Beer on prescription? How the right data can prevent disease

Imagine that in a few years you wake up and suddenly suffer from unbearable pain. You go to the doctor, who diagnoses you with kidney stones and subsequent kidney failure. This would change your life. But what if it were possible to determine today that you will become ill in a few years? Through analysis and data, you could act years in advance - and long before the onset of the disease. The doctor could recommend various measures such as an improved diet, special monitoring of certain parameters, diuretics - and perhaps there would even be beer on prescription. After all, it is well known that the drink can be healthy in moderation and can "flush" the kidneys. And so, you wouldn't get sick in the first place. That is the goal of predictive medicine.

Over the past few centuries, medicine has advanced rapidly, and the average life expectancy worldwide has increased greatly as a result. While many diseases used to be a death sentence, today we have them well under control and thanks to vaccinations, for example, we no longer get many diseases at all, or only in a weakened form.

Predictive medicine - various applications

Predictive medicine is also about preventing the outbreak of a disease. To do this, one looks at the data of affected people, of people who are on the verge of the outbreak of the disease and of healthy people. In this way, a precise picture of the disease is obtained, and patterns emerge from which it is possible to identify which warning signals may indicate a predisposition or an outbreak. With the help of these findings, it is then possible to act before the onset of the disease.

However, predictive medicine is also about preventing complications during a disease that has already broken out. In addition to data such as a patient's age, sex and weight, biological, histological, and genetic characteristics are also considered to enable an individually tailored therapy with the greatest possible success and the fewest possible complications. Data from other patients who did not develop complications during the same disease are also important for this. Based on their data, researchers can draw conclusions and use them to enable better treatment of patients with the disease.

Predictive medicine is also used in drug development.  Since every immune system reacts uniquely, a drug also works differently from patient to patient. It is therefore important for drug developers to be able to predict the effect as accurately as possible. To this end, active ingredients are tested on virtual patients on the computer. The resulting data can be used to determine how a drug is distributed in the human body and how it is metabolized. With the help of these tests on virtual patients, drug development becomes more effective and safer.

Predictive medicine is also used in areas such as oncology, cardiology and diabetology. In the case of some genetic predispositions to disease, such as some tumor syndromes, gene sequencing is used to filter out mutation carriers even before a disease occurs. Algorithms that consider both genetic and environmental factors are used to identify patients who are particularly at risk. These people can then take part in preventive programs, undergo regular checkups, and thus avoid contracting the disease or its severe course.

Predictive technologies can therefore help in many cases to predict disease outbreaks or progressions and to make individual therapy decisions for patients.

Where are we today - and is this just the beginning?

With the help of wearables, it is already possible for us to collect important medical data about ourselves "on the side" throughout the day and night. When do we sleep, how do we sleep, how high or low is our blood pressure, what is our temperature, how do we eat, what was the course of an illness? We can measure all this without much effort, in fact, most of the time without even realizing it. Our fitness tracker can alert us to cardiac arrhythmias, and the nutrition app warns us if our diet is too high in sugar.

But we are far from reaching the end of the possibilities. Predictive medicine can make a decisive contribution to improved patient care. The basic prerequisite is digitization of the healthcare system with modern information and communication technologies that make it possible to collect large amounts of data anonymously and process it in such a way that the findings can be used to improve or even save human lives. To accomplish this, digital solutions must be found, and new work processes established. Always with the goal in mind: to enable medicine that can respond to a patient's individual needs and is able to prevent diseases before they occur. In this way, predictive medicine can form the cornerstone for a new kind of medicine that moves away from the pure treatment of diseases toward preventive medicine from which everyone can benefit.