Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Abstract

I will start by briefly introducing the concept of precision oncology as well as its mode of action, the molecular tumor board (MTBs), which interdisciplinarily issues individualized evidence-based treatment recommendations for cancer patients. These recommendations encompass patient-drug matches and patient-clinical trial matches. Precision oncology programs are registries, and secondary use of the data aggregated across patients enables cohort analyses via multi-omics characterization as well as the development of novel predictive and prognostic markers, which, in turn, can be used to enrich patients for clinical trials and/or provide the basis for future individualized treatment recommendations in MTBs. Traditionally this whole cycle often uses bulk technologies, but single cell technologies may be at reach for clinical translation soon. One such example is a modern application of flow cytometry, in particular spectral flow cytometry, which makes use of the full emission spectrum of fluorophores for enhanced deconvolution and consequently higher combinatorial complexity, for the analysis of single cell landscapes as well as cellular interactions.

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Referent:? PD Dr. Dr. Daniel Hübschmann

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Kurzbiographie

PD Dr. Dr. Daniel Hübschmann is a physicist, mathematician, and physician with clinical experience in pediatric oncology. He heads the Innovation and Service Unit at the German Cancer Research Center (DKFZ) as well as the research group Computational Oncology in the Molecular Precision Oncology Program (MPOP) at the National Center for Tumor Diseases (NCT) Heidelberg and the group Pattern Recognition and Digital Medicine at the Heidelberg Institute for Stem cell Technology and Experimental Medicine (HI-STEM). His research focuses on bioinformatics, clinic-multi-omics integration, pattern recognition, machine learning, cancer genomics, DNA repair and cellular interactions and precision medicine. One of his core translational activities, together with his team, is the responsibility for the fast-track bioinformatics workup for molecular tumor boards of patients in several precision oncology programs at NCT Heidelberg.

Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Abstract

Artificial intelligence (AI) is increasingly integrated into regulated industrial environments, such as pharmaceutical manufacturing. At a production site for the synthesis of active pharmaceutical ingredients (APIs), an image-based AI system was developed to support microbiological process control. This system applies random forest algorithms trained on microscopic images to assess the morphology of microorganisms involved in biotechnological processes for in-process contamination detection.

The AI system functions as a decision-support tool, enabling laboratory experts to identify signs of contamination or process instability. Through real-time assessment and pattern recognition, it enhances process robustness, reduces the risk of production loss, and supports continuous quality in accordance with Good Manufacturing Practice (GMP) standards.

Unlike generative AI models, this AI is specifically designed for supervised visual analysis, ensuring full human oversight and compliance with relevant regulations. Different aspects matter, such as the development pipeline, training and validation methodology, and integration of the model into an existing GMP framework, illustrating how image-based AI can improve reliability and efficiency in pharmaceutical production without compromising patient safety.

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Referent:? Dr. Yvonne Gladbach

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Dr. Yvonne Saara Gladbach is a Data Scientist in the pharmaceutical industry, currently working at Bayer AG in Bergkamen, Germany, where she develops and implements artificial intelligence (AI) systems for manufacturing processes in regulated pharmaceutical production. She completed her Ph.D. at the University of Heidelberg in collaboration with the University Medical School Rostock, focusing on the integration of multi-omics data for predicting novel drug targets in Acute Lymphoblastic Leukemia (ALL).

Her academic background includes extensive research in bioinformatics, next-generation sequencing (NGS) analysis, and systems biology, with applications to oncology and neurodegenerative diseases. Dr. Gladbach holds an M.Sc. in Bioinformatics from Saarland University, where she developed a bioinformatic pipeline for automated bacterial characterization using MLST schemes. Her interdisciplinary expertise bridges computational biology, machine learning, and pharmaceutical manufacturing, with a strong focus on data integrity and digital transformation in GMP-regulated environments.

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Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Abstract

Artificial intelligence has the potential to transform neurosurgical practice, yet a significant gap remains between data scientists who develop algorithms and models and clinicians who face real-world problems. The lecture will address the importance of closing this gap to create meaningful, clinically integrated AI tools. Drawing on the experience of the GEIBAC research group at Río Hortega University Hospital, several ongoing projects will be presented, including GlioMap, CereBleed, SonoDetect, SAH-Mortality, and NeuroRIS-AI, which leverage machine/deep learning and computer vision applied to multimodal neuroimaging. The session will highlight practical strategies for interdisciplinary collaboration, data curation, validation, and clinical deployment of AI systems within hospital workflows, aiming to translate computational innovation into improved neurosurgical care.

