@inproceedings{WuKemper2016,
  author    = {Wu, Ziyi and Kemper, Hans},
  title     = {The optimal 48 V - battery pack for a specific load profile of a heavy duty vehicle},
  series = {8. Internationale Fachtagung Kraftwerk Batterie : 26. - 27. April 2016, M{\"u}nster, Deutschland},
  booktitle = {8. Internationale Fachtagung Kraftwerk Batterie : 26. - 27. April 2016, M{\"u}nster, Deutschland},
  year      = {2016},
  language  = {en}
}
@inproceedings{WulfhorstDuweMoehringetal.2016,
  author    = {Wulfhorst, H. and Duwe, A. and M{\"o}hring, S. and Jurca, O. and Tippk{\"o}tter, Nils},
  title     = {Analysis of pretreated biomass by differential scanning 132 calorimetry and multivariate data analysis},
  series = {New frontiers of biotech-processes (Himmelfahrtstagung) : 02-04 May 2016, Rhein-Mosel-Halle, Koblenz/Germany},
  booktitle = {New frontiers of biotech-processes (Himmelfahrtstagung) : 02-04 May 2016, Rhein-Mosel-Halle, Koblenz/Germany},
  publisher = {DECHEMA},
  address   = {Frankfurt am Main},
  pages     = {132},
  year      = {2016},
  language  = {en}
}
@article{WulfhorstDuweMerseburgetal.2016,
  author    = {Wulfhorst, Helene and Duwe, Anna-Maria and Merseburg, Johannes and Tippk{\"o}tter, Nils},
  title     = {Compositional analysis of pretreated (beech) wood using differential scanning calorimetry and multivariate data analysis},
  series = {Tetrahedron},
  volume    = {72},
  journal   = {Tetrahedron},
  number    = {46},
  publisher = {Elsevier},
  address   = {Amsterdam},
  doi       = {10.1016/j.tet.2016.04.029},
  pages     = {7329 -- 7334},
  year      = {2016},
  abstract  = {The composition of plant biomass varies depending on the feedstock and pre-treatment conditions and influences its processing in biorefineries. In order to ensure optimal process conditions, the quantitative proportion of the main polymeric components of the pre-treated biomass has to be determined. Current standard procedures for biomass compositional analysis are complex, the measurements are afflicted with errors and therefore often not comparable. Hence, new powerful analytical methods are urgently required to characterize biomass. In this contribution, Differential Scanning Calorimetry (DSC) was applied in combination with multivariate data analysis (MVA) to detect the cellulose content of the plant biomass pretreated by Liquid Hot Water (LHW) and Organosolv processes under various conditions. Unlike conventional techniques, the developed analytic method enables the accurate quantification of monosaccharide content of the plant biomass without any previous sample preparation. It is easy to handle and avoids errors in sample preparation.},
  language  = {en}
}
@article{ZhangHeimbachScheeretal.2016,
  author    = {Zhang, Jin and Heimbach, Tycho and Scheer, Nico and Barve, Avantika and Li, Wenkui and Lin, Wen and He, Handan},
  title     = {Clinical Exposure Boost Predictions by Integrating Cytochrome P450 3A4-Humanized Mouse Studies With PBPK Modeling},
  series = {Journal of Pharmaceutical Sciences},
  volume    = {Volume 105},
  journal   = {Journal of Pharmaceutical Sciences},
  number    = {Issue 4},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0022-3549},
  doi       = {doi.org/10.1016/j.xphs.2016.01.021},
  pages     = {1398 -- 1404},
  year      = {2016},
  abstract  = {NVS123 is a poorly water-soluble protease 56 inhibitor in clinical development. Data from in vitro hepatocyte studies suggested that NVS123 is mainly metabolized by CYP3A4. As a consequence of limited solubility, NVS123 therapeutic plasma exposures could not be achieved even with high doses and optimized formulations. One approach to overcome NVS123 developability issues was to increase plasma exposure by coadministrating it with an inhibitor of CYP3A4 such as ritonavir. A clinical boost effect was predicted by using physiologically based pharmacokinetic (PBPK) modeling. However, initial boost predictions lacked sufficient confidence because a key parameter, fraction of drug metabolized by CYP3A4 (ƒₘCYP3A4), could not be estimated with accuracy on account of disconnects between in vitro and in vivo preclinical data. To accurately estimate ƒₘCYP3A4 in human, an in vivo boost effect study was conducted using CYP3A4-humanized mouse model which showed a 33- to 56-fold exposure boost effect. Using a top-down approach, human ƒₘCYP3A4 for NVS123 was estimated to be very high and included in the human PBPK modeling to support subsequent clinical study design. The combined use of the in vivo boost study in CYP3A4-humanized mouse model mice along with PBPK modeling accurately predicted the clinical outcome and identified a significant NVS123 exposure boost (∼42-fold increase) with ritonavir.},
  language  = {en}
}