Geomer (Germany)

Abstract Personalized cell therapies engineer millions of a patient’s T cells to recognize and kill cancer cells using a patient derived cancer-targeting T cell receptor (TCR). The results can be impressive: in an early trial a patient with late stage metastatic breast cancer refractory to chemotherapy was completely cured of cancer 1. Unfortunately the process of identifying a suitable cancer-targeting TCR for a patient is labor intensive, slow and thus expensive, taking 3-6 months in a commercial setting 2. While pipelines utilizing cancer genome sequencing identify high quality, neoepitope-specific TCRs, the long turnaround time is too slow to be of clinical utility for many patients, and too expensive for widescale use. We used >100,000 TCRs to train the ‘predicTCR’ machine learning classifier to identify tumor-reactive TCR clonotypes form single-cell sequenced tumor infiltrating lymphocytes (TILs) samples. predicTCR is over 85% accurate at detecting tumor-reactive TCRs across diverse tumor types and sequencing technologies 3. predicTCR is antigen agnostic, recognizing tumor-reactive T cells clonotypes in minutes. We then developed makeTCR: a rapid, modular TCR cloning platform to manufacture candidate tumor-reactive TCRs in as little as 24 hours 4. Using makeTCR, candidate TCRs’ tumor killing capacity is validated and TCRs prioritized using autologous T cells and either patient cancer cells or individualized patient-derived tumor organoids (IPTOs) 5. We have combined these platforms to generate the 2T2T pipeline, enabling a 2 week turnaround to patient-specific TCR therapy using experimentally validated TCRs. Our tools are available to the scientific community at https://predictcr.com and https://maketcr.com. 1. Zacharakis et al (Nature Medicine 2018). Immune recognition of somatic mutations leading to complete durable regression in metastatic breast cancer 2. Foy et al (Nature 2023). Non-viral precision T cell receptor replacement for personalized cell therapy. 3. Tan et al (Nature Biotechnology 2024). Prediction of tumor-reactive T cell receptors from scRNA-seq data for personalized T cell therapy. 4. Hamberger et al (biorxiv 2025). makeTCR: A Modular Platform for Rapid, Flexible, Scalable, Single-Step T Cell Receptor Synthesis. 5. Peng et al (Cell Stem Cell 2025). Individualized patient tumor organoids faithfully preserve human brain tumor ecosystems and predict patient response to therapy. Citation Format: Chin Leng Tan, Tamara Boschert, Marie-Therese Neuhoff, Moritz Hamberger, Amelie C. Dietsch, Katherina Lindner, Claudia Maldonado-Torres, Alina Errerd, Isabel Poschke, John M. Lindner, Hai-Kun Liu, Lukas Bunse, Michael Platten, Edward W. Green. 2T2T: 2 week turnaround to personalised TCR therapy: Rapid identification, validation and prioritization of patient-specific, cancer-targeting TCRs [abstract]. In: Proceedings of the AACR Immuno-Oncology Conference (AACR IO): Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2026 Feb 18-21; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2026;14(2 Suppl):Abstract nr B006.

The study showcases the evolution and versatility of two-photon absorption (2PA) in 3D printing. Using the in-situ material exchange system MergeOne system, we successfully fabricated diverse structures and analyzed laminar flow dynamics with fluorescence microscopy. Computational flow dynamics simulations confirmed the observed behavior. We demonstrated lateral multi-material micro-lens printing, along with precise control over material exchange and polymerization parameters. This approach enhances design flexibility and functionality, particularly in additive manufacturing, marking significant advancements in commercial 2PA technology.