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Referent:? Dr. Santiago Cepeda

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Kurzbiographie

Dr. Cepeda is a neurosurgeon specialized in brain tumor surgery, trained at Hospital 12 de Octubre in Madrid, and awarded a cum laude PhD from Universidad Complutense, where he also completed a postgraduate diploma in translational oncology. He currently serves as coordinatior of the brain tumor scientific committee and staff neurosurgeon at Río Hortega University Hospital.?

He leads the Biomedical Imaging and Computational Analysis Group (GEIBAC), part of the Biomedical Research Institute of Valladolid (IBioVall), and serves as Principal Investigator in nationally and regionally funded R&D projects focused on artificial intelligence and neuroimaging. With expertise in programming and data science, Dr. Cepeda bridges clinical neurosurgery and computational analysis to develop AI-based tools for glioblastoma, intraoperative ultrasound, and neurovascular pathology. https://geibac.uva.es/

Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Abstract

Sometimes regulatory science is seen as paperwork. This is a misunderstanding of what it is, what it can science and why it is critical in digital health futures.?What is the largest barrier to progress in digitalisation and the?implementation of AI-enabled technologies in German university clinics?and private hospitals? Is it the absence of appropriate tools and technologies or the absence of the ability to develop them? No. I argue and I present work to show that it is largely?the?lack of coordinated efforts that bring?implementation science together with practical operational leadership. That bring together?quality oversight and regulatory strategy with the development and implementation of tools that?are?highly focused on patient and doctor needs and?are?deeply integrated with each?other and with human workflows. I will present work focused on this theme and bring in our parallel research themes on cybersecurity and health?data sharing.

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Referent:? Prof. Dr. Stephen Gilbert

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Kurzbiographie

Prof. Dr. Gilbert worked in senior MedTech and Digital Heath roles in industry for 5 years, before returning to academia in 2022 in Dresden, Germany as Europe's first full Professor of Medical Device Regulatory Science for AI and Digital Health, where he teaches and conducts research. His research goals are the advancement of regulatory science in digital medicine and AI-enabled medical devices. Innovative digital approaches in healthcare must be accompanied by innovative regulatory and oversight approaches to ensure speed to market, to maximise the access of patients to life saving treatments, while at the same time ensuring safety on market.?His team?uses?data science approaches for literature research. They?develop new solutions and approaches for monitoring AI and digital health solutions, and for the evaluation of existing methods and regulatory frameworks.

Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Abstract

Real-time magnetic resonance imaging (rt-MRI) represents a major advancement in pediatric radiology, enabling ultrafast image acquisition at up to 50 frames per second — comparable to ultrasound — while maintaining the high spatial and tissue contrast characteristic of MRI. This innovative technique effectively eliminates motion artifacts caused by physiological or voluntary movement, allowing diagnostic-quality imaging in awake, unsedated infants and young children. In clinical practice, rt-MRI has already demonstrated substantial benefits, reducing the need for anesthesia or sedation in children under six years of age by up to 40%. Applications now span from rapid brain imaging to dynamic visualization of the beating heart, breathing lungs, swallowing mechanisms, and joint motion. The technique opens new diagnostic possibilities, including real-time assessment of thoracic wall malformations and cerebrospinal fluid dynamics, while offering parents and clinicians a faster, safer, and radiation-free imaging alternative. As rt-MRI continues to integrate into pediatric workflows, it is poised to transform routine imaging protocols and expand the horizons of functional and dynamic assessment in children.

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Referent:? PD Dr. Daniel Gr?fe

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Kurzbiographie

PD Dr. med. Daniel Gr?fe studied medicine at the universities of Regensburg and Dresden, obtaining his medical license in Dresden in 2007. In 2012, he became a board-certified specialist in paediatrics at the University Hospital Dresden and the Heart Center Leipzig. He later expanded his expertise, earning additional qualifications as a specialist in radiology and paediatric radiology, as well as in paediatric cardiology.

