Medical progress is facing a crisis: the significant investments into the development of new therapies in recent years have not resulted in an increase in approvals of innovative drugs. The number of newly launched medications has already been stagnating for some time, although pharmaceutical industry investments into research and development have multiplied. Furthermore, the decoding of the human genome, which celebrated its tenth anniversary last year, has not changed anything. It caused a wave of euphoria, but until now has unfortunately not delivered what it had promised.
In individual areas, there have been impressive advances: only 10 years ago, many new active ingredients were failing during clinical testing due to an insufficient pharmacokinetic human profile. Today, this is virtually no longer the case, because the constant improvement of forecasting models in preclinical research, with the aid of in silico, in vitro and cellular models, enables a prediction. Conversely, however, there is an increase in failures, especially in the advanced stages of clinical development. Active ingredients repeatedly fail in late clinical trials because the prognosis and medical benefits that are hoped for are not achieved. Such failures are extremely expensive and not least, therefore, an opportunity for intensive analyses. What must pharmaceutical research do differently to improve the situation?
Obviously, even after years of intensive research, it has not been possible to use preclinical models to make predictions about the effect in humans. The transfer of knowledge from pure research to the situation in humans is lacking, or the transition of the research results, in short: the translational medicine is missing.
Translational medicine is a complex science and is still in its infancy. Nevertheless, even in its “developmental stage”, I consider it to be by far the most important research direction within the life sciences, the principles of which require further research, development and standardisation, if we want to avoid studies continuing to fail in clinical reality. Essential for this is the research and classification of biomarkers, i.e. analytically measurable signal compounds of the human body. These are specific to a disease and the disease course can ultimately be predicted by observing their alteration, often before the actual disease has even come to light. Cholesterol values or blood sugar levels, for example, are among the best known markers. Such established surrogate markers are by no means sufficient for the medicine of the future. Already very early in the research and development of a new drug, we must be able to recognise whether it works similarly to the postulated molecular principle, and whether as a medication it can also fulfil its purpose at the molecular level in humans. Therein lies the challenge, which is why completely new analysis methods, reaching far beyond traditional clinical chemistry, are necessary.
Conversely, the results of the clinical trials will have and must have considerably stronger influence on current basic research than in the past. Just like “from bench to bedside”, clinical knowledge must be back-translated “from bedside to bench” into new findings, thus allowing the efficacy of a new active ingredient to be recognised in cellular models. Further, we must learn to better understand how different individuals react to different active ingredients. Tailor-made, personalised medicine is not possible without better understanding of the various molecular principles in different patient groups. Personalised and translation medicine are inseparably linked with one another: both share the goal of a better understanding of the molecular causes of our lives. If it is possible for them to be better coordinated with one another in the future, so that the strengths of individual research disciplines work together better and that doctors and scientists communicate with each other more efficiently, we will – I am both confident and hopeful – be able to create more medical innovations for the good of the patient.
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