

Pancreatic lipase digestion: The forgotten barrier in oral administration of lipid-based delivery systems?

This review highlights the importance of controlling the digestion process of orally administered lipid-based delivery systems (LBDS) and their performance. Oral LBDS are prone to digestion via pancreatic lipase in the small intestine. Rapid or uncontrolled digestion may cause the loss of delivery system integrity, its structural changes, reduced solubilization capacity and physical stability issues. All these events can lead to uncontrolled drug release from the digested LBDS into the gastrointestinal environment, exposing the incorporated drug to precipitation or degradation by luminal proteases. To prevent this, the digestion rate of orally administered LBDS can be estimated by appropriate choice of the formulation type, excipient combinations and their ratios. In addition, in vitro digestion models like pH-stat are useful tools to evaluate the formulation digestion rate. Controlling digestion can be achieved by conventional lipase inhibitors like orlistat, sterically hindering of lipase adsorption on the delivery system surface with polyethylene glycol (PEG) chains, lipase desorption or saturation of the interface with surfactants as well as formulating LBDS with ester-free excipients. Recent in vivo studies demonstrated that digestion inhibition lead to altered pharmacokinetic profiles, where Cmax and Tmax were reduced in spite of same AUC compared to control or even improved oral bioavailability.

pH stimuli-responsive hydrogels from non-cellulosic biopolymers for drug delivery

Over the past several decades, there has been significant growth in the design and development of more efficient and advanced biomaterials based on non-cellulosic biological macromolecules. In this context, hydrogels based on stimuli-responsive non-cellulosic biological macromolecules have garnered significant attention because of their intrinsic physicochemical properties, biological characteristics, and sustainability. Due to their capacity to adapt to physiological pHs with rapid and reversible changes, several researchers have investigated pH-responsive-based non-cellulosic polymers from various materials. pH-responsive hydrogels release therapeutic substances in response to pH changes, providing tailored administration, fewer side effects, and improved treatment efficacy while reducing tissue damage. Because of these qualities, they have been shown to be useful in a wide variety of applications, including the administration of chemotherapeutic drugs, biological material, and natural components. The pH-sensitive biopolymers that are utilized most frequently include chitosan, alginate, hyaluronic acid, guar gum, and dextran. In this review article, the emphasis is placed on pH stimuli-responsive materials that are based on biological macromolecules for the purposes of drug administration.

Applying Material Science Principles to Chemical Stability: Modelling Solid State Autoxidation in Mifepristone Containing Different Degrees of Crystal Disorder

Ball-milling and harsh manufacturing processes often generate crystal disorder which have practical implications on the physical and chemical stabilities of solid drugs during subsequent storage, transport, and handling. The impact of the physical state of solid drugs, containing different degrees/levels of crystal disorder, on their autoxidative stability under storage has not been widely investigated. This study investigates the impact of differing degrees of crystal disorder on the autoxidation of Mifepristone (MFP) to develop a predictive (semi-empirical) stability model. Crystalline MFP was subjected to different durations of ambient ball milling, and the resulting disorder/ amorphous content was quantified using a partial least square (PLS) regression model based on Raman spectroscopy data. Samples of MFP milled to generate varying levels of disorder were subjected to a range of (accelerated) stability conditions, and periodically sampled to examine their recrystallization and degradation extents. Crystallinity was monitored by Raman spectroscopy, and the degradation was evaluated by liquid chromatography. The analyses of milled samples demonstrated a competition between recrystallization and degradation via autoxidation of MFP, to different extents depending on stability conditions/exposure time. The degradation kinetics were analyzed by accounting for the preceding amorphous content, and fitted with a diffusion model. An extended Arrhenius equation was used to predict the degradation of stored samples under long-term (25°C/60% RH) and accelerated (40°C/75% RH, 50°C/75% RH) stability conditions. This study highlights the utility of such a predictive stability model for identifying the autoxidative instability in non-crystalline/partially crystalline MFP, owing to the degradation of the amorphous phases. This study is particularly useful for identifying drug-product instability by leveraging the concept of material sciences.

