Multi-parametric Statistical Analysis of Economic Data for Continuous Pharmaceutical Manufacturing

Brigitta Nagy, G. Marosi, Dimitrios I. Gerogiorgis

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

The global pharmaceutical industry faces high R&D, regulatory and cost pressure which can be alleviated by the advent of Continuous Pharmaceutical Manufacturing (CPM). Embarking upon demonstrating and commissioning continuous processes is not trivial: judicious product selection and process design is quintessential for viable investments. Technological as well as economic considerations must be inseparably combined, but a quantitative method for elucidating only the most viable candidates has yet to emerge. This study illustrates how systematic statistical analysis can support business decisions and process R&D for the synthesis and design of continuous pharmaceutical processes. A systematic statistical evaluation of UK economic data has been performed to identify viable drug substances (DS) and drug products (DP) for continuous manufacturing. Product classification and ranking is employed to select those with the highest demand, and statistical hypothesis testing explores causality and correlations of key parameters. Molecular weight and complexity have been correlated with trade and value statistics, indicating that amides, lactones, antibiotics and hormones have high CPM potential.

Original languageEnglish
Title of host publication26 European Symposium on Computer Aided Process Engineering, 2016
PublisherElsevier B.V.
Pages1045-1050
Number of pages6
Volume38
ISBN (Print)9780444634283
DOIs
Publication statusPublished - 2016

Publication series

NameComputer Aided Chemical Engineering
Volume38
ISSN (Print)15707946

Fingerprint

Drug products
Statistical methods
Economics
Pharmaceutical Preparations
Hormones
Lactones
Antibiotics
Amides
Process design
Industry
Molecular weight
Statistics
Anti-Bacterial Agents
Testing
Costs

Keywords

  • Continuous Pharmaceutical Manufacturing (CPM)
  • economics
  • statistics

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

Cite this

Nagy, B., Marosi, G., & Gerogiorgis, D. I. (2016). Multi-parametric Statistical Analysis of Economic Data for Continuous Pharmaceutical Manufacturing. In 26 European Symposium on Computer Aided Process Engineering, 2016 (Vol. 38, pp. 1045-1050). (Computer Aided Chemical Engineering; Vol. 38). Elsevier B.V.. https://doi.org/10.1016/B978-0-444-63428-3.50179-X

Multi-parametric Statistical Analysis of Economic Data for Continuous Pharmaceutical Manufacturing. / Nagy, Brigitta; Marosi, G.; Gerogiorgis, Dimitrios I.

26 European Symposium on Computer Aided Process Engineering, 2016. Vol. 38 Elsevier B.V., 2016. p. 1045-1050 (Computer Aided Chemical Engineering; Vol. 38).

Research output: Chapter in Book/Report/Conference proceedingChapter

Nagy, B, Marosi, G & Gerogiorgis, DI 2016, Multi-parametric Statistical Analysis of Economic Data for Continuous Pharmaceutical Manufacturing. in 26 European Symposium on Computer Aided Process Engineering, 2016. vol. 38, Computer Aided Chemical Engineering, vol. 38, Elsevier B.V., pp. 1045-1050. https://doi.org/10.1016/B978-0-444-63428-3.50179-X
Nagy B, Marosi G, Gerogiorgis DI. Multi-parametric Statistical Analysis of Economic Data for Continuous Pharmaceutical Manufacturing. In 26 European Symposium on Computer Aided Process Engineering, 2016. Vol. 38. Elsevier B.V. 2016. p. 1045-1050. (Computer Aided Chemical Engineering). https://doi.org/10.1016/B978-0-444-63428-3.50179-X
Nagy, Brigitta ; Marosi, G. ; Gerogiorgis, Dimitrios I. / Multi-parametric Statistical Analysis of Economic Data for Continuous Pharmaceutical Manufacturing. 26 European Symposium on Computer Aided Process Engineering, 2016. Vol. 38 Elsevier B.V., 2016. pp. 1045-1050 (Computer Aided Chemical Engineering).
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