A multiparametric analysis of molecular complexities vs. economic data towards the continuous pharmaceutical manufacturing (CPM) of antibiotics

Mabel Ellerker, Samir Diab, Dimitrios Gerogiorgis

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

Continuous pharmaceutical manufacturing (CPM) has a documented potential to reduce production costs, offering opportunities to simultaneously streamline product development and improve economics for the pharmaceutical industry. Selecting technically feasible and economically viable candidate active pharmaceutical ingredients (APIs) for CPM is imperative for this transition to succeed. The present paper outlines a statistical correlation analysis of structural complexity and trade statistics for antibiotics, towards establishing economically viable CPM candidates. Bertz molecular complexity indices (CIs) are compared with molecular weights and price, sales and revenue data to identify the strength of correlation among variables. Sales data show that penicillins and quinolones are the most economically promising antibiotic families, composing 60% of total antibiotic revenues in the period 2009-2011. Spearman's rank correlation coefficients confirm strong monotonic relationships between antibiotic Bertz CIs and trade parameters. To the best of our knowledge, this is the first study highlighting promising antibiotics towards systematising CPM pursuits.
Original languageEnglish
Title of host publication28th European Symposium on Computer Aided Process Engineering
EditorsAnton Friedl, Jiri Klemeš, Stefan Radl, Petar Varbanov, Thomas Wallek
Place of PublicationAmsterdam
PublisherElsevier B.V.
Pages1093-1098
Number of pages6
DOIs
Publication statusPublished - 11 Jun 2018

Publication series

NameComputer-Aided Chemical Engineering

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