Emerging technologies for the non-invasive characterization of physical-mechanical properties of tablets

The density, porosity, breaking force, viscoelastic properties, and the presence or absence of any structural defects or irregularities are important physical-mechanical quality attributes of popular solid dosage forms like tablets. The irregularities associated with these attributes may influence the drug product functionality. Thus, an accurate and efficient characterization of these properties is critical for successful development and manufacturing of a robust tablets. These properties are mainly analyzed and monitored with traditional pharmacopeial and non-pharmacopeial methods. Such methods are associated with several challenges such as lack of spatial resolution, efficiency, or sample-sparing attributes. Recent advances in technology, design, instrumentation, and software have led to the emergence of newer techniques for non-invasive characterization of physical-mechanical properties of tablets. These techniques include near infrared spectroscopy, Raman spectroscopy, X-ray microtomography, nuclear magnetic resonance (NMR) imaging, terahertz pulsed imaging, laser-induced breakdown spectroscopy, and various acoustic- and thermal-based techniques. Such state-of-the-art techniques are currently applied at various stages of development and manufacturing of tablets at industrial scale. Each technique has specific advantages or challenges with respect to operational efficiency and cost, compared to traditional analytical methods. Currently, most of these techniques are used as secondary analytical tools to support the traditional methods in characterizing or monitoring tablet quality attributes. Therefore, further development in the instrumentation and software, and studies on the applications are necessary for their adoption in routine analysis and monitoring of tablet physical-mechanical properties

Choice of speed under compromised Dynamic Message Signs.

This study explores speed choice behavior of travelers under realistic and fabricated Dynamic Message Signs (DMS) content. Using web-based survey information of 4,302 participants collected by Amazon Mechanical Turk in the United States, we develop a set of multivariate latent-based ordered probit models participants. Results show female, African-Americans, drivers with a disability, elderly, and drivers who trust DMS are likely to comply with the fabricated messages. Drivers who comply with traffic regulations, have a good driving record, and live in rural areas, as well as female drivers are likely to slow down under fabricated messages. We highlight that calling or texting, taking picture, and tuning the radio are distracting activities leading drivers to slow down or stop under fictitious scenarios

The factors affecting household transmission dynamics and community compliance with Ebola control measures: a mixed-methods study in a rural village in Sierra Leone.

BACKGROUND: Little is understood of Ebola virus disease (EVD) transmission dynamics and community compliance with control measures over time. Understanding these interactions is essential if interventions are to be effective in future outbreaks. We conducted a mixed-methods study to explore these factors in a rural village that experienced sustained EVD transmission in Kailahun District, Sierra Leone. METHODS: We reconstructed transmission dynamics using a cross-sectional survey conducted in April 2015, and cross-referenced our results with surveillance, burial, and Ebola Management Centre (EMC) data. Factors associated with EVD transmission were assessed with Cox proportional hazards regression. Following the survey, qualitative semi-structured interviews explored views of community informants and households. RESULTS: All households (n = 240; 1161 individuals) participated in the survey. 29 of 31 EVD probable/confirmed cases died (93·5% case fatality rate); six deaths (20·6%) had been missed by other surveillance systems. Transmission over five generations lasted 16 weeks. Although most households had ≤5 members there was a significant increase in risk of Ebola in households with > 5 members. Risk of EVD was also associated with older age. Cases were spatially clustered; all occurred in 15 households. EVD transmission was better understood when the community experience started to concord with public health messages being given. Perceptions of contact tracing changed from invading privacy and selling people to ensuring community safety. Burials in plastic bags, without female attendants or prayer, were perceived as dishonourable. Further reasons for low compliance were low EMC survival rates, family perceptions of a moral duty to provide care to relatives, poor communication with the EMC, and loss of livelihoods due to quarantine. Compliance with response measures increased only after the second generation, coinciding with the implementation of restrictive by-laws, return of the first survivor, reduced contact with dead bodies, and admission of patients to the EMC. CONCLUSIONS: Transmission occurred primarily in a few large households, with prolonged transmission and a high death toll. Return of a survivor to the village and more effective implementation of control strategies coincided with increased compliance to control measures, with few subsequent cases. We propose key recommendations for management of EVD outbreaks based on this experience

Stochastic Game Approach to Air Operations

A Command and Control (C2) problem for Military Air Operations is addressed. Specifically, we consider C2 problems for air vehicles against ground based targets and defensive systems. The problem is viewed as a stochastic game. In this paper, we restrict our attention to the C2 level where the problem may consist of a few UCAVs or aircraft (or possibly teams of vehicles); less than say, a half-dozen enemy SAMs; a few enemy assets (viewed as targets from our standpoint); and some enemy decoys (assumed to mimic SAM radar signatures). At this low level, some targets are mapped out and possible SAM sites that are unavoidably part of the situation are known. One may then employ a discrete stochastic game problem formulation to determine which of these SAMs should optimally be engaged (if any), and by what series of air vehicle operations. Since this is a game model, the optimal opponent strategy is also determined. We provide analysis, numerical implementation, and simulation for full state feedback and measurement feedback control within this C2 context

