Publications

2004 Jan; 19(1): 11-6
MORENO JB. ET AL.: Inhibition of neutrophil activity in cardiac surgery with cardiopulmonary bypass: a novel strategy with the leukocyte inhibition module

2004 Jun; 127(6): 1735-42
SCHOLZ M. ET AL.: In vivo inhibition of neutrophil activity by a FAS (CD95) stimulating module: arterial in-line application in a porcine cardiac surgery model

2005 Mar-Apr; 51(2): 144-7
SCHOLZ M. ET AL.: First efficacy and safety results with the antibody containing leukocyte inhibition module in cardiac surgery patients with neutrophil hyperactivity

2005 Apr 8; 329(2): 616-23
SCHULLER AM. ET AL.: Degradation of microvascular brain endothelial cell beta-catenin after co-culture with activated neutrophils from patients undergoing cardiac surgery with prolonged cardiopulmonary bypass

2005 May; 25(3): 331-42
SCHOLZ M. ET AL.: Fas/FasL interaction: a novel immune therapy approach with immobilized biologicals

2007 May; 27(3): 401-16
SCHOLZ M. ET AL.: Neutrophils and the blood-brain barrier dysfunction after trauma

2007 Oct; 4:21
ABDEL-RAHMAN U. ET AL.: Inhibition of neutrophil activity improves cardiac function after cardiopulmonary bypass

2008 Oct; 30 (4): 352-8
MARGRAF S. ET AL.: Neutrophil-derived circulating free DNA (cf-DNA/NETs): a potential prognostic marker for posttraumatic development of inflammatory second hit and sepsi

2009 Nov; 27(11): 1401-7
LÖGTERS T. ET AL.: Diagnostic accuracy of neutrophil-derived circulating free DNA (cf-DNA/NETs) for septic arthritis

2009 Jul; 32(1): 29-34
LÖGTERS T. ET AL.: Increased plasma kynurenine values and kynurenine: tryptophan ratios after major trauma are early indicators for the development of sepsis

2009-nov-198(4)-211-9-lögters-t-et-al-the-clinical-value-of-extracellular-traps

2009 Nov; 15: 183(10): 6198-6206
PAUNEL-GOERGUELUE A. ET AL.: McI-1-mediated impairment of the intrinsic apoptosis pathway in circulating neutrophils from critically ill patients can be overcome by Fas stimulation

2010 Apr; 20(7): 18
LÖGTERS T. ET AL.: Extracorporeal immune therapy with immobilized agionistic anti-Fas antibodies leads to transient reduction of circulating neutrophil numbers and limits tissue damage after hemorrhagic shock/resuscitation in a porcine model

2011 Mar; 216(3): 334-42
PAUNEL-GOERGUELUE A. ET AL.: Stimulation of Fas signaling down-regulates activity of neutrophils from major trauma patients with SIRS

2012 March; Vol. 7, Issue 8
SCHOLZ M. and LÜKING A.: A protein-stabilizing technology for enhanced antibody stability and antibody-binding profiles in a microchip array

2012 September; Vol. 15, Number 9
TSCHELIESSNIG R. ET AL.: Nano-coating protects biofunctional materials

2014 April; Vol. 32, Issue 19
SCHERLIESS R. ET AL.: Induction of protective immunity against H1N1 influenza A(H1N1)pdm09 with spray-dried and electron-beam sterilised vaccines in non-human primates

2014 July; Vol. 10, Issue 10, Meeting Report
DERWAND R.: Annual World Vaccine Congress 2014: A re-evaluation of the value proposition for increasing vaccine thermostability

2014 December, PLoS ONE 9(12): e115940. doi:10.1371/journal.pone.
WINDOLF C.D. ET AL.:Lysostaphin-Coated Titan-Implants Preventing Localized Osteitis by Staphyloccus aureus in a Mouse Model

Biotechnol. J. 2018, 13, 1700523
SCHOLZ M. ET AL.:Amino acid-based advanced liquid formulation development for highly concentrated therapeutic antibodies balances physical and chemical stability and low viscosity

European Biotechnology | Autumn Edition | Vol. 17 | 2018
"Formulation matters": Interview with LEUKOCARE´s CEO Michael Scholl about the impact of formulation on drug product performance.

Rentschler Biopharma SE / LEUKOCARE AG/ Informa Pharma Intelligence
"2018 Survey- Formulation in the Drug Product Development Process": 2018 Survey ‘Formulation in the Drug Product Development Process’, based on research from Informa Pharma Intelligence

European Biopharmaceutical Review January 2019, pages 28-36. © Samedan Ltd
ALTRICHTER J. ET AL: Exploring Amino Acid- Based and Stable Spray- Dried Vaccinations

Journal of Pharmaceutical Sciences 109 (2020) 818-829
REINAUER E. ET AL: Algorithm-Based Liquid Formulation Development Including a DoE Concept Predicts Long-Term Viral Vector Stability

Rentschler Biopharma SE/ Leukocare AG: Contract Pharma_54-58 Advertorial 1020
BHONSLE-DEENG L. and PETROPOULOS K.: Advanced Formulation Development by Design in the Context of Holistic Drug Production

F. Thomas,” Pharmaceutical Technology Europe 33 (4) 2021.

pharmtech.com/view/focusing-on-accelerated-formulation-strategies

S. Smith,” Liquid formulation bolstered by AI". ISSN 2644-2787

”A Specialist in Bioinformatics based Stabilization of All kinds of Biological Molecules". ISSN 2831-8331

JHEP Reports. 2023 Feb; 5(2): 100603
SACHERL J. ET AL: Efficient stabilization of therapeutic hepatitis B vaccine components by amino-acid formulation maintains its potential to break immune tolerance

ArchPharm 2023 Aug;356(8):e2300101
ABDEL-TAWAB M. ET AL: An exploratory study on the effect of mechanical stress on particle formation in monoclonal antibody infusions

Formulation development of protein biopharmaceuticals has become increasingly challenging due to new modalities and higher desired drug substance concentrations. The constraint in drug substance supply and the need for a holistic set of analytical methods means that only a small selection of excipients can be thoroughly tested in the wet lab. Until now there have been few in-silico tools developed to refine the candidate excipients selected for wet lab testing. To fill this gap we developed the Excipient Prediction Software (ExPreSo), a machine learning algorithm that suggests inactive ingredients based on the properties of the protein drug substance and target product profile. A dataset of over 350 peptide/protein drug formulations with proven long-term stability was created. The dataset was augmented with predictive features including protein structural properties, protein language model embeddings, and drug product characteristics. Supervised machine learning was conducted to create a model that suggests excipients for each drug substance in the dataset. ExPreSo could successfully predict the presence of the nine most prevalent excipients, with validation scores well above a random prediction, and minimal overfitting. A fast variant of ExPreSo using only sequence-based input features showed similar prediction power to slower models that relied on molecular modeling. Interestingly, an ExPreSo variant with only protein-based input features also showed good performance, proving that the algorithm was resilient to the influence of platform formulations in the dataset. To our knowledge, this is the first time that machine learning has been used to suggest biopharmaceutical excipients. Overall, ExPreSo shows great potential to reduce the time, costs, and risks associated with excipient screening during formulation development.