Within biological cells, molecules are constantly in motion. Investigating these motions, however, is still difficult, due to the fact that these processes occur on very small length and time scales. To overcome these challenges, researchers from HITS and MPI-P have developed a simulation method that works rapidly and can predict chemical processes in cells with high precision. Their findings have been published in Nature Communications.

Computer simulations and Artificial Intelligence are the main pillars of the “SIMPLAIX” collaboration, initiated by the Heidelberg Institute for Theoretical Studies (HITS). Together with colleagues from Heidelberg University and Karlsruhe Institute of Technology, HITS researchers are addressing challenges in the simulation of biomolecules and molecular materials by pooling their expertise in multiscale computer simulation and machine learning.

Computer simulations and Artificial Intelligence are the main pillars of the “SIMPLAIX” collaboration, initiated by the Heidelberg Institute for Theoretical Studies (HITS). Together with colleagues from Heidelberg University and Karlsruhe Institute of Technology, HITS researchers are addressing challenges in the simulation of biomolecules and molecular materials by pooling their expertise in multiscale computer simulation and machine learning.

In ovarian cancer, immunotherapies using checkpoint inhibitors have so far been effective in only a small number of patients. Researchers at the HI-TRON Mainz* have now discovered that lipid metabolism processes in the tumor microenvironment play a decisive role in how well such therapies work. The findings open up new avenues for using immunotherapies in a more targeted manner, increasing their effectiveness, and overcoming resistance.

In a study, a team of researchers show that groups of magnetic microrobots can generate fluidic forces strong enough to rotate objects in different directions without touching them. These microrobot swarms can turn gear systems, rotate objects much larger than the robots themselves, assemble structures on their own, and even pull in or push away many small objects. The work was now published in Science Advances.

CorTec GmbH, a pioneer in active implantable medical technologies, announced the successful second implantation of its proprietary Brain-Computer Interface system in a clinical trial. The implantation follows neurological gains observed in the study’s first participant. This represents another key milestone to evaluate CorTec’s fully implantable closed-loop BCI platform for therapeutic applications.

Artificial intelligence allows tracing the evolution of genetic control elements in the developing mammalian cerebellum. An international research team led by biologists from Heidelberg University as well as the Vlaams Instituut voor Biotechnologie and KU Leuven has now developed advanced AI models that can predict the activity of these elements based solely on their DNA sequence.

Scientists at the German Cancer Research Center (DKFZ), Heidelberg University Hospital (UKHD), and Mannheim University Medical Center (UMM) are presenting a method that enables artificial intelligence (AI) to learn how to transfer medical image data from animals to humans. This “xeno-learning” could help make surgical procedures safer and more precise in the future – without relying on human training data.

Recreating tumour tissue in the laboratory as realistically as possible and developing new approaches for personalised cancer medicine: A total of 20 doctoral students in the life sciences and ten Medicine students will be researching this in the new "Organoid-Based mOdelling of Solid Tumours" research training group. They want to gain a better understanding of cancer and better predict the course of the disease and the effect of…

Researchers at the Hopp Children's Cancer Center Heidelberg, the German Cancer Research Center, the Heidelberg Medical Faculty of Heidelberg University, and Heidelberg University Hospital have taken a decisive step toward more precise diagnosis of brain tumors. The latest version of the AI-based Heidelberg CNS Tumor Methylation Classifier can identify more than 180 tumor types —twice as many as the previous version.

Inside cells, RNAs and proteins form biomolecular condensates. These droplets are essential for organizing cellular life, yet why some RNAs cluster more readily than others has remained unclear. Disruptions in condensate formation are linked to developmental defects, cancer, and neurodegenerative diseases. Researchers at KIT have now identified a new class of RNA called smOOPs and gained a better understanding of how biomolecular condensates form

CELLnROLL is a spin-off from the Max Planck Institute for Intelligent Systems. The newly founded company develops a high-precision microrobotic-based cell sorting system to help clinicians make fast, affordable, and informed decisions for cancer diagnostics. Now, the project has received €865,000 in funding through the EXIST Transfer of Research program, a funding program initiated by the German Federal Ministry for Economic Affairs and Energy.