Optimal Direct Yaw Moment Control of a 4WD Electric Vehicle

This thesis is concerned with electronic stability of an all-wheel drive electric vehicle with independent motors mounted in each wheel. The additional controllability and speed permitted using independent motors can be exploited to improve the handling and stability of electric vehicles. In this thesis, these improvements arise from employing a direct yaw moment control (DYC) system that seeks to adapt the understeer gradient of the vehicle and achieve neutral steer by employing a supervisory controller and simultaneously tracking an ideal yaw rate and ideal sideslip angle. DYC enhances vehicle stability by generating a corrective yaw moment realized by a torque vectoring controller which generates an optimal torque distribution among the four wheels. The torque allocation at each instant is computed by finding a solution to an optimization problem using gradient descent, a well-known algorithm that seeks the minimum cost employing the gradient of the cost function. A cost function seeking to minimize excessive wheel slip is proposed as the basis of the optimization problem, while the constraints come from the physical limitations of the motors and friction limits between the tires and road. The DYC system requires information about the tire forces in real-time, so this study presents a framework for estimating the tire force in all three coordinate directions. The sideslip angle is also a crucial quantity that must be measured or estimated but is outside the scope of this study. A comparative analysis of three different formulations of sliding mode control used for computation of the corrective yaw moment and an evaluation of how successfully they achieve neutral steer is presented. IPG Automotive’s CarMaker software, a high-fidelity vehicle simulator, was used as the plant model. A custom electric powertrain model was developed to enable any CarMaker vehicle to be reconfigured for independent control of the motors. This custom powertrain, called TVC_OpenXWD uses the torque/speed map of a Protean Pd18 implemented with lookup tables for each of the four motors. The TVC_OpenXWD powertrain model and controller were designed in MATLAB and Simulink and exported as C code to run them as plug-ins in CarMaker. Simulations of some common maneuvers, including the J-turn, sinusoidal steer, skid pad, and mu-split, indicate that employing DYC can achieve neutral steer. Additionally, it simultaneously tracks the ideal yaw rate and sideslip angle, while maximizing the traction on each tire[CB1] . The control system performance is evaluated based on its ability to achieve neutral steer by means of tracking the reference yaw rate, stabilizing the vehicle by means of reducing the sideslip angle, and to reduce chattering. A comparative analysis of sliding mode control employing a conventional switching function (CSMC), modified switching function (MSMC), and PID control (HSMC) demonstrates that the MSMC outperforms the other two methods in addition to the open loop system

Latent variable modeling approaches to assist the implementation of quality-by-design paradigms in pharmaceutical development and manufacturing