Abstract The transboundary region of the Iishana system in the western Cuvelai Basin, between southern Angola and northern Namibia, is frequently affected by floods at irregular intervals. As a result, the predominantly rural, subsistence farming population has experienced crop failures, human, and economic losses. To date, very little is known about the generation of floods, flood concentration, and stormwater drainage dynamics in this region. In this study, 2D‐hydrodynamic modeling was applied to reconstruct one of the latest major flood events during the rainy season from November 2008 to March 2009 in order to study the runoff behavior and interconnectivity of the Iishana system. The model focused on the eastern part of the Iishana system, which was most affected by floods and flood damage due to the high population density in and around Oshakati, the regional capital. Two main streams were identified noteworthy because they merge and subsequently affect Oshakati. Regarding the simulated flood event water depths vary from 0.1 m to 14 m, with an average of 0.2 m, while water depths above 5 m were attributed to borrow pits. The inundation area ranged up to 1860 km2 and the amount of water left after the rainy season on March 25th, 2009, was determined between 0.116 and 0.547 km3, depending on the amount of evapotranspiration considered in the model. Thus, in the Angolan part of the Iishana system, significantly larger quantities of water are available for longer periods of time during the subsequent dry season, whereas the system in Namibia stores less water, resulting in a shorter water retention period.

Abstract Vietnam is exposed to different types of floods that cause severe economic losses, damage to infrastructure, and loss of life. Reliable information on the drivers, patterns and dynamics of flood risk is crucial for the identification, prioritization and planning of risk reduction and adaptation measures. Here, we present a systematic review of existing flood risk assessments in Vietnam. We evaluate the current status, persisting gaps, and challenges regarding the understanding and assessment of flood risk in the country. The literature review revealed that: (i) 65 % of the reviewed papers did not provide a clear definition of flood risk, (ii) assessments had a tendency to prioritize physical and environmental drivers of risk over social, economic or governance‐related drivers, (iii) future‐oriented assessments tended to focus on hazard and exposure trends, while vulnerability scenarios were often lacking, (iv) large and middle‐sized cities were assessed more frequently than others, (v) only few studies engaged with relevant local stakeholders for the assessment of risk and the development of potential solutions, and (vi) ecosystem‐based adaptation and flood risk insurance solutions were rarely considered. Based on these findings, we point out several directions for future research on flood risk in Vietnam.

Abstract. This paper proposes a novel approach to facilitate air quality aware decision making and to support planning actors to take effective measures for improving the air quality in cities and regions. Despite many improvements over the past decades, air pollutants such as particulate matter (PM), nitrogen dioxide (NO2) and ground-level ozone (O3) pose still one of the major risks to human health and the environment. Based on both a general analysis of the air quality situation and regulations in the EU and Germany as well as an in-depth analysis of local management practices requirements for better decision making are identified. The requirements are used to outline a system architecture following a co-design approach, i.e., besides scientific and industry partners, local experts and administrative actors are actively involved in the system development. Additionally, the outlined system incorporates two novel methodological strands: (1) it employs a deep neural network (DNN) based data analytics approach and (2) makes use of a new generation of satellite data, namely Sentinel-5 Precursor (Sentinel-5P). Hence, the system allows for providing areal and high-resolution (e.g., street-level) real-time and forecast (up to 48 hours) data to inform decision makers for taking appropriate short-term measures, and secondly, to simulate air quality under different planning options and long-term actions such as modified traffic flows and various urban layouts.

We conducted a high-density arrayed CSAMT survey to delineate active fault in the eastern foot of Tsugaru Mountains in Japan. The survey purpose is to delineate subsurface structure of this area including blind thrust as materials of predicting the magnitude of an earth quake. In this area, the seismic reflection survey was conducted. The CSAMT survey line was a part of seismic survey line and the length was 4.6 km. We set 93 scalar measurement stations at intervals of 50 m so as to be able to capture steep structures. We used Geode EM3D as receivers and GeoTx20 as a transmitter, manufactured by Geometrics. Geode EM3D receiver is multi-channel and distributed EM survey instruments. We set 6 receivers array at maximum. Each receiver can collect 3 scalar measurements of adjacent stations. Hence we can acquire 18 stations during a procedure of transmitting 33 kinds of frequencies from 0.125 Hz to 8192 Hz. Such array CSAMT measurement contributed to improve measurement efficiency. The result of resistivity section clearly presents a gap of low resistivity zone. From integrated interpretation with seismic reflection, we concluded that the gap of low resistivity structure seems to be caused by blind thrust. Presentation Date: Wednesday, September 27, 2017 Start Time: 3:55 PM Location: Exhibit Hall C, E-P Station 2 Presentation Type: EPOSTER