On the influence of raw material attributes on process behaviour and product quality in a continuous WET granulation tableting line

Continuous manufacturing of oral solids is a complex process in which critical material attributes (CMAs), formulation and critical process parameters (CPPs) play a fundamental role. However, assessing their effect on the intermediate and final product's critical quality attributes (CQAs) remains challenging. The aim of this study was to tackle this shortcoming by evaluating the influence of raw material properties and formulation composition on the processability and quality of granules and tablets on a continuous manufacturing line. Powder-to-tablet manufacturing was performed using four formulations in various process settings. Pre-blends of different drug loadings (2.5 % w/w and 25% w/w) and two BCS classes (Class I and II) were continuously processed on an integrated process line ConsiGmaTM 25, including twin screw wet granulation, fluid bed drying, milling, sieving, in-line lubrication and tableting. The liquid-to-solid ratio and the granule drying time were varied to process granules under nominal, dry and wet conditions. It was shown that the BCS class and the drug dosage influenced the processability. Intermediate quality attributes, such as the loss on drying and the particle size distribution, directly correlated with the raw material's properties and process parameters. Process settings had a profound impact on the tablet's hardness, disintegration time, wettability and porosity.

Neutralizing Antibody Validation Testing and Reporting Harmonization

Evolving immunogenicity assay performance expectations and a lack of harmonized neutralizing antibody validation testing and reporting tools have resulted in significant time spent by health authorities and sponsors on resolving filing queries. A team of experts within the American Association of Pharmaceutical Scientists' Therapeutic Product Immunogenicity Community across industry and the Food and Drug Administration addressed challenges unique to cell-based and non-cell-based neutralizing antibody assays. Harmonization of validation expectations and data reporting will facilitate filings to health authorities and are described in this manuscript. This team provides validation testing and reporting strategies and tools for the following assessments: (1) format selection; (2) cut point; (3) assay acceptance criteria; (4) control precision; (5) sensitivity including positive control selection and performance tracking; (6) negative control selection; (7) selectivity/specificity including matrix interference, hemolysis, lipemia, bilirubin, concomitant medications, and structurally similar analytes; (8) drug tolerance; (9) target tolerance; (10) sample stability; and (11) assay robustness.

Development of a Digital Interface for Personalized Dosing in Renal Impaired Patients: A Case-Study Using the ACE-Inhibitor Benazepril

BACKGROUND

Personalized dosing regimens have great potential to improve the standard level of care from "one-fits-all" to the "right dose, to the right patient at the right time".

OBJECTIVES

Development of a digital interface that can inform healthcare professionals on the dosing of an ACE inhibitor on an individual basis.

METHODS

A physiologically based pharmacokinetic (PBPK) model and a one-compartment model were implemented for the prodrug benazepril and its metabolite benazeprilat, respectively. In sequence, to capture inter-individual differences the models were extended to a population based one (PopPBPK).

RESULTS

Both models predicted the pharmacokinetic data in the observed ranges. Application of the models help identify the factors influencing drug concentrations in the body and to find subgroups of patients, in which a dose adjustment is recommended, or a higher degree of caution is required.

CONCLUSION

The use of the models via a practical user interface can help inform clinical decisions and design optimal dosing based on the individual anthropometric characteristics and stage of renal impairment.

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 β-cyclodextrin (HPβCD) 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 HPβCD, 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.

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.

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.

Screening Autoxidation Propensities of Drugs in the Solid-State Using PVP and in the Solution State Using N-Methyl Pyrrolidone

Oxidative degradation of drugs is one of the major routes of drug substance and drug product instability. Among the diverse routes of oxidation, autoxidation is considered to be challenging to predict and control, potentially due to the multi-step mechanism involving free radicals. C–H bond dissociation energy (C–H BDE) is evidenced to be a calculated descriptor shown to predict drug autoxidation. While computational predictions for the autoxidation propensity of drugs are both swift and possible, no literature to date has highlighted the relationship between the computed C–H BDE and the experimentally-derived autoxidation propensities of solid drugs. The objective of this study is to investigate this missing relationship. The present work is an extension to the previously reported novel autoxidation approach that involves subjecting a physical mixture of pre-milled polyvinyl pyrrolidone (PVP) K-60 and a crystalline drug under high temperature and pressurized oxygen setup. The drug degradation was measured using chromatographic methods. An improved trend between the extent of solid autoxidation and C–H BDE could be observed after normalizing the effective surface area of drugs in the crystalline state, pointing to a positive relationship. Additional studies were conducted by dissolving the drug in N-methyl pyrrolidone (NMP) and exposing the solution under a pressurized oxygen setup at diverse elevated temperatures. Chromatographic results of these samples indicated a similarity in the formed degradation products to the solid-state experiments pointing to the utility of NMP, a PVP monomer surrogate, as a stressing agent for faster and relevant autoxidation screening of drugs in formulations.