With the introduction of the Quality-by-Design (QbD) initiative, the American Food and Drug Administration and the other pharmaceutical regulatory Agencies aimed to change the traditional approaches to pharmaceutical development and manufacturing. Pharmaceutical companies have been encouraged to use systematic and science-based tools for the design and control of their processes, in order to demonstrate a full understanding of the driving forces acting on them. From an engineering perspective, this initiative can be seen as the need to apply modeling tools in pharmaceutical development and manufacturing activities. The aim of this Dissertation is to show how statistical modeling, and in particular latent variable models (LVMs), can be used to assist the practical implementation of QbD paradigms to streamline and accelerate product and process design activities in pharmaceutical industries, and to provide a better understanding and control of pharmaceutical manufacturing processes. Three main research areas are explored, wherein LVMs can be applied to support the practical implementation of the QbD paradigms: process understanding, product and process design, and process monitoring and control. General methodologies are proposed to guide the use of LVMs in different applications, and their effectiveness is demonstrated by applying them to industrial, laboratory and simulated case studies. With respect to process understanding, a general methodology for the use of LVMs is proposed to aid the development of continuous manufacturing systems. The methodology is tested on an industrial process for the continuous manufacturing of tablets. It is shown how LVMs can model jointly data referred to different raw materials and different units in the production line, allowing to understand which are the most important driving forces in each unit and which are the most critical units in the line. Results demonstrate how raw materials and process parameters impact on the intermediate and final product quality, enabling to identify paths along which the process moves depending on its settings. This provides a tool to assist quality risk assessment activities and to develop the control strategy for the process. In the area of product and process design, a general framework is proposed for the use of LVM inversion to support the development of new products and processes. The objective of model inversion is to estimate the best set of inputs (e.g., raw material properties, process parameters) that ensure a desired set of outputs (e.g., product quality attributes). Since the inversion of an LVM may have infinite solutions, generating the so-called null space, an optimization framework allowing to assign the most suitable objectives and constraints is used to select the optimal solution. The effectiveness of the framework is demonstrated in an industrial particle engineering problem to design the raw material properties that are needed to produce granules with desired characteristics from a high-shear wet granulation process. Results show how the framework can be used to design experiments for new products design. The analogy between the null space and the Agencies’ definition of design space is also demonstrated and a strategy to estimate the uncertainties in the design and in the null space determination is provided. The proposed framework for LVM inversion is also applied to assist the design of the formulation for a new product, namely the selection of the best excipient type and amount to mix with a given active pharmaceutical ingredient (API) to obtain a blend of desired properties. The optimization framework is extended to include constraints on the material selection, the API dose or the final tablet weight. A user-friendly interface is developed to aid formulators in providing the constraints and objectives of the problem. Experiments performed industrially on the formulation designed in-silico confirm that model predictions are in good agreement with the experimental values. LVM inversion is shown to be useful also to address product transfer problems, namely the problem of transferring the manufacturing of a product from a source plant, wherein most of the experimentation has been carried out, to a target plant which may differ for size, lay-out or involved units. An experimental process for pharmaceutical nanoparticles production is used as a test bed. An LVM built on different plant data is inverted to estimate the most suitable process conditions in a target plant to produce nanoparticles of desired mean size. Experiments designed on the basis of the proposed LVM inversion procedure demonstrate that the desired nanoparticles sizes are obtained, within experimental uncertainty. Furthermore, the null space concept is validated experimentally. Finally, with respect to the process monitoring and control area, the problem of transferring monitoring models between different plants is studied. The objective is to monitor a process in a target plant where the production is being started (e.g., a production plant) by exploiting the data available from a source plant (e.g., a pilot plant). A general framework is proposed to use LVMs to solve this problem. Several scenarios are identified on the basis of the available information, of the source of data and on the type of variables to include in the model. Data from the different plants are related through subsets of variables (common variables) measured in both plants, or through plant-independent variables obtained from conservation balances (e.g., dimensionless numbers). The framework is applied to define the process monitoring model for an industrial large-scale spray-drying process, using data available from a pilot-scale process. The effectiveness of the transfer is evaluated in terms of monitoring performances in the detection of a real fault occurring in the target process. The proposed methodologies are then extended to batch systems, considering a simulated penicillin fermentation process. In both cases, results demonstrate that the transfer of knowledge from the source plant enables better monitoring performances than considering only the data available from the target plant

The factors affecting household transmission dynamics and community compliance with Ebola control measures: a mixed-methods study in a rural village in Sierra Leone

Background: Little is understood of Ebola virus disease (EVD) transmission dynamics and community compliance with control measures over time. Understanding these interactions is essential if interventions are to be effective in future outbreaks. We conducted a mixed-methods study to explore these factors in a rural village that experienced sustained EVD transmission in Kailahun District, Sierra Leone. Methods: We reconstructed transmission dynamics using a cross-sectional survey conducted in April 2015, and cross-referenced our results with surveillance, burial, and Ebola Management Centre (EMC) data. Factors associated with EVD transmission were assessed with Cox proportional hazards regression. Following the survey, qualitative semi-structured interviews explored views of community informants and households. Results: All households (n = 240; 1161 individuals) participated in the survey. 29 of 31 EVD probable/confirmed cases died (93·5% case fatality rate); six deaths (20·6%) had been missed by other surveillance systems. Transmission over five generations lasted 16 weeks. Although most households had ≤5 members there was a significant increase in risk of Ebola in households with > 5 members. Risk of EVD was also associated with older age. Cases were spatially clustered; all occurred in 15 households. EVD transmission was better understood when the community experience started to concord with public health messages being given. Perceptions of contact tracing changed from invading privacy and selling people to ensuring community safety. Burials in plastic bags, without female attendants or prayer, were perceived as dishonourable. Further reasons for low compliance were low EMC survival rates, family perceptions of a moral duty to provide care to relatives, poor communication with the EMC, and loss of livelihoods due to quarantine. Compliance with response measures increased only after the second generation, coinciding with the implementation of restrictive by-laws, return of the first survivor, reduced contact with dead bodies, and admission of patients to the EMC. Conclusions: Transmission occurred primarily in a few large households, with prolonged transmission and a high death toll. Return of a survivor to the village and more effective implementation of control strategies coincided with increased compliance to control measures, with few subsequent cases. We propose key recommendations for management of EVD outbreaks based on this experience.MSF funded this study as part of emergency response activities