Personalized medicine, supported by artificial intelligence (AI), marks a paradigm shift in healthcare. It aims to tailor therapies to individual patients by taking genetic, clinical and lifestyle factors into account. This approach promises not only more effective treatments, but also a reduction in side effects.
Basics of personalized medicine
The basis of personalized medicine lies in the analysis of large amounts of data provided by modern technologies such as high-throughput methods and imaging. AI systems can process this data efficiently and recognize patterns that are crucial for diagnosis and treatment planning. For example, genetic profiles of patients are used to identify specific disease characteristics and develop treatment strategies based on them [1][3].
Possible applications of AI in personalized medicine
1. diagnostics and early detection:
– AI-supported systems analyze imaging (e.g. MRI) and laboratory values in order to detect diseases at an early stage. One example is the early detection of sepsis by analyzing vital parameters such as heart rate and blood pressure [1][5].
2. therapy planning:
– AI makes it possible to customize treatment plans. In oncology, for example, the genetic profile of tumors is used to develop targeted therapies such as immunotherapies or combination therapies [4][7].
3. drug development:
– The development of new active ingredients is accelerated by AI. It helps to identify suitable drug targets and optimize chemical syntheses, which is particularly useful in precision oncology [7].
4. prevention and aftercare:
– Wearables and health apps continuously collect data on patients’ lifestyles and health status. This information is fed into AI systems to recommend preventive measures or monitor the success of treatment [2][6].
Advantages of AI-supported personalized medicine
AI-supported medical treatment offers a range of benefits that can significantly improve healthcare. By precisely analyzing individual patient data, treatments can be more targeted and therefore more effective. This means that patients receive customized therapies that are optimally tailored to their specific needs. At the same time, the risk of unwanted side effects is reduced, as the selection of medication and dosages is based on precise analyses.
Another advantage lies in the considerable time savings: AI systems can evaluate large amounts of data in the shortest possible time, enabling faster diagnosis and more efficient treatment planning [1][3]. This not only helps to improve patient care, but also leads to long-term cost savings in the healthcare system. More precise diagnoses and more targeted therapies reduce unnecessary treatments and hospital stays, allowing resources to be used more effectively [5].
Challenges and outlook
Despite the promising possibilities, there are still some challenges that make comprehensive implementation difficult. One key problem is data protection: the processing and storage of sensitive patient data requires the highest security measures and compliance with strict legal requirements. There are also regulatory hurdles. The approval of new AI-based applications is a complex process, as they are often embedded in various regulatory frameworks and require comprehensive clinical trials [4]. Interdisciplinary collaboration is also required. The integration of AI requires close cooperation between computer scientists, physicians and biologists to ensure that the technology is used efficiently and can support medical professionals in the best possible way.
Nevertheless, the future of personalized medicine is promising. Advances in single-cell analysis and projects such as the Human Cell Atlas could soon make it possible to adapt therapies even more precisely [6]. It is clear that as healthcare becomes increasingly digitalized, AI will play a central role in making the vision of tailored medicine for every patient a reality. However, in order to fully exploit this potential, ethical, regulatory and technical challenges must be consistently addressed.
Citations:
[1] https://scientifica.ch/ausstellungen/personalisierte-medizin-durch-kuenstliche-intelligenz/
[2] https://www.iks.fraunhofer.de/de/themen/kuenstliche-intelligenz/kuenstliche-intelligenz-medizin.html
[3] https://www.gesundheitsforschung-bmbf.de/de/personalisierte-medizin-9457.php
[4] https://healthcare-in-europe.com/de/news/ki-personalisierte-krebs-medizin-zulassung.html
[5] https://www.aok.de/pp/gg/versorgung/interview-ki-medizin-versorgung/
[6] https://www.helmholtz-munich.de/newsroom/im-fokus/die-zukunft-der-medizin-ist-personalisiert