Revolution in Cancer Medicine: AI promotes personalized therapies!

Revolution in Cancer Medicine: AI promotes personalized therapies!

The progress in personalized medicine takes on a new dimension, especially in the area of ​​cancer treatment. An interdisciplinary research team from the Medical Faculty of the University of Duisburg-Essen (UDE), the Ludwig Maximilians University in Munich (LMU) and Bifold at the TU Berlin has developed an innovative approach to improve personalized cancer therapy using artificial intelligence (AI). This new approach could have far -reaching effects in the way treatments are tailored to the individual needs of patients.

The tailor -made medicine, which previously only based on a limited number of parameters, is revolutionized by analyzing over 15,000 patient data. The AI ​​model examines the interaction of 350 different parameters, which are obtained from medical pre-stories, laboratory values, imaging methods and genetic analyzes. This comprehensive database enables a deeper insight into the prognostic probabilities for different types of cancer. Professor Frederick Klauschen, director of the LMU pathological institute, emphasizes that consistent and comprehensive analysis methods are necessary to exploit the full potential of personalized medicine.

explainable AI for individual forecasts

A remarkable aspect of research is the use of explanable artificial intelligence (Xai), which enables to develop comprehensible forecasts. This technology makes it possible to make the specific contribution of each parameter understandable to the overall prognosis. Professor Jens Kleesiek emphasizes the relevance of this approach, especially when taking into account that rigid evaluation systems such as tumor stages are often used in Oncological-Clinical practice. The results of the study published in the Nature Cancer specialist magazine show promising perspectives for individualized cancer therapy.

The AI ​​model, which has already been validated with data of over 3,000 lung cancer patients, is able to determine a total forecast and at the same time show how the individual parameters interact with each other. The researchers also intend to use this method in emergencies in order to quickly evaluate diagnostic parameters. Professor Martin Schuler announced clinical studies to prove the actual benefits for patients.

challenges for implementation

Nevertheless, the AI-based personalized medicine also faces challenges. According to a report, the importance of new technologies is often underestimated by legislators and regulatory authorities, which leads to obstacle approval processes. Stephen Gilbert, Professor of Medical Device Regulatory Science, emphasizes the need for a fundamental change in these processes in order to enable faster implementation of innovative treatment methods.

Suggestions for improving the Situation include a re-evaluation of the benefit-risk assessments in highly personalized treatment approaches and the introduction of decision-making aids already proven in the USA in the EU. In addition, a more flexible adaptation of the security assessment of existing digital applications is stimulated. Various institutions are involved in this interdisciplinary challenge, including the EKFZ for digital health at the TU Dresden and the Fraunhofer Institute for Cell Therapy and Immunology.

The results of this groundbreaking research not only offer a new look at personalized cancer therapy, but also show urgent need for action in order to effectively integrate innovative approaches into clinical practice. Numbers and data -based therapy approaches could soon become a standard, which is crucial for improved treatment results.

For more information, you can view the studies and reports under the following links: University of Duisburg-Essen , lmu munich , and Healthcare in Europe .