Designing and formulating an ideal pharmaceutical product is a very tedious job for a formulator as it comprises of multiple objectives. The traditional method followed for years is not only expensive and time consuming but it also needs lot of effort to be put in and in spite of that at times it proves to be unfavourable and unpredictable too.The recent approach to optimise i.e. to achieve the best combination of product and process characteristics under the given conditions is by using Design of Experiment (DoE).Design of Experiment (DoE) is an organised approach to determine the relationship between the factors (Xs) affecting a process and the output of that process (Ys).The recent optimisation methodologies include various approaches that come under the 2 main categories namely, simultaneous optimisation and sequential optimisation. Nowadays there are various software available to carry out the optimisation of pharmaceutical products.

Author Name: REHA S. CHODANKAR*, ASISH DEV

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Keywords: Artificial neural network (ANN), Design of experiment (DoE), Factors, Levels, Optimization, Variables

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EISSN: 2320-9267

EOI/DOI: https://doi.org/10.30750/ijpbr

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