Role of Crystal Disorder and Mechanoactivation in Solid-State Stability of Pharmaceuticals

Common energy-intensive processes applied in oral solid dosage development, such as milling, sieving, blending, compaction, etc. generate particles with surface and bulk crystal disorder. An intriguing aspect of the generated crystal disorder is its evolution and repercussion on the physical- and chemical stabilities of drugs. In this review, we firstly examine the existing literature on crystal disorder and its implications on solid-state stability of pharmaceuticals. Secondly, we discuss the key aspects related to the generation and evolution of crystal disorder, dynamics of the disordered/amorphous phase, analytical techniques to measure/quantify them, and approaches to model the disordering propensity from first principles. The main objective of this compilation is to provide special impetus to predict or model the chemical degradation(s) resulting from processing-induced manifestation in bulk solid manufacturing. Finally, a generic workflow is proposed that can be useful to investigate the relevance of crystal disorder on the degradation of pharmaceuticals during stability studies. The present review will cater to the requirements for developing physically- and chemically stable drugs, thereby enabling early and rational decision-making during candidate screening and in assessing degradation risks associated with formulations and processing.

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 (K_m) 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 (K_m) 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.

Temperature cycling-induced formation of crystalline coatings

The surface of particles is the hotspot of interaction with their environment and is therefore a major target for particle engineering. Particles with tailored coatings are greatly desired for a range of different applications. Amorphous coatings applied via film coating or microencapsulation have frequently been described in the pharmaceutical context and usually result in homogeneous surfaces. In the present study we have been exploring the feasibility of coating core particles with crystalline substances, a matter that has rarely been investigated. The expansion of the range of possible coating materials to include small organic molecules enables completely new product properties to be achieved. We present an approach based on temperature cycles performed in a tubular crystallizer to result in engineered crystalline coatings on excipient core particles. By manipulating the process settings and by the choice of coating substance we are able to tailor surface roughness, topography as well as surface chemistry. Benefits of our approach are demonstrated by using resulting particles as carriers in dry-powder-inhaler formulations. Depending on the resulting surface chemistry and surface roughness, coated carrier particles show varying fitness for delivering the model API salbutamol sulphate to the lung.

Trends in oral small-molecule drug discovery and product development based on product launches before and after the Rule of Five

In 1997, the 'Rule of Five' (Ro5) suggested physicochemical limitations for orally administered drugs, based on the analysis of chemical libraries from the early 1990s. In this review, we report on the trends in oral drug product development by analyzing products launched between 1994 and 1997 and between 2013 and 2019. Our analysis confirmed that most new oral drugs are within the Ro5 descriptors; however, the number of new drug products of drugs with molecular weight (MW) and calculated partition coefficient (clogP) beyond the Ro5 has slightly increased. Analysis revealed that there is no single scientific or technological reason for this trend, but that it likely results from incremental advances are being made in molecular biology, target diversity, drug design, medicinal chemistry, predictive modeling, drug metabolism and pharmacokinetics, and drug delivery.

Pharmaceutical hot melt extrusion process development using QbD and digital twins

Pharmaceutical product development guided by Quality by Design (QbD) is based on a complete understanding of the critical process parameters (CPPs) that are important for achieving the desired product critical quality attributes (CQAs). The effect of process settings, such as the screw speed, the throughput, the barrel temperature, and the screw configuration, is a well-known factor in the setup of pharmaceutical hot melt extrusion (HME) processes. A CPP that has not yet been extensively researched is the type of cross-section geometry of the screw elements. Typically, pharmaceutical extruders have double-flighted screw cross-sections, with some elements having a single- or triple-flighted element section. The exception is a NANO16 extruder from Leistritz, with all screw elements having a triple-flighted screw geometry. We investigated the process setup and scale-up to a double-flighted extruder experimentally and in silico via a digital twin. Two formulations were processed on a NANO16 extruder and virtually transferred to a ZSE18 double-flighted co-rotating twin-screw extruder. Detailed smoothed particle hydrodynamics simulations of all screw elements available from both extruders were performed, and their efficiency in conveying, pressure build-up, and power consumption were studied. Reduced-order 1D HME simulations, which were carried out to investigate the process space and scalability of both extruders, were experimentally validated.

