LEADER 04616nam 2201069z- 450 001 9910595072803321 005 20231214133415.0 035 $a(CKB)5680000000080798 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/92142 035 $a(EXLCZ)995680000000080798 100 $a20202209d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBioprocess Systems Engineering Applications in Pharmaceutical Manufacturing 210 $aBasel$cMDPI Books$d2022 215 $a1 electronic resource (226 p.) 311 $a3-0365-5210-3 311 $a3-0365-5209-X 330 $aBiopharmaceutical and pharmaceutical manufacturing are strongly influenced by the process analytical technology initiative (PAT) and quality by design (QbD) methodologies, which are designed to enhance the understanding of more integrated processes. The major aim of this effort can be summarized as developing a mechanistic understanding of a wide range of process steps, including the development of technologies to perform online measurements and real-time control and optimization. Furthermore, minimization of the number of empirical experiments and the model-assisted exploration of the process design space are targeted. Even if tremendous progress has been achieved so far, there is still work to be carried out in order to realize the full potential of the process systems engineering toolbox. Within this reprint, an overview of cutting-edge developments of process systems engineering for biopharmaceutical and pharmaceutical manufacturing processes is given, including model-based process design, Digital Twins, computer-aided process understanding, process development and optimization, and monitoring and control of bioprocesses. The biopharmaceutical processes addressed focus on the manufacturing of biopharmaceuticals, mainly by Chinese hamster ovary (CHO) cells, as well as adeno-associated virus production and generation of cell spheroids for cell therapies. 606 $aTechnology: general issues$2bicssc 606 $aHistory of engineering & technology$2bicssc 610 $aclonal cell population 610 $aphenotypic diversity 610 $ainoculum train 610 $auncertainty-based 610 $acell culture model 610 $abiopharmaceutical manufacturing 610 $aEscherichia coli 610 $ahybrid modeling 610 $amachine learning 610 $amodel-assisted DoE 610 $aquality by design 610 $aupstream bioprocessing 610 $asurface plasmon resonance (SPR) 610 $abioprocess 610 $amonitoring 610 $abiosensor 610 $aquality by design (QbD) 610 $aprocess analytical technology (PAT) 610 $abiotherapeutics production 610 $avaccines production 610 $aCHO DP-12 610 $acomputational fluid dynamics 610 $abioreactor characterization 610 $ahydrodynamic gradients 610 $aprocess development 610 $acritical shear stress 610 $aKolmogorov length scale 610 $aoperational space 610 $asensors 610 $acell culture 610 $aspectroscopy 610 $aPAT 610 $asmart biomanufacturing 610 $asoft-sensor 610 $aAdeno-associated virus 610 $atransfection 610 $aPEI 610 $acontinuous 610 $agene therapy 610 $amicrocarriers 610 $abioreactor 610 $atransient expression 610 $aspheroid strength 610 $a?-cells 610 $adiabetes 610 $ashear stress-guided production 610 $ahydrodynamic stress 610 $aGaussian processes 610 $aBayes optimization 610 $aPareto optimization 610 $amulti-objective 610 $aseed train 610 $aChinese hamster ovary cells 610 $acryopreservation 610 $amonoclonal antibodies 610 $aN?1 perfusion 610 $aprocess intensification 610 $aupstream processing 615 7$aTechnology: general issues 615 7$aHistory of engineering & technology 700 $aPo?rtner$b Ralf$4edt$01207271 702 $aMo?ller$b Johannes$4edt 702 $aPo?rtner$b Ralf$4oth 702 $aMo?ller$b Johannes$4oth 906 $aBOOK 912 $a9910595072803321 996 $aBioprocess Systems Engineering Applications in Pharmaceutical Manufacturing$93033986 997 $aUNINA