Minimizing Variability of Cascade Impaction Measurements in Inhalers and Nebulizers

The purpose of this article is to catalogue in a systematic way the available information about factors that may influence the outcome and variability of cascade impactor (CI) measurements of pharmaceutical aerosols for inhalation, such as those obtained from metered dose inhalers (MDIs), dry powder inhalers (DPIs) or products for nebulization; and to suggest ways to minimize the influence of such factors. To accomplish this task, the authors constructed a cause-and-effect Ishikawa diagram for a CI measurement and considered the influence of each root cause based on industry experience and thorough literature review. The results illustrate the intricate network of underlying causes of CI variability, with the potential for several multi-way statistical interactions. It was also found that significantly more quantitative information exists about impactor-related causes than about operator-derived influences, the contribution of drug assay methodology and product-related causes, suggesting a need for further research in those areas. The understanding and awareness of all these factors should aid in the development of optimized CI methods and appropriate quality control measures for aerodynamic particle size distribution (APSD) of pharmaceutical aerosols, in line with the current regulatory initiatives involving quality-by-design (QbD). Editorial Comment: The International Pharmaceutical Aerosol Consortium on Regulation and Science (IPAC-RS) is an international association of innovator and generic companies that develop, manufacture or market orally inhaled and nasal drug products for local and systemic treatment of a variety of debilitating diseases such as asthma, chronic obstructive pulmonary disease and diabetes. IPAC-RS is committed to advancing consensus-based, scientifically driven standards and regulations for these products, with the purpose of facilitating the availability of high-quality, safe, and efficacious drug products to patients.     

Improved Quality Control Metrics for Cascade Impaction Measurements of Orally Inhaled Drug Products (OIPs)

This study of aerodynamic mass-weighted particle size distribution (APSD) data from orally inhaled products (OIPs) investigated whether a set of simpler (than currently used) metrics may be adequate to detect changes in APSD for quality control (QC) purposes. A range of OIPs was examined, and correlations between mass median aerodynamic diameter and the ratio of large particle mass (LPM) to small particle mass (SPM) were calculated. For an Andersen cascade impactor, the LPM combines the mass associated with particle sizes from impactor stage 1 to a product-specific boundary size; SPM combines the mass of particles from that boundary through to terminal filter. The LPM–SPM boundary should be chosen during development based on the full-resolution impactor results so as to maximize the sensitivity of the LPM/SPM ratio to meaningful changes in quality. The LPM/SPM ratio along with the impactor-sized mass (ISM) are by themselves sufficient to detect changes in central tendency and area under the APSD curve, which are key in vitro quality attributes for OIPs. Compared to stage groupings, this two-metric approach provides better intrinsic precision, in part due to having adequate mass and consequently better ability to detect changes in APSD and ISM, suggesting that this approach should be a preferred QC tool. Another advantage is the possibility to obtain these metrics from the abbreviated impactor measurements (AIM) rather than from full-resolution multistage impactors. Although the boundary is product specific, the testing could be accomplished with a basic AIM system which can meet the needs of most or all OIPs.     

Operational Changes in a Shared Resource Laboratory with the Use of a Product Lifecycle Management Approach: A Case Study

Shared Resource Laboratories (SRLs) provide investigators access to necessary scientific and resource expertise to leverage complex technologies fully for advancing high-quality biomedical research in a cost-effective manner. At the University of Nebraska Medical Center, the Flow Cytometry Research Facility (FCRF) offered access to exceptional technology, but the methods of operation were outdated and unsustainable. Whereas technology has advanced and the institute has expanded, the operations at the facility remained unchanged for 35 yr. To rectify this, at the end of 2013, we took a product lifecycle management approach to affect large operational changes and align the services offered with the SRL goal of education, as well as to provide service to researchers. These disruptive operational changes took over 10 mo to complete and allowed for independent end-user acquisition of flow cytometry data. The results have been monitored for the past 12 mo. The operational changes have had a positive impact on the quality of research, increased investigator-facility interaction, reduced stress of facility staff, and increased overall use of the resources. This product lifecycle management approach to facility operations allowed us to conceive of, design, implement, and monitor effectively the changes at the FCRF. This approach should be considered by SRL management when faced with the need for operationally disruptive measures.     

A Systems Approach to Sustainable Technical Product Design

Many existing methods for sustainable technical product design focus on environmental efficiency while lacking a framework for a holistic, sustainable design approach that includes combined social, technical, economic, and environmental aspects in the whole product life cycle, and that provides guidance on a technical product development level. This research proposes a framework for sustainable technical product design in the case of skis. We developed a ski under the Grown brand, benchmarked according to social, environmental, economic, and technical targets, following an initial sustainability assessment, and delivered the first environmental life cycle assessment (ELCA) and the first social life cycle assessment (SLCA) of skis. The framework applies a virtual development process as a combination of ELCA to calculate the environmental footprint as carbon equivalents of all materials and processes and a technical computer‐aided design (CAD) and computer‐aided engineering (CAE) simulation and virtual optimization using parameter studies for the nearly prototype‐free development of the benchmarked skis. The feedback loops between life cycle assessment (LCA) and virtual simulation led to the elimination of highly energy intensive materials, to the pioneering use of basalt fibers in skis, to the optimization of the use of natural materials using protective coatings from natural resins, and to the optimization of the production process. From an environmental perspective, a minimum 32% reduction in carbon equivalent emissions of materials in relation to other comparably performing skis has been achieved, as well as a pioneering step forward toward transparent communication of the environmental performance by the individual, comparable, and first published ski carbon footprint per volume unit.     