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.

The Impact of the Water Evaporation Rate and Saccharide Excipients on the Oxidative Degradation of Polysorbates During Oven Drying and Spray Drying

In recent years, many fast drying techniques such as spray-drying are being explored as alternatives to biopharmaceutical freeze-drying. Thus, it is essential to understand how the processability of commonly used excipients will be affected when these new techniques are employed. This study reports a series of observations outlining how the thermally-induced oxidative degradation of polysorbates (PS) evolves in liquid to solid transitions, such as those expected in spray-drying. Firstly, the impact of different evaporation rates on the oxidative degradation of aqueous solutions of two different PS types namely, PS20 and PS80, were screened via evaporative solvent casting. The latter revealed that the evaporation rate could critically impact the rate-limiting steps of PS thermal oxidation. In addition, the potential of saccharides as excipients to mitigate the thermal oxidation of PS80 under slow and fast evaporation conditions was investigated. Five different saccharide excipients were screened, i.e., trehalose dihydrate, maltodextrin, hydroxypropyl-β-cyclodextrin, and Dextran 40. Under slow evaporation conditions, only trehalose dihydrate seemed to be beneficial in avoiding the thermal oxidation of PS80. For fast evaporation conditions, hydroxypropyl-β-cyclodextrin prevented the oxidative degradation of PS80. This implies that distinct strategies to mitigate PS oxidative degradation might be necessary depending on the drying process and rates.

Metastatic adenocarcinoma of the prostate presenting as a solitary cystic brain mass

Carcinoma prostate is the second most common cancer in men after skin cancer. It is the most common visceral malignancy in the United States of America. Like any other cancerous lesion, it has the propensity to metastasize to any part of the body; the most common locations being bones, lymph nodes, liver, and thoracic organs. However, it rarely metastasizes to the brain. It is even rarer for brain metastases to manifest as cystic lesions. We describe an unusual case of a metastatic prostate carcinoma presenting as a cystic brain mass.

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.

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.

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.

Lipid-based solubilization technology via hot melt extrusion: promises and challenges

INTRODUCTION

Self-emulsifying drug delivery systems (SEDDS) are a promising strategy to improve the oral bioavailability of poorly water-soluble drugs (PWSD). The excipients of SEDDS enable permeation through the mucus and gastro-intestinal barrier, inhibiting efflux transporters (e.g. P-glycoprotein) of drugs. Poor drug loading capacity and formulation instability are the main setbacks of traditional SEDDS. The use of polymeric precipitation inhibitors was shown to create supersaturable SEDDS with increased drug payload, and their solidification can help to overcome the instability challenge. As an alternative to several existing SEDDS solidification technologies, hot melt extrusion (HME) holds the potential for lean and continuous manufacturing of supersaturable solid-SEDDS. Despite being ubiquitously applied in solid lipid and polymeric processing, HME has not yet been widely considered for the preparation of SEDDS.

AREAS COVERED

The review begins with the rationale why SEDDS as the preferred lipid-based delivery systems (LBDS) is suitable for the oral delivery of PWSD and discusses the common barriers to oral administration. The potential of LBDS to surmount them is discussed. SEDDS as the flagship of LBDS for PWSD is proposed with a special emphasis on solid-SEDDS. Finally, the opportunities and challenges of HME from the lipid-based excipient (LBE) processing and product performance standpoint are highlighted.

EXPERT OPINION

HME can be a continuous, solvent-free, cost-effective, and scalable technology for manufacturing solid supersaturable SEDDS. Several critical formulations and process parameters in successfully preparing SEDDS via HME are identified.

Data Analytics and Artificial Intelligence in the Complex Environment of Megaprojects: Implications for Practitioners and Project Organizing Theory

This article articulates the prospect of improving megaproject execution and performance via digital project delivery. Various digitalization options, such as cloud computing, automation, artificial intelligence, information modeling, and data analytics and their recent usage in megaprojects, are critically reviewed. Prospective future developments and forthcoming challenges of digitalization in megaprojects have also been identified based on the current progress of these technologies. In terms of theory, we suggest information economics and organizational economics as a starting place to develop a research approach to artificial intelligence and megaprojects.