At Leipzig University Hospital, Dr. Gr?fe serves as a senior physician at the Institute of Paediatric Radiology. His work focuses on the field of imaging in children — from prenatal diagnostics and newborns to adolescents. Scientifically, he is engaged in research on advanced imaging techniques, including real-time MRI applications in paediatric medicine.

Through his multidisciplinary background in paediatrics, cardiology, and radiology, Dr. Gr?fe combines clinical expertise with innovative imaging methods to provide the best possible diagnostic care for infants, children, and adolescents.

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Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Abstract

In this talk I will first give a brief summary of the principles governing why we move slowly or fast, and how these principles also affect the way we make decisions. I will then present recent studies in which we investigated how the speed of decision-making is modulated in cortico-subthalamic networks and whether neural control of decision-making speed is related to movement speed. Finally, I will present a behavioural framework for abnormally slow movements as observed in Parkinson’s disease based on concepts from utility theory and optimal control. This framework might be useful for future studies investigating the neural mechanisms underlying changes in decision-making and motor control in Parkinson’s disease and other neuro-psychiatric disorders.

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Referent:? Dr. Damian Herz

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Kurzbiographie

Damian Herz, MD PhD, is a Neurologist and Senior Physician at the University Hospital Heidelberg with vast experience in research including 5 years of post-doctoral training at the University of Oxford, U.K., under supervision of Peter Brown. His translational research focuses on the neurobiological basis of clinical impairment in Parkinson’s disease and how this can be ameliorated using neuromodulation in particular adaptive deep brain stimulation approaches. He has published >50 peer-reviewed manuscripts in high-impact journals such as Nature Communications, Current Biology, Plos Biology, Brain and Annals of Neurology (>4000 citations, H-index: 29). Clinically, he mainly works with patients with Neurodegenerative disorders, in particular Parkinson’s disease, and deep brain stimulation.

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Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Abstract

Understanding how genes shape metabolism is key to uncovering the mechanisms underlying metabolic health and disease. Our group focuses on disentangling the complex interactions between metabolic pathways, genetic regulation, and environmental influences across tissues and organs. By integrating multi-omics, fluxomics, and metabolic phenotyping data, we aim to build a comprehensive picture of metabolic regulation and its perturbations in disease states, with a particular emphasis on Type 2 Diabetes. Through these integrative approaches, we seek to advance the mapping of genetic-metabolic wiring and uncover new insights into metabolic dysfunction.

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Referent:? Dr. Dominik Lutter

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Kurzbiographie

Dr. Dominik Lutter is Group Leader of Computational Discovery Research at the Institute for Diabetes and Obesity, Helmholtz Munich. He earned his PhD in Biology from the University of Regensburg in 2009, focusing on computational methods to identify regulatory networks in mammalian transcriptomes. After postdoctoral positions in systems biology and computational modeling at Helmholtz Munich, he joined the Institute for Diabetes and Obesity in 2013 and established his research group in 2015. His research combines computational biology, multi-omics integration, and metabolic phenotyping to elucidate the genetic and regulatory architecture of metabolism and its dysregulation in diseases such as Type 2 Diabetes.

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Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Abstract

Artificial intelligence (AI) and biotechnology are two of the six key technologies of Germany's High-Tech Agenda. Both fields receive strong support in Bavaria through dedicated research clusters and numerous initiatives. Their success is evident in internationally successful research projects with disruptive solutions in the development of generative AI and the increasing use of agents. Biotechnology has also succeeded in bringing new products and therapies into clinical development and onto the medical market in recent decades, thanks to numerous innovative startups. The application of AI will accelerate the translation of biomedical research into further products. To this end, BioM has launched the AI4Biotech initiative, which aims to more closely connect these two key technologies.

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Referent:? Prof. Dr. Dr. Ralf Huss

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Kurzbiographie

Prof. Dr. med. Dr. h.c. Ralf Huss is Managing Director of BioM Biotech Cluster Development GmbH in Martinsried near Munich and member of numerous boards of trustees.

Until the end of 2022, he was the Founding Director of the Institute for Digital Medicine (IDM) and Professor of Pathology and Molecular Diagnostics at Augsburg University Hospital. Before joining the Faculty of Medicine in Augsburg, he worked for many years in the biopharmaceutical and diagnostics industry at Roche Diagnostics and AstraZeneca, including as Head of Pathology and responsible for the development of AI-supported algorithms for predicting treatment response. Prof. Huss was an Associate Professor at the Institute for Regenerative Medicine in Wake Forest, Winston-Salem, North Carolina, and continues to lecture on "Biomaterials and Bioresponsive Polymers" at the Department of Chemistry at the Technical University of Munich. Prof. Huss is also an Honorary Professor at University College Dublin in Ireland.?

