In pharmaceutical drug discovery and agricultural crop product discovery, in vivo bioassay experiments are used to identify promising compounds for further research. The reproducibility and accuracy of the bioassay is...
详细信息
In pharmaceutical drug discovery and agricultural crop product discovery, in vivo bioassay experiments are used to identify promising compounds for further research. The reproducibility and accuracy of the bioassay is crucial to be able to correctly distinguish between active and inactive compounds. In the case of agricultural product discovery, a replicated dose-response of commercial crop protection products is assayed and used to monitor test quality. The activity of these compounds on the test organisms, the weeds, insects, or fungi, is characterized by a dose-response curve measured from the bioassay. These curves are used to monitor the quality of the bioassays. If undesirable conditions in the bioassay arise, such as equipment failure or problems with the test organisms, then a bioassay monitoring procedure is needed to quickly detect such issues. In this article we illustrate a proposed nonlinear profile monitoring method to monitor the variability of multiple assays, the adequacy of the dose-response model chosen, and the estimated dose-response curves for aberrant cases in the presence of heteroscedasticity. We illustrate these methods with in vivo bioassay data collected over one year from DuPont Crop Protection.
We develop a class of new multivariate procedures for monitoring quality by detecting a change in the level of a multivariateprocess. Following the ideas of S.N. Roy, we first consider a linear combination statistic ...
详细信息
We develop a class of new multivariate procedures for monitoring quality by detecting a change in the level of a multivariateprocess. Following the ideas of S.N. Roy, we first consider a linear combination statistic which results from projecting the multivariate observations onto a unit vector and then maximizing a selected univariate statistic over all directions. An application to a sheet metal assembly process is discussed in Section 3. Comparisons are made between one of our new procedures and other major multivariate quality monitoring schemes in Section 4. A small simulation study compares the average run lengths of the different procedures both when the process is in-control and after a shift has occurred. Some large sample properties are discussed in Section 5 and some computational details in Section 6. (C) 2007 Elsevier B.V. All rights reserved.
Real time release (RTR) of products is a new paradigm in the pharmaceutical industry. An RTR system assures that when the last manufacturing step is passed all the final release criteria are met. Various types of mode...
详细信息
Real time release (RTR) of products is a new paradigm in the pharmaceutical industry. An RTR system assures that when the last manufacturing step is passed all the final release criteria are met. Various types of models can be used within the RTR framework. For each RTR system, the monitoring capability, control capability and RTR capability need to be tested. This paper presents some practical examples within the RTR framework using near-infrared and process data obtained from a tablet manufacturing process. (c) 2006 Elsevier B.V. All rights reserved.
process analytical technology is an essential step forward in pharmaceutical industry. Real-time analyzers will provide timely data on quality properties. This information combined with process data (temperatures, flo...
详细信息
process analytical technology is an essential step forward in pharmaceutical industry. Real-time analyzers will provide timely data on quality properties. This information combined with process data (temperatures, flow rates, pressure readings) collected in real time can become a powerful tool for this industry, for process understanding, process and quality monitoring, abnormal situation detection and for improving product quality and process reliability. A very important tool for this achievement is the multivariate analysis.
Partial least squares (PLS) has been extensively used in process monitoring and modeling to deal with many, noisy, and collinear variables. However, the conventional linear PLS approach may be not effective due to the...
详细信息
Partial least squares (PLS) has been extensively used in process monitoring and modeling to deal with many, noisy, and collinear variables. However, the conventional linear PLS approach may be not effective due to the fundamental inability of linear regression techniques to account for nonlinearity and dynamics in most chemical and biological processes. A hybrid approach, by combining a nonlinear PLS approach with a dynamic modeling method, is potentially very efficient for obtaining more accurate prediction of nonlinear process dynamics. In this study, neural network PLS (NNPLS) were combined with finite impulse response (FIR) and auto-regressive with exogenous (ARX) inputs to model a full-scale biological wastewater treatment plant. It is shown that NNPLS with ARX inputs is capable of modeling the dynamics of the nonlinear wastewater treatment plant and much improved prediction performance is achieved over the conventional linear PLS model. (c) 2006 Elsevier Ltd. All rights reserved.
process analytical chemistry was recognized by Callis et al. (Analytical Chemistry, 59 (1987): 624A-635A) (1) as a field that extends well beyond real time measurements of process parameters. process Analytical Techno...