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.

Search for an Excess of Electron Neutrino Interactions in MicroBooNE Using Multiple Final-State Topologies

We present a measurement of ν_{e} interactions from the Fermilab Booster Neutrino Beam using the MicroBooNE liquid argon time projection chamber to address the nature of the excess of low energy interactions observed by the MiniBooNE Collaboration. Three independent ν_{e} searches are performed across multiple single electron final states, including an exclusive search for two-body scattering events with a single proton, a semi-inclusive search for pionless events, and a fully inclusive search for events containing all hadronic final states. With differing signal topologies, statistics, backgrounds, reconstruction algorithms, and analysis approaches, the results are found to be either consistent with or modestly lower than the nominal ν_{e} rate expectations from the Booster Neutrino Beam and no excess of ν_{e} events is observed.

Rational and practical considerations to guide a Target Product Profile for patient-centric drug product development with measurable patient outcomes - A proposed roadmap

The increasing awareness of acceptability and usability of pharmaceutical drug products by the patient as a key quality requirement continues to drive need for integrating patient centric drug product design into the pharmaceutical development process. The complex matrix of multiple drug product related decisions during the early drug development process often limits patient-centric drug product (PCDP) design options in the final commercial drug product development phase. To integrate the specific needs and perspectives of patients into drug development and product design process, a rational approach integrated into the complex development matrix is required from the start and weighs product development decision options accordingly. The aim of this work was to develop a roadmap for PCDP design in a multidisciplinary approach that leads to better usability, adherence and acceptance of the drug by patients via early integration into the development matrix. The proposed rational approach is based upon regulatory requirements and lessons learned from pediatric and geriatric drug development.

Assessment of Diverse Solid−State Accelerated Autoxidation Methods for Droperidol

The present study aimed to investigate methods for accelerating autoxidation of crystalline drugs in the solid-state that can potentially predict real−time stability. Solid droperidol (DPD) was selected as the model drug. A common free−radical initiator, 2,2′−azobisisobutyronitrile (AIBN), was used to induce autoxidation in solutions. AIBN decomposes at elevated temperatures to yield carbon−centred cyano−isopropyl free radicals that can auto−oxidize neighboring drug molecules. Although the reaction of AIBN is relatively straightforward in solution, it is less so in solids. In this study, we used solid AIBN mixed with DPD powder in the presence and absence of pressurized oxygen headspace. Samples were prepared directly in the form of binary mixtures with DPD and additionally in the form of powder compact/pellet with DPD. The main challenge in carrying out the reaction was related to the preservation of AIBN at elevated temperatures due to the disintegration of the pellet containing the latter. A commercially available free−radical coated silica particle (i.e., 2,2,6,6−tetramethyl−1−piperinyloxy (TEMPO) or (SiliaCAT^TM TEMPO)) was tested as a potential stressor, but with limited success to induce autoxidation. The most valuable results were obtained when a physical mixture of pre−milled PVP K−60 containing free radicals and DPD was exposed to elevated oxygen−temperature conditions, which yielded significant degradation of DPD. The study highlights the practical challenges for conducting accelerated solid−state stress studies to assess the autoxidation susceptibility of drugs using traditional free−radical initiators and presents a proof of application of milled PVP with free−radical as a potential alternative.

First Measurement of Energy-Dependent Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector

We report a measurement of the energy-dependent total charged-current cross section σ(E_{ν}) for inclusive muon neutrinos scattering on argon, as well as measurements of flux-averaged differential cross sections as a function of muon energy and hadronic energy transfer (ν). Data corresponding to 5.3×10^{19} protons on target of exposure were collected using the MicroBooNE liquid argon time projection chamber located in the Fermilab booster neutrino beam with a mean neutrino energy of approximately 0.8 GeV. The mapping between the true neutrino energy E_{ν} and reconstructed neutrino energy E_{ν}^{rec} and between the energy transfer ν and reconstructed hadronic energy E_{had}^{rec} are validated by comparing the data and Monte Carlo (MC) predictions. In particular, the modeling of the missing hadronic energy and its associated uncertainties are verified by a new method that compares the E_{had}^{rec} distributions between data and a MC prediction after constraining the reconstructed muon kinematic distributions, energy, and polar angle to those of data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well modeled and underpins first-time measurements of both the total cross section σ(E_{ν}) and the differential cross section dσ/dν on argon.

