The Children’s Clinic and Children’s Polyclinic at the Dr. von Hauner Children’s Hospital is a reference center for many children with severe, chronic, complex illnesses. We are committed to the legacy of Dr. August von Hauner, who laid the foundation stone in 1846 to help the children of Munich as a “poor doctor”. Today, we not only treat children with acute and chronic illnesses from Munich and Bavaria, but also serve patients from Germany and all over the world—regardless of their ethnic or national origin.
We promote highly specialized, child-oriented and holistic medicine. We are not satisfied with the current state of knowledge, but work together with many regional, national and international partners to develop a new era of personalized precision medicine in the interests of our patients and their families.
Children are our future—but by virtue of being children, children also defy the principles that shape our world today. At Hauner Children’s Hospital, we want to promote respect for the reality of children’s lives.
As a university hospital, we take our academic mission seriously. We can only improve medicine through the rationality of science. Children also have a right to participate in medical progress. Together with our patients and their families, we therefore want to understand the basics of diseases in order to derive new ways of diagnosis, treatment and prevention. The paediatrics of the future will be personalized, predictive and participatory precision medicine - we are working on this as an integral partner in the new German Centre for Child and Adolescent Health.
Children with rare diseases, until now the “orphans of medicine”, can become pioneers of a new era against the backdrop of epochal innovations in the various disciplines of life sciences, biotechnology and data sciences. Our clinic wants to give hope to all those children whose diseases cannot yet be cured!
SCIVIAS Study
The SCIVIAS study at the Dr von Hauner Children’s Hospital focuses on the examination of children with rare diseases in order to identify biomarkers that enable early diagnosis. Various methods are used for this purpose, including imaging of the fundus oculi, OMICS analyses of blood and urine and artificial intelligence methods for data analysis. The aim is to use a simple and painless examination to detect a disease before the child is sick.
Data collection within the SCIVIAS study involves several steps and methods that are carefully carried out in order to obtain accurate and meaningful information.
- Imaging of the fundus oculi: High-resolution images of the back of the eye are taken to identify eye problems that may indicate certain genetic diseases. Modern equipment and technologies are used to obtain precise and detailed images.
- OMICS analyses: This includes various “OMICS” technologies such as genome sequencing, transcriptome analysis, proteome and metabolome analysis. These methods enable the comprehensive analysis of genetic, transcriptional and metabolic profiles of the children. By analysing this data, potential biomarkers that indicate certain diseases can be identified.
- Artificial intelligence (AI) methods: Artificial intelligence methods such as machine learning are used to process the large and complex data sets and identify patterns or biomarkers. These algorithms help to extract relevant information from the data and recognise diagnostic patterns.
The security and processing of data are of crucial importance, particularly in the area of data protection and ethics. The following measures are taken:
- Anonymisation and pseudonymisation: personal identification data is removed or encrypted to ensure patient anonymity.
- Secure data transmission and storage: Secure protocols are used for the transmission and storage of data to ensure its integrity and confidentiality.
- Access control: Access to data is strictly controlled and only granted to authorised persons to prevent misuse or unauthorised disclosure.
- Ethics committees and data protection guidelines: The study will be overseen by ethics committees and clear privacy policies will be established to ensure that the rights and privacy of participants are protected.
Through these careful measures in data collection, processing and security, the SCIVIAS study endeavours to achieve high-quality and ethically acceptable results that can contribute to improving the early detection and treatment of rare diseases in children.
For more Information, please see Scivias Study | Comprehensive Childhood Research Center (ccrc-hauner.de)!
AMIGO
The “AMIGO: Advanced Medical Intelligence for Guiding Orphan Medicine“ project, which was launched and is managed by the Dr. von Hauner Children’s Hospital in Munich, aims to give hope to children with rare diseases, the so-called orphans of medicine.
When a child comes to the clinic, a large amount of data is collected as part of the medical history and diagnosis using standardized questionnaires, blood and urine tests and physical examinations. Genomes, proteomes, metabolomes or (as in the SCIVIAS study) OCT images are recorded. The data is processed and analyzed by our bioinformaticians. In most cases, this leads to a diagnosis. However, if the child suffers from a rare disease, we only find a cause for the disease in 30% of cases. This is usually of genetic origin. For more than 95% of rare diseases, there is no tested and approved medication. This poses huge challenges for our medical staff, as well as the children and their families. Although progress in medicine is advancing rapidly, it is impossible for clinicians to learn, analyze and incorporate the latest findings into diagnostics and treatment on a daily basis.
The AMIGO project should make it possible to generate more knowledge from the data. We want to use the information that the data gives us. At the same time, data protection should be safeguarded during this process. Federated machine learning (ML) opens up this possibility for us.
The decentralized approach allows us to keep the data securely in the clinic. This means that it is not issued or stored on cloud servers. The bioinformaticians at Dr. von Hauner Children’s Hospital pre-process the data. The FeatureCloud tool used enables data protection-compliant analysis of multi-institutional data. This means that the information (e.g. “Encoded child 1 has proteome values XY and metabolome values AB”) is read and processed.
By feeding our information into a so-called “Clinical Knowledge Graph”, scientists and doctors all over the world can benefit from this knowledge. Ideally, they will use the same technology and thus continuously expand the graph. The result is a network that always provides doctors with the latest information. This means that the data information can be used to make diagnoses more quickly and correctly. This opens up the possibility of targeted therapy and, in a broader sense, drug development.
However, it is not only pediatric medicine that can be raised to a new level by analyzing the data. The knowledge gained can also be used in adult medicine and thus support the prevention and treatment of cardiovascular or neurological diseases, for example.