Process Understanding is the underpinning knowledge that allows the manufacture of chemical entities to be carried out routinely, robustly and to the required standard of quality. This area has gained in importance over the last few years, particularly due to the recent impetus from the USA`s Food and Drug Administration. This book covers the multidisciplinary aspects required for successful process design, safety, modeling, scale-up, PAT, pilot plant implementation, plant design as well the rapidly expanding area of outsourcing.

In discussing what process understanding means to different disciplines and sectors throughout a product`s life cycle, this handbook and ready reference reveals the factors important to the development and manufacture of chemicals. The book focuses on the fundamental scientific understanding necessary. for a smoother technical transfer between the disciplines, leading to more effective and effi cient process development and manufacturing. A range of case studies are used to exemplify and illustrate the main issues raised.

As a result, readers will appreciate that process understanding can deliver a real competitive advantage within the pharmaceuticals and fine chemicals industry. This book serves as an aid to meeting the stringent regulations required by the relevant authorities through demonstrable understanding of the underlying science.

Jose Camacho-Paez is a scientist at the research Group of Complex Systems in the Institute of Control Systems and Industrial Computing of the Technical University of Valencia, in Spain. He holds a degree in Computer Science from the University of Granada (2003) and a Ph.D. in Control Systems and Industrial Computing from the Technical University of Valencia (2007). His Ph.D. was awarded with the second Rosina Ribalta Prize to the best Ph.D. projects from the EPSON Foundation, and with the D.L. Massart Award in Chemometrics from the Belgian Chemometrics Society. He is reviewer of Chemometrics and Intelligent Laboratory Systems, AIChE Journal, Industrial& Engineering Chemistry Research, Chemical Engineering Science and Biosystems Engineering.

Jesus Pico received the M.S.Eng. degree in industrial engineering and the Ph.D. degree in control engineering, both from the Technical University of Valencia (UPV), Spain. Currently he is Associate Professor at the Department of Systems Engineering and Control at the UPV. His main research interests are in nonlinear and adaptive control, modeling and control of fedbatch processes, and control methods in systems biology and bioprocesses. He has been involved in several European industry-oriented projects related to batch processes. He is member of the Technical Comitee on Bioprocesses and Biosystems of the International Federation of Automatic Control (IFAC).

Alberto Ferrer is Professor of Statistics at the Department of Applied Statistics, Operation Research and Quality, and Head of the Multivariate Statistical Engineering Research Group of the Technical University of Valencia (Spain). He holds a M.S.Eng. in Agricultural Engineering (1987 - First Spanish National Award) and a Ph.D. in Statistics (1992) from the Technical University of Valencia. His research focuses on statistical techniques for quality and productivity improvement. He has been involved in several industry-oriented research projects related to batch and continuous processes. Prof. Ferrer is currently associate editor of Technometrics, member of the editorial board of Quality Engineering, member of the Council of the International Society for Business and Industrial Statistics (ISBIS), and the European Network for Business and Industrial Statistics (ENBIS).

INTRODUCTION
State of the Art
Two-way latent structures-based models
MODELLING OF BATCH PROCESSES WITH 2-WAY MODELS
Modelling of Batch Process data
Cross-validation algorithms
Multi-Phase Analysis Framework
MULTIVARIATE STATISTICAL PROCESS CONTROL OF BATCH PROCESSES
Statistical Process Control in Continuous Processes
Analysis of historical data in batch processes (Phase I)
On-line Monitoring of batch processes (Phase II)
OTHER APPLICATIONS OF LVB METHODS TO BATCH PROCESSES
Soft-sensors in batch processes
Optimization of batch processes