Search for Neutrino-Induced Neutral-Current Δ Radiative Decay in MicroBooNE and a First Test of the MiniBooNE Low Energy Excess under a Single-Photon Hypothesis

We report results from a search for neutrino-induced neutral current (NC) resonant Δ(1232) baryon production followed by Δ radiative decay, with a ⟨0.8⟩  GeV neutrino beam. Data corresponding to MicroBooNE's first three years of operations (6.80×10^{20} protons on target) are used to select single-photon events with one or zero protons and without charged leptons in the final state (1γ1p and 1γ0p, respectively). The background is constrained via an in situ high-purity measurement of NC π^{0} events, made possible via dedicated 2γ1p and 2γ0p selections. A total of 16 and 153 events are observed for the 1γ1p and 1γ0p selections, respectively, compared to a constrained background prediction of 20.5±3.65(syst) and 145.1±13.8(syst) events. The data lead to a bound on an anomalous enhancement of the normalization of NC Δ radiative decay of less than 2.3 times the predicted nominal rate for this process at the 90% confidence level (C.L.). The measurement disfavors a candidate photon interpretation of the MiniBooNE low-energy excess as a factor of 3.18 times the nominal NC Δ radiative decay rate at the 94.8% C.L., in favor of the nominal prediction, and represents a greater than 50-fold improvement over the world's best limit on single-photon production in NC interactions in the sub-GeV neutrino energy range.

Focusing on powder processing in dry powder inhalation product development, manufacturing and performance

Dry powder inhalers (DPI) are well established products for the delivery of actives via the pulmonary route. Various DPI products are marketed or developed for the treatment of local lung diseases such as chronic obstructive pulmonary disease (COPD), asthma or cystic fibrosis as well as systemic diseases targeted through inhaled delivery (i.e. Diabetes Mellitus). One of the key prerequisites of DPI formulations is that the aerodynamic size of the drug particles needs to be below 5 µm to enter deeply into the respiratory tract. These inherently cohesive inhalable size particles are either formulated as adhesive mixture with coarse carrier particles like lactose called carrier-based DPI or are formulated as free-flowing carrier-free particles (e.g. soft agglomerates, large hollow particles). In either case, it is common practice that drug and/or excipient particles of DPI formulations are obtained by processing API and API/excipients. The DPI manufacturing process heavily involves several particle and powder technologies such as micronization of the API, dry blending, powder filling and other particle engineering processes such as spray drying, crystallization etc. In this context, it is essential to thoroughly understand the impact of powder/particle properties and processing on the quality and performance of the DPI formulations. This will enable prediction of the processability of the DPI formulations and controlling the manufacturing process so that meticulously designed formulations are able to be finally developed as the finished DPI dosage form. This article is intended to provide a concise account of various aspects of DPI powder processing, including the process understanding and material properties that are important to achieve the desired DPI product quality. Various endeavors of model informed formulation/process design and development for DPI powder and PAT enabled process monitoring and control are also discussed.

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.

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.

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 β-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 β-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.

The Influence of Relative Humidity and Storage Conditions on the Physico-chemical Properties of Inhalation Grade Fine Lactose

Dry powder inhalers (DPIs) are favorable devices for the delivery of dry formulations to the lungs; still, they largely fail to deliver higher doses of active pharmaceutical ingredient (API) to the lower airways. Addition of fine particles of excipient (fines) to the blend of API and carrier was shown to improve aerosolization performance. Lactose monohydrate is ubiquitous excipient used for this purpose. Lactose exists in a thermodynamically stable crystalline form; however, processes like milling, sieving, or even mixing may induce alteration of crystalline structure and introduce amorphous domains, which could further affect the physico-chemical properties of the material. Therefore, the aim of this work is a detailed characterization of two commercially available types of inhalation grade fine lactose powders (Inhalac 400 and Inhalac 500) prepared using different air-jet milling parameters, with a focus on impact of storage conditions on material properties. We found that the different milling parameters resulted in variable particle size distribution (PSD), and thus surface areas, variable initial amorphous content, cohesivity, flowability, and moisture sorption of materials. In addition, exposure of fine powders to higher humidity reduced the amorphous content present in the materials, but also affected agglomeration tendency and dispersion behavior of both powders. We believe the obtained findings to be important for the aerosolization performance of carrier-based DPIs containing fines and thus need to be duly considered during formulation development.