详细信息
process analytical chemistry was recognized by Callis et al. (Analytical Chemistry, 59 (1987): 624A-635A) (1) as a field that extends well beyond real time measurements of process parameters. process Analytical Technology is taking central stage with the 2004 guidance from the Food and Drug Administration, with a mandate much wider than real time measurements. The pharmaceutical industry is entering a new era. Chemometrics has played an integral part for the real time development of process analytical measurements (multivariate calibration) and it is ready to face the challenge of process Analytical Technology in this wider definition. The scope of this paper is to demonstrate that multivariate, data based statistical methods, can play a critical role in process understanding, multivariate statistical process control, abnormal situation detection, fault diagnosis, processcontrol and process scale-up, as linked to process analytical technology.
statisticalprocesscontrol (SPC) is widely used in process industries to monitor variations in process attributes. Typically, automatic devices capture a multitude of measurements on process and product characteristi...
详细信息
statisticalprocesscontrol (SPC) is widely used in process industries to monitor variations in process attributes. Typically, automatic devices capture a multitude of measurements on process and product characteristics every few seconds. Operators and engineers commonly monitor only a small subset of these. multivariate SPC has been proposed to fully utilize the available data, however, interpretation of multivariate information is often too complex for most line operators. This paper describes the design and implementation of a real-time multivariateprocesscontrol system that features a graphical user interface (GUI) and provides useful information for both line operators and engineers. The information system described in this paper should provide large-scale manufacturers with better access to information for identifying opportunities in continuing to improve processes performance and business competitiveness. (C) 2002 Published by Elsevier Science B.V.
The quality of a product is dynamic in nature and develops over time. We present a case study from the food industry in which the concept of measuring the end-product quality is extended to incorporate the shelf-life ...
详细信息
The quality of a product is dynamic in nature and develops over time. We present a case study from the food industry in which the concept of measuring the end-product quality is extended to incorporate the shelf-life period of the product with practical examples showing the harm of ignoring the changes that occur in the product quality as a function of time. The article also addresses the use of in-line spectroscopy to relate the variations in the input parameters, such as the raw materials, and the process variables to the final product quality over the entire shelf-life of the product. We also discuss multivariate statistical process control and monitoring issues.
Most applications of MSPC have tended to focus upon the manufacture of a single product with separate models being developed to monitor individual recipes. With process manufacturing trends being influenced by custome...
详细信息
Most applications of MSPC have tended to focus upon the manufacture of a single product with separate models being developed to monitor individual recipes. With process manufacturing trends being influenced by customer demands there has been an increase in the manufacture of a wide variety of products, there is a real need for process models which allow a range of products, grades or recipes to be monitored using a single process model. With increasing attention now being paid to the FDA process Analytical Technologies (PAT) initiative, the use of spectro-chemical information for enhanced monitoring of reactions and is now gaining impetus. An application of the performance monitoring of a multi-recipe multi-reactor industrial batch polymer manufacturing is discussed in which NIR spectroscopic data is also integrated with process data to provide enhanced batch monitoring.
In this work, the integration of ARMA filters into the multivariate statistical process control (MSPC) framework is presented to improve the monitoring of large-scale industrial processes. As demonstrated in the paper...
详细信息
In this work, the integration of ARMA filters into the multivariate statistical process control (MSPC) framework is presented to improve the monitoring of large-scale industrial processes. As demonstrated in the paper, such filters can remove auto-correlation from the monitored variables to avoid the production of false alarms. This is exemplified by application studies to a synthetic example from the literature and to the Tennessee Eastman benchmark process. (C) 2004 Elsevier Ltd. All rights reserved.
暂无评论