A new software enables brain simulations which both imitate the processes in the brain in detail and can solve challenging cognitive tasks. The program was developed by a research team at the Cluster of Excellence ‘Machine Learning: New Perspectives for Science’ at the University of Tübingen. The software thus forms the basis for a new generation of brain simulations which allow deeper insights into the functioning and performance of the brain.

Heidelberg researchers identify local outbreak indicators and develop new regional modeling approach. The highly pathogenic avian influenza virus infection – commonly known as bird flu – primarily affects birds. Mammals, however, are also increasingly infected. This increases the probability that the virus will cross over to humans.

Enhancing human perception of the imperceptible - 28/08/2025

AI-driven imaging expands possibilities in surgery

Doctors frequently experience a restricted view of the surgical field, particularly during endoscopic procedures. A novel technique developed by Prof. Dr. Lena Maier-Hein's team at the DKFZ in Heidelberg integrates spectral imaging with AI-driven data analysis. This innovation facilitates accurate tissue differentiation and delivers real-time insights into organ function.

If the brain no longer responds properly to insulin (insulin resistance), this can lead to overweight, diabetes, and Alzheimer's disease. Researchers at the DZD in Potsdam and Tübingen have discovered small chemical modifications to genetic material (epigenetic changes*) in the blood that indicate how well the brain responds to insulin. These markers could help to detect insulin resistance in the brain – by means of a simple blood test.

Designing protein binders from scratch has long been a daunting challenge within the field of computational biology. Researchers have now developed an innovative, training-free pipeline that uses the fundamental principle of shape complementarity to design site-specific protein binders, which are then optimised to fit precisely onto chosen target sites. The researchers tested this on proteins linked to cancer.

A team of researchers from HITS and MPIP have developed a model that learns how to generate proteins whose structures are highly flexible, even with patterns that are uncommon in natural proteins. Their work, presented at the International Conference on Machine Learning (ICML), marks a step towards the goal of designing new proteins for applications in biotechnology, therapeutics and environmental research.

AI-supported image recognition accelerates identification of zebrafish mutants - 16/07/2025

EmbryoNet AI automatically identifies developmental disorders

In complex organisms, embryonic development is tightly regulated by intricate signalling pathways. When these pathways are disrupted, they can lead to characteristic developmental defects that are not easy to detect with the naked eye. Developmental biologist Prof. Dr. Patrick Müller from the University of Konstanz has developed EmbryoNet, an AI-powered software tool that uses image analysis to reliably identify such developmental disorders.

Tübingen achieves remarkable success and has good chance of maintaining its University of Excellence title – Top research in three areas to be sustained from other sources of support.

A building with 7400 m² of research space for robotics and artificial intelligence is being built on the Max Planck Campus in Büsnau. Researchers from the Max Planck Institute for Intelligent Systems (MPI-IS) and the University of Stuttgart will be working there with partners from science and industry as well as start-ups from 2027.

Baden-Württemberg AI Alliance - 08/04/2025

Achieving widespread use of AI

Artificial intelligence presents both opportunities and risks. The Baden-Württemberg AI Alliance is dedicated to fostering collaboration among AI stakeholders to ensure that AI solutions deliver tangible benefits to citizens and businesses across the state. The alliance will also place greater emphasis on advancing AI applications within the healthcare sector.

A recent article by Prof. Dr. Martin Haimerl and Prof. Dr. Christoph Reich of Furtwangen University shows that machine learning (ML) in medicine is often evaluated without a comprehensive risk assessment. The authors investigated the extent to which current scientific papers include risk-based metrics in the evaluation of AI models for medical devices.

The MedTech company KARL STORZ announces the acquisition of the innovative software manufacturer Innersight Labs Ltd. (ISL) headquartered in London. In addition to state-of-the-art endoscopes, high-end medical devices, and integrated solutions for the operating room, KARL STORZ is also continuing to expand in innovative software solutions. Its large customer base, including top-class physicians worldwide, can now look forward to 3D models.

Vicinity Bio: Optimisation of cancer diagnostics - 27/11/2024

Comprehensive histological diagnostics through high-dimensional imaging and artificial intelligence

Microscopic examination of tissue samples is essential, particularly in tumour diagnostics. The Tübingen-based company Vicinity Bio leverages cutting-edge imaging technologies combined with machine learning to generate comprehensive datasets of individual cells from tissue sections. This approach not only helps identify more targeted therapies but also enhances our understanding of cellular functions and processes within tissues and tumours.