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.

A Tribute to Professor Saranjit Singh - A Critical Thinker, Innovator, Mentor, and Educator

This commentary presents contributions and accomplishments of Professor Saranjit Singh, National Institute of Pharmaceutical Education and Research (NIPER), SAS Nagar, India, to pharmaceutical research and education. Prof. Singh completed his successful tenure in October 2021. Over his 40+ years of illustrious academic career, he trained 147 Masters and 15 PhD students in the fields of drug stability testing, degradation chemistry, impurity and metabolite characterization, and advanced analytical technologies. He has published ∼250 research articles, reviews, editorials, patent, book, and book chapters, and received numerous awards, including the Professor M.L. Khorana Memorial Lecture Award from the Indian Pharmaceutical Association (IPA) and the Outstanding Analyst and Eminent Analyst awards from the Indian Drug Manufacturers' Association (IDMA). This commentary highlights Prof. Singh's inspiring personal and renowned professional journey, including early life, education, career, accomplishments, as well as his services to academia, industry, and regulatory. By sharing the contributions and accomplishments of Prof. Singh, we strongly believe that his story will inspire the next generation of scientists to continue his legacy to advance the field.

Search for a Higgs Portal Scalar Decaying to Electron-Positron Pairs in the MicroBooNE Detector

We present a search for the decays of a neutral scalar boson produced by kaons decaying at rest, in the context of the Higgs portal model, using the MicroBooNE detector. We analyze data triggered in time with the Fermilab NuMI neutrino beam spill, with an exposure of 1.93×10^{20} protons on target. We look for monoenergetic scalars that come from the direction of the NuMI hadron absorber, at a distance of 100 m from the detector, and decay to electron-positron pairs. We observe one candidate event, with a standard model background prediction of 1.9±0.8. We set an upper limit on the scalar-Higgs mixing angle of θ<(3.3-4.6)×10^{-4} at the 95% confidence level for scalar boson masses in the range (100-200)  MeV/c^{2}. We exclude, at the 95% confidence level, the remaining model parameters required to explain the central value of a possible excess of K_{L}^{0}→π^{0}νν[over ¯] decays reported by the KOTO collaboration. We also provide a model-independent limit on a new boson X produced in K→πX decays and decaying to e^{+}e^{-}.

Near-Infrared Hyperspectral Imaging as a Monitoring Tool for On-Demand Manufacturing of Inkjet-Printed Formulations

This study evaluates the potential use of near-infrared hyperspectral imaging (NIR-HSI) for quantitative determination of the drug amount in inkjet-printed dosage forms. We chose metformin hydrochloride as a model active pharmaceutical ingredient (API) and printed it onto gelatin films using a piezoelectric inkjet printing system. An industry-ready NIR-HSI sensor combined with a motorized movable linear stage was applied for spectral acquisition. Initial API-substrate screening revealed best printing results for gelatin films with TiO₂ filling. For calibration of the NIR-HSI system, escalating drug doses were printed on the substrate. After spectral pre-treatments, including standard normal variate (SNV) and Savitzky-Golay filtering for noise reduction and enhancement of spectral features, principal component analysis (PCA) and partial least squares (PLS) regression were applied to create predictive models for the quantification of independent printed metformin hydrochloride samples. It could be shown that the concentration distribution maps provided by the developed HSI models were capable of clustering and predicting the drug dose in the formulations. HSI model prediction showed significant better correlation to the reference (HPLC) compared to on-board monitoring of dispensed volume of the printer. Overall, the results emphasize the capability of NIR-HSI as a fast and non-destructive method for the quantification and quality control of the deposited API in drug-printing applications.

Case Report: Pulmonary sarcomatoid carcinoma in a female patient from Nepal

Sarcomatoid carcinoma of the lung is an uncommon subtype of non-small-cell lung cancer (NSCLC). Even in the early stages, pulmonary sarcomatoid carcinoma (PSC) has a dismal prognosis when compared to other kinds of NSCLC with a mean survival of 9–12 months and a five-year survival rate of around 20%. We present the case of a 68-year-old woman with a two-month history of shortness of breath and cough. Initial computed tomography (CT) scan showed features of interstitial lung disease with chronic obstructive airway changes. After 34 months, the patient’s condition worsened with newer complaints of sore throat and hemoptysis. A repeat CT scan showed a ∼49x38x59mm size lesion in the superior segment of the left lower lobe. A core needle biopsy was performed, which revealed tumor cells consisting of irregular tubules and sarcomatoid components. The patient was started on chemotherapy. Unfortunately, she succumbed to her disease. Our case highlights the aggressiveness of PSC.

