Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-15719
For citation please use:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorPaulick, Katharina-
dc.contributor.authorSeidel, Simon-
dc.contributor.authorLange, Christoph-
dc.contributor.authorKemmer, Annina-
dc.contributor.authorCruz-Bournazou, Mariano Nicolas-
dc.contributor.authorBaier, André-
dc.contributor.authorHaehn, Daniel-
dc.date.accessioned2022-05-17T13:20:01Z-
dc.date.available2022-05-17T13:20:01Z-
dc.date.issued2022-04-07-
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/16940-
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-15719-
dc.description.abstractThe fourth industrial revolution in 2011 aimed to transform the traditional manufacturing processes. As part of this revolution, disruptive innovations in drug development and data science approaches have the potential to optimize CMC (chemistry, manufacture, and control). The real-time simulation of processes using “digital twins” can maximize efficiency while improving sustainability. As part of this review, we investigate how the World Health Organization’s 17 sustainability goals can apply toward next-generation drug development. We analyze the state-of-the-art laboratory leadership, inclusive personnel recruiting, the latest therapy approaches, and intelligent process automation. We also outline how modern data science techniques and machine tools for CMC help to shorten drug development time, reduce failure rates, and minimize resource usage. Finally, we systematically analyze and compare existing approaches to our experiences with the high-throughput laboratory KIWI-biolab at the TU Berlin. We describe a sustainable business model that accelerates scientific innovations and supports global action toward a sustainable future.en
dc.description.sponsorshipBMBF, 01DD20002A, Verbundprojekt: Internationales Zukunftslabor für KI-gestützte Bioprozessentwicklung "KIWI-biolab"; Teilvorhaben: Koordination und Aufbau eines KI-Exzellenzzentrumsen
dc.language.isoenen
dc.rightsLicensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subject.ddc570 Biowissenschaften; Biologiede
dc.subject.otherIndustry 4.0en
dc.subject.otherpharmaceutical industryen
dc.subject.otherCMCen
dc.subject.otherautomationen
dc.subject.othersustainabilityen
dc.subject.otherdiversityen
dc.subject.otherbioprocess developmenten
dc.subject.otherdigital twinen
dc.subject.othermachine learningen
dc.subject.otherintelligent systemsen
dc.titlePromoting Sustainability through Next-Generation Biologics Drug Developmenten
dc.typeArticleen
dc.date.updated2022-05-05T14:42:55Z-
tub.accessrights.dnbfreeen
tub.publisher.universityorinstitutionTechnische Universität Berlinen
dc.identifier.eissn2071-1050-
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.doi10.3390/su14084401en
dcterms.bibliographicCitation.journaltitleSustainabilityen
dcterms.bibliographicCitation.originalpublisherplaceBaselen
dcterms.bibliographicCitation.volume14en
dcterms.bibliographicCitation.originalpublishernameMDPIen
dcterms.bibliographicCitation.issue8en
dcterms.bibliographicCitation.articlenumber4401en
tub.affiliationFak. 3 Prozesswissenschaften » Inst. Biotechnologie » FG Bioverfahrenstechnikde
Appears in Collections:Technische Universität Berlin » Publications

Files in This Item:
sustainability-14-04401.pdf
Format: Adobe PDF | Size: 11.43 MB
DownloadShow Preview
Thumbnail

Item Export Bar

This item is licensed under a Creative Commons License Creative Commons