Buket Aksu and Gizem Ye?en
The manufacture of pharmaceuticals is a complicated process from formulation to the finished product. This process involves multivariate interactions between raw materials and process conditions, which are crucial for process ability and product quality. As developing drugs becomes more complex and challenging, this has increased the costs, time losses and the issues encountered in product licensing process. As the costs of R&D studies and new product release into the market increase, drug companies avoid taking innovative steps and developing new products. Hence, overcome these obstacles new approach has been arrived by ICH Guidelines and Quality by Design (QbD) concept which means designing and developing formulations and manufacturing processes to ensure the predefined product quality via determining critical parameters that significantly affect the quality and conducting experiments designated by scientific knowledge and statistics and creating a design space. While maintaining predefined product quality there is a requirement to use advanced statistical methods and mathematical modelling technics for choosing the right experiments and screening the parameters effect the quality of the targeted product which are quite a lot in drug production. Nowadays there are several software’s contains variety of statistical methods and mathematical modelling techniques which developed to carry out each quality by design steps like experimental design, optimisation within; and are being developed to be more user friendly and easier to be evaluate the experimental data and the results of the analyses with statistical values, charts and graphics; also grow into combine all the stages of QbD approach at same software. Developing software that includes the creation of design space and design of experiments via advanced modelling techniques, which examine both linear and nonlinear relations has become very critical in terms of pharmaceutical product development and will continue to do so.
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