Publications by authors named "Heiner Falkenberg"

Host cell proteins (HCPs) must be sufficiently cleared from recombinant biopharmaceuticals during the downstream process (DSP) to ensure product quality, purity, and patient safety. For monitoring of HCP clearance, the typical method chosen is an enzyme-linked immunosorbent assay (ELISA) using polyclonal anti-HCP antibodies obtained from an immunization campaign. This polyclonal reagent is a critical factor for functionality and confidence of the ELISA.

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For production of different monoclonal antibodies (mAbs), biopharmaceutical companies often use related upstream and downstream manufacturing processes. Such platforms are typically characterized regarding influence of upstream and downstream process (DSP) parameters on critical quality attributes (CQAs). CQAs must be monitored strictly by an adequate control strategy.

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Stem cell transplantation is a promising therapeutic strategy to enhance axonal regeneration after spinal cord injury. Unrestricted somatic stem cells (USSC) isolated from human umbilical cord blood is an attractive stem cell population available at GMP grade without any ethical concerns. It has been shown that USSC transplantation into acute injured rat spinal cords leads to axonal regrowth and significant locomotor recovery, yet lacking cell replacement.

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Ex vivo expansion of haematopoetic cells by application of specific cytokines is one approach to overcome boundaries in cord blood transplantation due to limited numbers of haematopoetic stem cells. While many protocols describe an effective increase of total cell numbers and the amount of CD34-positive cells, it still remains unclear if and how the procedure actually affects the cells' properties. In the presented publications, CD34-positive cells were isolated from cord blood and expanded for up to 7 days in media supplemented with stem cell factor (SCF), thrombopoietin (THPO), interleukin 6 (IL-6), and fms-related tyrosine kinase 3 ligand (FLT3lg).

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In large-scale proteomics studies there is a temptation, after months of experimental work, to plug resulting data into a convenient-if poorly implemented-set of tools, which may neither do the data justice nor help answer the scientific question. In this paper we have captured key concerns, including arguments for community-wide open source software development and "big data" compatible solutions for the future. For the meantime, we have laid out ten top tips for data processing.

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