905
Views
55
CrossRef citations to date
0
Altmetric
Research Article

A quality by design approach using artificial intelligence techniques to control the critical quality attributes of ramipril tablets manufactured by wet granulation

, , , , &
Pages 236-245 | Received 06 Feb 2012, Accepted 17 Jun 2012, Published online: 13 Aug 2012

References

  • DeMatas M, Shao Q, Shukla R. Artificial intelligence the key to process understanding. Pharm Tech Eur 2007;19:1.
  • US Food and Drug Administration (FDA). (2004). Pharmaceutical cGMPs for the 21st century: A risk-based approach, final report. Available at: http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/Manufacturing/Questionsand AnswersonCurrentGoodManufacturingPracticescGMPforDrugs/UCM176374.pdf
  • Garcia T, Cook G, Nosal R. PQLI key topics – criticality, design space and control strategy. J Pharm Innov 2008;3:60–68.
  • Yu LX. Pharmaceutical quality by design: Product and process development, understanding, and control. Pharm Res 2008;25:781–791.
  • International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. (2009). Pharmaceutical development, Q8(R2) Available at: http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Quality/Q8_R1/Step4/Q8_R2_Guideline.pdf.
  • Vogt N. Quality by design: Managing research and development. Chemometr Intell Lab Syst 1992;14:93–101.
  • Wu H, Khan M, Hussain AS. Process control perspective for process analytical technology: Integration of chemical engineering practice into semiconductor and pharmaceutical industries. Chem Eng Commun 2007;194:760–779.
  • Xu X, Khan MA, Burgess DJ. A quality by design (QbD) case study on liposomes containing hydrophilic API: I. Formulation, processing design and risk assessment. Int J Pharm 2011;419:52–59.
  • Shao Q, Rowe RC, York P. Comparison of neurofuzzy logic and neural networks in modelling experimental data of an immediate release tablet formulation. Eur J Pharm Sci 2006;28:394–404.
  • Agatonovic-Kustrin S, Beresford R. Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research. J Pharm Biomed Anal 2000;22:717–727.
  • Colbourn EA, Rowe RC. Modeling and optimization of a tablet formulation using neural networks and genetic algorithms. Pharm Tech Eur 1996;8:46–55.
  • Krogh A. What are artificial neural networks? Nat Biotechnol 2008;26:195–197.
  • Armstrong NA, James KC. (1996). Pharmaceutical experimental design and interpretation. Abingdon: Taylor and Francis Ltd.
  • Rowe RC, Roberts JR. (1998). Intelligent software for product formulation. Product Formulation and Artificial Intelligence. Boca Raton: Taylor/Francis, 1–8.
  • Martindale W. (1996). Martindale, the extra pharmacopeia. 33rd edition. London: The Pharm Press.
  • Patel PH, Patel JK, Patel RR, Patel PM. Formulation development and optimization of multiple unit particles system (mups) containing ramipril and hydrochlorothiazide. Der Pharmacia Lettre 2010;2:72–82.
  • International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. (1996). Validation of analytical procedures: Text and methodology, Q2 (R1). Available at: http://www.ich.org/fileadmin/Public_Web_Site/ICH_Products/Guidelines/Quality/Q2_R1/Step4/Q2_R1__Guideline.pdf
  • The European Pharmacopoeia (online). EU, 2010.
  • Intelligensys Ltd. INForm Intelligent Formulation. UK, 2009.
  • Shao Q, Rowe RC, York P. Investigation of an artificial intelligence technology–Model trees. Novel applications for an immediate release tablet formulation database. Eur J Pharm Sci 2007;31:137–144.
  • Ritchie MD, White BC, Parker JS, Hahn LW, Moore JH. Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases. BMC Bioinformatics 2003;4:28.
  • Bourquin J, Schmidli H, van Hoogevest P, Leuenberger H. Comparison of artificial neural networks (ANN) with classical modelling techniques using different experimental designs and data from a galenical study on a solid dosage form. Eur J Pharm Sci 1998;6:287–301.
  • Ferreira C. (2006). Gene expression programming: Mathematical modelling by an artificial intelligence. 2nd edition. Germany: Springer-Verlag.
  • Colbourn EA, Roskilly SJ, Rowe RC, York P. Modelling formulations using gene expression programming–a comparative analysis with artificial neural networks. Eur J Pharm Sci 2011;44:366–374.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.