In his more than 30 years of academic and industrial activity, Prof. Huss has published more than 180 publications, books and book chapters on immunology, cancer and stem cell research, as well as on the use of artificial intelligence in digital medicine.

Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Abstract

This talk presents an ongoing PhD project on enhanced clinician-AI Computer-Aided Diagnosis (CADx) framework designed to improve transparency and trust in medical imaging. The system integrates concept-based explainability, visual attribution methods, and a multi-XAI agreement metric that aligns pixel-level and concept-level reasoning. A large language model further enables interactive, clinician-driven queries grounded in these explanations. Together, these components create a unified, interpretable CADx system aimed at supporting reliable clinician-AI collaboration and improving diagnostic decision-making.

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Referent:? Yuki Hagiwara

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Yuki Hagiwara is a research scientist at the Fraunhofer Institute of Cognitive Systems, IKS at the department of Trustworthy Digital Health and a current PhD candidate in the Technical University of Munich under Prof. Dr. Mario Trapp at the Chair of Engineering Resilient Cognitive Systems. Her doctoral research focuses on improving the trustworthiness, safety, and explainability of AI-driven diagnostic tools, aiming to strength clinician-AI teamwork and support informed clinical decision-making in the development of enhanced clinician-AI collaborative systems for computer-aided diagnosis. Her work emphasizes the critical need for interpretable and robust AI models in healthcare, where patient safety is paramount.? In recognition of her contributions to the field, she was ranked in the top 1 % of highly cited researchers in the year 2022.

Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Abstract

The development of microfluidic "lab-on-a-chip" (LOC) systems offers enormous potential for a wide range of applications in biotechnology, bioprocess engineering, and medicine. Demand for the use of microfluidics for biotechnological applications continues unabated, as such systems enable precise and rapid manipulation of living cells and other biological samples. Three-dimensional (3D) printing technologies are an attractive alternative to conventional microfabrication techniques because they can produce complex structures with high resolution in a short time. Therefore, 3D printing is particularly driving the development of LOC prototypes. The availability of biocompatible printing materials also enables the fabrication of customized microsystems for biological and biomedical applications. Our research at the Chair of "Technical Biology" focuses on the development of 3D-printed microfluidic systems that can be directly integrated into bioprocesses. In my talk, I will present some examples of the current developments and applications. For instance, 3D-printed micromixers enable rapid and homogeneous mixing of cells, particles, and detergents. By integrating 3D-printed spiral separators, continuous separation of animal cells at the end of a cultivation is achieved. Another focus is the development of 3D-printed biosensor systems, which are used for online detection and monitoring of analytes in cell culture processes through specific aptamer sequences and show great potential for use in medical diagnostics (point-of-care).

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Referent:? Prof. Dr. Janina Bahnemann

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Janina Bahnemann is Professor of Life Sciences and Head of the Chair of Technical Biology at the Institute of Physics, University of Augsburg, Germany, since 2022. She studied Life Science (Bachelor and Master studies) at the Leibniz University Hannover from 2004 to 2009. In 2014, she completed her PhD at the Institute of Bioprocess and Biosystems Technology at Hamburg University of Technology. In 2015, Janina Bahnemann joined the California Institute of Technology (Caltech, USA) as a postdoctoral fellow, where she worked at the Institute for Environmental and Applied Sciences in the group of Prof. Michael Hoffmann. In 2017, she was awarded the competitive Emmy Noether fellowship of the German Research Foundation (DFG). From 2017 to 2022, she headed an independent Emmy Noether junior research group at the Institute of Technical Chemistry, Leibniz University Hannover, and held a substitute professorship at the Faculty of Technology at Bielefeld University from 2021 to 2022. Her research focuses on biotechnology, cell culture and microsystems technology as well as the development of lab-on-a-chip systems and biosensors for biotechnological and medical applications.

Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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Referent:? Prof. Dr. Philipp Altrock

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Veranstaltungsort: H?rsaal N2045 (Fakult?t für Angewandte Informatik)

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