Scientists at the Technical University of Munich (TUM) are researching new digitally-assisted methods of treatment and approaches on how to handle big data in medicine - initial results are already being implemented in the operating theater. "Modern molecular medicine alone witnessed more data generated in 2015 than in the entire period from 1990 to 2005," explains Burkhard Rost, Professor of Bioinformatics at the TUM.
"And this is going to continue at this rate." However, up to now, when it comes to preparing, analysing and applying this treasure trove of data, we have lagged far behind the available technical possibilities.
We also lack the necessary algorithms and the ability to link diverse areas such as medicine and biology, on the one hand, and computer science, on the other. "A biologist cannot interpret the gigantic quantities of data on his or her own," stresses Hans-Werner Mewes, Professor of Genome-Oriented Bioinformatics, TUM. "Here you need bioinformatical methods."
At the TUM, a whole host of scientists from different disciplines have set themselves a target of collecting the data treasure trove from the life sciences and making it usable for researchers, patients, doctors and clinics. In addition, specialists are taking care of data security. Together with the mainframes at the Leibniz Supercomputing Center in Garching, the university has a unique infrastructure for bioinformatics and medical informatics.
At Professor Nassir Navab’s Chair for Computer Aided Medical Procedures & AR, researchers are working toward simplifying the assignment of such annotations, among other things. "Doctors and laboratory staff rarely have time to take care of processing their data," explains Shadi Albarqouni.
He has therefore developed a project, which enables large numbers of Internet users to make contributions. This process is called crowdsourcing and it allows anyone who has the time and the motivation to participate in the completion of certain digital tasks. In Albarqouni’s case, this means analysing histological tissue sections for breast cancer, for example.
Since, up to now, it has not been possible to determine the sensitivity of patients using genetic markers with any degree of reliability, a team from Wolf’s chair has developed sensors that measure in advance how strongly cells, which are taken from the patient, react to various chemotherapeutic agents.
Based on this effect, the doctor can then apply the active ingredient that is best suited to the individual case. The system is ready for use and is currently being tested in a preclinical study in cooperation with the Asklepios Clinic Barmbek in Hamburg. However, ideally, there would be a gene test for the patient to determine the correct chemotherapeutic agent automatically.
The ideal scenario would be precision medicine. This means aiming to have the focus on the individual characteristics of the patient, so that predictions, therapies and prognoses can be tailored precisely to the needs of the individual. In the long term, the doctor should be able to know which treatment best suits the patient based on his or her genetic profile.
However, there is still a long way to go yet. This is due to a second major error, namely the idea that the non-coding DNA fragments that are located between the known genes serve no purpose at all; this so-called "junk DNA" as it has been labeled. Researchers gradually discovered that parts of this DNA, still amounting to around 95% of the human genetic material, also perform important functions; for example, these parts deal with the turning on and off of genes and also contain information about the evolutionary development of the organism.
By analysing naturally occurring genetic variations in the proteins of the human body, both Hans-Werner Mewes and Burkhard Rost want to find out, for example, which mutations are responsible for rare diseases.
These are diseases that are rare if taken in isolation but affect about 5% of the population in total. They can surface very early in life - even before birth in many cases - and can accompany a person throughout their life. "They are almost impossible to detect using traditional methods; you usually need five to 20 years before getting a clinical diagnosis," explains Hans-Werner Mewes. "However, if the genetic defect is found, you know in 25% to 40% of cases exactly whether therapeutic measures can specifically be taken."
Digitalised medical data is not only used for research, but it can also help to ease the pressure on doctors directly if they can be put in virtual contact with chronic patients, in particular. In recent years, Bernhard Wolf and his team have developed a prototype for this with the COMES system.
It uses various sensors to collect individual data and transmits it to a database. This data is processed and evaluated there. If a value exceeds the predefined threshold values, the system automatically alerts the attending doctor or the responsible nursing service on their cell phone.
In this way, pulse and blood pressure can be monitored and you can also determine from the skin resistance whether the person is adequately hydrated. Similarly, the device can transfer blood sugar levels and monitor weight.
What is always important here is that the patient must release the data; that is, he or she is not forcibly monitored. Because COMES is designed in such a way that, on the one hand, users can check their medical data using a database and release it to the doctor when required; on the other hand, they receive additional information themselves via feedback systems.
Another example is the intelligent tooth splint called SensoBite. This is a dental splint, as prescribed by a dentist in the event of bruxism during sleep. A piezoelectric sensor system is integrated into this splint to measure the masticatory movements.
A radio transmitter sends the measured data wirelessly to a receiver that is the size of a matchbox and is located on the body of the patient or where he or she sleeps. A USB interface can be used to transfer the stored data to the computer of the attending doctor or a vibration signal can be sent to the person sleeping via biofeedback. In this way, doctors can analyse the causes of the grinding or patients can break the grinding habit directly themselves.