Two‐dimensional (2D) hydraulic models are widely used as tools for flood hazard mapping and also to support flood risk management. Yet, only few models are capable of using high‐resolution terrain data (raster‐based Digital Terrain Model with 1 m spatial resolution) on a large scale (hundreds of square kilometres and more). Central to the model approach presented in this article is the raster‐based 2D model High Performance Computing version of FloodArea (FloodAreaHPC), which allows for multicore processing, thus being able to model large areas without having to make compromises regarding spatial details. The model has been applied for inundation modelling of rivers, dike breaks, and heavy rainfall runoff (pluvial flooding). For the latter case, the model is coupled with a hydrologic preprocessor data base which provides spatially and temporally variable runoff coefficients based on land use, soil, and slope. The case study presented in this study has an area of 144 km2 and is located close to Dortmund in Western Germany. The modelling results of two heavy rainfall scenarios, presented in analogue and digital flood hazard maps, were used in a Public Relations (PR) campaign to inform the public about pluvial flood risk and possible mitigation measures.

Dike failure events pose severe flood crisis situations on areas in the hinterland of dikes. In recent decades the importance of being prepared for dike breaches has been increasingly recognized. However, the pre-assessment of inundation resulting from dike breaches is possible only based on scenarios, which might not reflect the situation of a real event. This paper presents a setup and workflow that allows to model dike breachinduced inundation operationally, i.e. when an event is imminent or occurring. A comprehensive system setup of an operational modelling unit has been developed and implemented in the frame of a federal project in Saxony-Anhalt, Germany. The modelling unit setup comprises a powerful methodology of flood modelling and elaborated operational guidelines for crisis situations. Nevertheless, it is of fundamental importance that the modelling unit is instated prior to flood events as a permanent system. Moreover the unit needs to be fully integrated in flood crisis management. If these crucial requirements are met, a modelling unit is capable of fundamentally supporting flood management with operational prognoses of adequate quality even in the limited timeframe of crisis situations.

Abstract. Since 2004, Halji village, home of the oldest Buddhist Monastery in north-western Nepal, has suffered from recurrent glacial lake outburst floods (GLOFs). A sudden englacial drainage of a supraglacial lake, located at a distance of 6.5 km from the village, was identified as the source of the flood. The topography of the lake basin was mapped by combining differential Global Positioning System (DGPS) measurements with a structure-from-motion (SFM) approach using terrestrial photographs. From this model the maximum filling capacity of the lake has been estimated as 1.06 ×10^6 m3 with a maximum discharge of 77.8 m3 s−1, calculated using the empiric Clague–Mathews formula. A simulation of the flooded area employing a raster-based hydraulic model considering six scenarios of discharge volume and surface roughness did not result in a flooding of the village. However, both the village and the monastery are threatened by undercutting of the river bank formed by unconsolidated sediments, as it already happened in 2011. Further, the comparison of the GLOF occurrences with temperature and precipitation from the High Asia Reanalysis (HAR) data set for the period 2001–2011 suggests that the GLOF is climate-driven rather than generated by an extreme precipitation event. The calculation of geodetic mass balance and the analysis of satellite images showed a rapid thinning and retreat of Halji Glacier which will eventually lead to a decline of the lake basin. As the basin will persist for at least several years, effective mitigation measures should be considered. A further reinforcement of the gabion walls was suggested as an artificial lake drainage is not feasible given the difficult accessibility of the glacier.