Impact of proactive low-molecular weight heparin therapy on outcomes in COVID-1

OBJECTIVES

Low molecular weight heparin (LMWH) may provide beneficial effects on outcomes of COVID-19. We aimed to examine the impact of LMWH treatment on clinical outcomes (duration of hospitalization, admission to intensive care unit, the requirement for mechanical ventilation, and death) of COVID-19 patients with normal D-dimer levels at admission.

BACKGROUND

Coronavirus disease-2019 (COVID-19) predisposes patients to arterial and venous thrombosis.

METHODS

In this retrospective, multicentre and observational study we analysed the data of 308 confirmed COVID-19 patients with normal D-dimer levels at initial admission. After propensity score matching (PSM) patients were grouped; Group 1; patients who received LMWH with D-dimer ≤0.5 mg/L, Group 2; patients who received LMWH after D-dimer levels exceeded 0.5 mg/L, and Group 3; patients who did not receive LMWH.

RESULTS

After PSM, each group comprised 40 patients. The patients in Group1 had the best clinical outcomes compared to the other groups. Group 3 had the worst clinical outcomes (p<0.005). The benefit of LMWH increased with early prophylactic therapy especially when started while the D-dimer levels were ≤0.5 mg/L.

CONCLUSION

Our results strongly suggest that proactive LMWH therapy improves clinical outcomes in hospitalized COVID-19 patients even with normal D-dimer levels (≤ 0.5 mg/L) (Tab. 3, Fig. 2, Ref. 34).

Impact of simulated lung fluid components on the solubility of inhaled drugs and predicted in vivo performance

Orally inhaled products (OIPs) are gaining increased attention, as pulmonary delivery is a preferred route for the treatment of various diseases. Yet, the field of inhalation biopharmaceutics is still in development phase. For a successful correlation between various in vitro data obtained during formulation characterization and in vivo performance, it is necessary to understand the impact of parameters such as solubility and dissolution of drugs. In this work, we used in vitro-in silico feedback-feedforward approach to gain a better insight into the biopharmaceutics behavior of inhaled Salbutamol Sulphate (SS) and Budesonide (BUD). The thorough characterization of the in vitro test media and the impact of different in vitro fluid components such as lipids and protein on the solubility of aforementioned drugs was studied. These results were subsequently used as an input into the developed in silico models to investigate potential PK parameter changes in vivo. Results revealed that media comprising lipids and albumin were the most biorelevant and impacted the solubility of BUD the most. On the contrary, no notable impact was seen in case of SS. The use of simple media such as phosphate buffer saline (PBS) might be sufficient to use in solubility studies of the highly soluble and permeable drugs. However, its use for the poorly soluble drugs is limited due to the greater potential for interactions within in vivo environment. The use of in silico tools showed that the model response varies, depending on the used media. Therefore, this work highlights the relevance of carefully selecting the media composition when investigating solubility and dissolution behavior, especially in the early phases of drug development and of poorly soluble drugs.

Towards predicting the product quality in hot-melt extrusion: Pilot plant scale extrusion

Following our study on the impact of hot melt extrusion (HME) process conditions on the product quality, we expanded our investigation to assessing the effect of scale-up on the product quality. To this end, we studied the influence of process settings and different scale-up variants on the active pharmaceutical ingredient (API) degradation in a pilot plant scale extruder. Six scale-up variants were investigated and none of them could replicate the product quality from the original process setup on a lab-scale extruder. By analyzing several process-dependent and -independent variables and cross referencing them to the experiments in the lab-scale extruder, we identified certain patterns. The results of the reduced order mechanistic 1D HME simulation of various process states made it possible to establish a correlation between the achieved API degradation and the local melt temperature and the exposure time in specific zones along the screw configuration. Since the same melt temperature and exposure time correlations were also valid for the lab scale-extruder, such an approach could be used in the future to predict the product quality as a function of processing conditions fully in silico prior to the first extrusion trials.