Inferential Clustering Approach for Microarray Experiments with Replicated Measurements

Cluster analysis has proven to be a useful tool for investigating the association structure among genes in a microarray data set. There is a rich literature on cluster analysis and various techniques have been developed. Such analyses heavily depend on an appropriate (dis)similarity measure. In this paper, we introduce a general clustering approach based on the confidence interval inferential methodology, which is applied to gene expression data of microarray experiments. Emphasis is placed on data with low replication (three or five replicates). The proposed method makes more efficient use of the measured data and avoids the subjective choice of a dissimilarity measure. This new methodology, when applied to real data, provides an easy-to-use bioinformatics solution for the cluster analysis of microarray experiments with replicates (see the Appendix). Even though the method is presented under the framework of microarray experiments, it is a general algorithm that can be used to identify clusters in any situation. The method's performance is evaluated using simulated and publicly available data set. Our results also clearly show that our method is not an extension of the conventional clustering method based on correlation or euclidean distance.     

A Process Chaining Approach toward Product Design for Environment

This article presents an approach toward product design for environment (DfE) at the level that integrates environmental hazard analysis with models of transformation processes. As a complementary analysis tool to life-cycle assessment (LCA), this method would support detailed design decisions through modeling of a "process chain" for a subset of the product's life cycle. The building blocks for this approach are a set of unit process models that can convert process and design parameters into estimates for energy utilization, production scrap, and ancillary waste flows. These values for quantity of environmental releases can be integrated using a multicriiteria environmental hazard evaluation methodology that can estimate the "qualrty" of environmental releases. Finally, the waste information can be used to support a design model that can link design parameters to material, process, and operational parameter selection. A case study illustrating printed circuit board (PCB) assembly is presented to show process chain implementation in manufacturing applications.     

Environmentally Conscious Product Design: A Collaborative Internet-based Modeling Approach

This paper proposes a computer-based method for providing product designers with real-time environmental impact assessment. In this concurrent modeling approach, environmental experts build life-cycle models, define their interfaces, and publish them as distributed objects on the Internet. Traditional designers integrating these objects into their design models have access to the impact assessment methods provided by the environmental expert. In this paradigm, the focus shifts from providing techniques that let non-expert designers perform life-cycle impact assessments to tools that facilitate timely communication and information transfer between designers and appropriate environmental experts. Establishing real-time communication between the product design models and the environmental life-cycle models is the primary focus of this paper. Methods for establishing and maintaining the interaction between life-cycle and product design models are described. A beverage container design example illustrates how this collaborative approach can use environmental and traditional design goals to determine effective tradeoffs between design alternatives.     

Functional Aspects of the EGF-Induced MAP Kinase Cascade: A Complex Self-Organizing System Approach

The EGF-induced MAP kinase cascade is one of the most important and best characterized networks in intracellular signalling. It has a vital role in the development and maturation of living organisms. However, when deregulated, it is involved in the onset of a number of diseases. Based on a computational model describing a “surface” and an “internalized” parallel route, we use systems biology techniques to characterize aspects of the network’s functional organization. We examine the re-organization of protein groups from low to high external stimulation, define functional groups of proteins within the network, determine the parameter best encoding for input intensity and predict the effect of protein removal to the system’s output response. Extensive functional re-organization of proteins is observed in the lower end of stimulus concentrations. As we move to higher concentrations the variability is less pronounced. 6 functional groups have emerged from a consensus clustering approach, reflecting different dynamical aspects of the network. Mutual information investigation revealed that the maximum activation rate of the two output proteins best encodes for stimulus intensity. Removal of each protein of the network resulted in a range of graded effects, from complete silencing to intense activation. Our results provide a new “vista” of the EGF-induced MAP kinase cascade, from the perspective of complex self-organizing systems. Functional grouping of the proteins reveals an organizational scheme contrasting the current understanding of modular topology. The six identified groups may provide the means to experimentally follow the dynamics of this complex network. Also, the vulnerability analysis approach may be used for the development of novel therapeutic targets in the context of personalized medicine.     

