Decision Support Systems for Pharmaceutical Formulation Development Based on Artificial Neural Networks
نویسندگان
چکیده
Once discovered and established as therapeutic agent, the drug substance is used for pharmacotherapy of various diseases. The drug substance itself has unique properties, which in certain cases do not allow for effective therapy. This is the area, where pharmaceutical technology allows to improve drug substance original characteristics by optimization of pharmaceutical formulation. The latter is a complicated process involving many variables concerning formulation qualitative and quantitative composition as well as technology parameters. This chapter will be dedicated to the computer systems based on artificial neural networks allowing for guided pharmaceutical formulation optimization.
منابع مشابه
Yarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms
Yarn tenacity is one of the most important properties in yarn production. This paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. The artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 Ne. As the first step for modeling, the empirical data is col...
متن کاملA DSS-Based Dynamic Programming for Finding Optimal Markets Using Neural Networks and Pricing
One of the substantial challenges in marketing efforts is determining optimal markets, specifically in market segmentation. The problem is more controversial in electronic commerce and electronic marketing. Consumer behaviour is influenced by different factors and thus varies in different time periods. These dynamic impacts lead to the uncertain behaviour of consumers and therefore harden the t...
متن کاملKnowledge Extraction from the Neural ‘Black Box’ in Ecological Monitoring
Phytoplankton biomass within the Saginaw Bay ecosystem (Lake Huron, Michigan, USA) was characterized as a function of select physical/chemical indicators. The complexity and variability of ecological systems typically make it difficult to model the influences of anthropogenic stressors and/or natural disturbances. Here, Artificial Neural Networks (ANNs) were developed to model chlorophyll a con...
متن کاملOn the convergence speed of artificial neural networks in the solving of linear systems
Artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. This paper is a scrutiny on the application of diverse learning methods in speed of convergence in neural networks. For this aim, first we introduce a perceptron method based on artificial neural networks which has been applied for solving a non-singula...
متن کاملCatching Up with Expert Systems
century, a new era that will be far more scientific, technologic, and sophisticated than anyone would have imagined just a quarter of a century ago. However, the continued success in all areas of pharmaceutical science will depend entirely on how fast pharmaceutical scientists will adapt to rapidly changing technology. Almost 10 years ago, a survey by Shangraw and Demarest revealed a very inter...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2012