Computer-Aided Applications in Pharmaceutical Technology. This item is unavailable.Computer-Aided Applications in Pharmaceutical Technology

Research and development in the pharmaceutical industry is a time-consuming and expensive process, making it difficult for newly developed drugs to be formulated into commercially available products. Both formulation and process development can be optimized by means of statistically organized experiments, artificial intelligence and other computational methods. Simultaneous development and investigation of pharmaceutical products and processes enables application of quality by design concept that is being promoted by the regulatory authorities worldwide. Computer-Aided Applications in Pharmaceutical Technology covers the fundamentals of experimental design application and interpretation in pharmaceutical technology, chemometric methods with emphasis of their application in process control, neural computing (artificial neural networks, fuzzy logic and decision trees, evolutionary computing and genetic algorithms, self-organizing maps), computer-aided biopharmaceutical characterization as well as application of computational fluid dynamics in pharmaceutical technology. All of these techniques are essential tools for successful building of quality into pharmaceutical products and processes from the early stage of their development to selection of the optimal ones. In addition to theoretical aspects of various methods, the book provides numerous examples of their application in the field of pharmaceutical technology.

• A comprehensive review of the current state of the art on various computer aided applications in pharmaceutical technology
• Case studies are presented in order to facilitate understanding of various concepts in computer-aided applications

Dr. Jelena Đuriš graduated from the University of Belgrade, Faculty of Pharmacy in 2007. She holds a PhD in pharmaceutical technology and academic specialization title in industrial pharmacy. She is teaching industrial pharmacy and pharmaceutical technology courses at both under- and postgraduate studies, including multidisciplinary master studies in advanced data analytics (course: Advanced data analysis in pharmaceutical research and development). Jelena Đuriš has supervised 24 student master theses, 2 defended and 5 ongoing PhD theses, and 16 academic specialization theses. Her main research interests are pharmaceutical development, machine learning, modeling and simulation, modified/targeted drug release, and biopharmaceutical characterization. Jelena Đuriš has been nominated as an expert for the assessment of marketing authorization submissions for medicines by the Medicines and Medical Devices Agency of Serbia. She has published more than 60 full-length peer-reviewed papers in international journals and has 7 book chapter contributions, with more than 950 citations and h-index 18 (Scopus).