Binary Regression Analysis with Pooled Exposure Measurements: A Regression Calibration Approach

Summary It has become increasingly common in epidemiological studies to pool specimens across subjects to achieve accurate quantitation of biomarkers and certain environmental chemicals. In this article, we consider the problem of fitting a binary regression model when an important exposure is subject to pooling. We take a regression calibration approach and derive several methods, including plug‐in methods that use a pooled measurement and other covariate information to predict the exposure level of an individual subject, and normality‐based methods that make further adjustments by assuming normality of calibration errors. Within each class we propose two ways to perform the calibration (covariate augmentation and imputation). These methods are shown in simulation experiments to effectively reduce the bias associated with the naive method that simply substitutes a pooled measurement for all individual measurements in the pool. In particular, the normality‐based imputation method performs reasonably well in a variety of settings, even under skewed distributions of calibration errors. The methods are illustrated using data from the Collaborative Perinatal Project.     

Almost Unbiased Ratio and Product Type Estimators: A New Approach

In this paper, we have proposed a new method, consisting of a linear variety of the estimators and a linear constraint to remove the bias appearing in the estimators of the ratio R = Y/X and product P = YX. The percent relative efficiency of proposed estimators has also been demonstrated with numerical illustrations.     

Multi-Parametric Relationships between PAM Measurements and Carbon Incorporation, an In Situ Approach

Primary production (PP) in the English Channel was measured using (13)C uptake and compared to the electron transport rate (ETR) measured using PAM (pulse amplitude modulated fluorometer). The relationship between carbon incorporation (P(obs)) and ETR was not linear but logarithmic. This result can be explained by alternative electron sinks at high irradiance which protect the phytoplankton from photoinhibition. A multi-parametric model was developed to estimate PP by ETR. This approach highlighted the importance of taking physicochemical parameters like incident light and nutrient concentrations into account. The variation in the ETR/P(obs) ratio as a function of the light revealed different trends which were characterized by three parameters (R(max), the maximum value of ETR/P(obs); E(Rmax), the light intensity at which R(max) is measured; γ the initial slope of the curve). Based on the values of these three parameters, data were divided into six groups which were highly dependent on the seasons and on the physicochemical conditions. Using the multi-parametric model which we defined by P(obs) and ETR measurements at low frequencies, the high frequency measurements of ETR enabled us to estimate the primary production capacity between November 2009 and December 2010 at high temporal and spatial scales.     

Relating Single-Molecule Measurements to Thermodynamics

Measurements made on large ensembles of molecules are routinely interpreted using thermodynamics, but the normal rules of thermodynamics may not apply to measurements made on single molecules. Using a polymer stretching experiment as an example, it is shown that in the limit of a single, short molecule the outcome of experimental measurements may depend on which variables are held fixed and which are allowed to fluctuate. Thus an experiment in which the end-to-end distance of the polymer molecule is fixed and the tension fluctuates yields a different result than an experiment where the force is fixed and the end-to-end distance fluctuates. It is further shown that this difference is due to asymmetry in the distribution of end-to-end distances for a single molecule, and that the difference vanishes in the appropriate thermodynamic limit; that is, as the polymer molecule becomes long compared to its persistence length. Despite these differences, much of the thermodynamic formalism still applies on the single-molecule level if the thermodynamic free energies are replaced with appropriate potentials of mean force. The primary remaining differences are consequences of the fact that unlike the free energies, the potentials of mean force are not in general homogeneous functions of their variables. The basic thermodynamic concepts of an intensive or extensive quantity, and the thermodynamic relationships that follow from them, are therefore less useful for interpreting single-molecule experiments.     

Pyranose Dehydrogenase Ligand Promiscuity: A Generalized Approach to Simulate Monosaccharide Solvation,Binding, and Product Formation

The flavoenzyme pyranose dehydrogenase (PDH) from the litter decomposing fungus Agaricus meleagris oxidizes many different carbohydrates occurring during lignin degradation. This promiscuous substrate specificity makes PDH a promising catalyst for bioelectrochemical applications. A generalized approach to simulate all 32 possible aldohexopyranoses in the course of one or a few molecular dynamics (MD) simulations is reported. Free energy calculations according to the one-step perturbation (OSP) method revealed the solvation free energies (ΔG_solv) of all 32 aldohexopyranoses in water, which have not yet been reported in the literature. The free energy difference between β- and α-anomers (ΔG_β-α) of all d-stereoisomers in water were compared to experimental values with a good agreement. Moreover, the free-energy differences (ΔG) of the 32 stereoisomers bound to PDH in two different poses were calculated from MD simulations. The relative binding free energies (ΔΔG_bind) were calculated and, where available, compared to experimental values, approximated from K _m values. The agreement was very good for one of the poses, in which the sugars are positioned in the active site for oxidation at C1 or C2. Distance analysis between hydrogens of the monosaccharide and the reactive N5-atom of the flavin adenine dinucleotide (FAD) revealed that oxidation is possible at HC1 or HC2 for pose A, and at HC3 or HC4 for pose B. Experimentally detected oxidation products could be rationalized for the majority of monosaccharides by combining ΔΔG_bind and a reweighted distance analysis. Furthermore, several oxidation products were predicted for sugars that have not yet been tested experimentally, directing further analyses. This study rationalizes the relationship between binding free energies and substrate promiscuity in PDH, providing novel insights for its applicability in bioelectrochemistry. The results suggest that a similar approach could be applied to study promiscuity of other enzymes.