AI is at the centre of a more accessible, personalised form of healthcare.
Germany’s life sciences industry has already proven itself to be globally renowned, successful, and innovative… But how is AI impacting German life sciences?
The digital transformation of Germany’s life sciences industry was accelerated by the Covid-19 pandemic and the need for reform in outdated processes in healthcare.
A number of steps have been taken in Germany to push digital transformation in the region, such as recently published laws that make it easier for doctors to hold video consultations and reimburse patients for using digital health apps.
Additionally, hospitals are now able to apply for funding to improve their digital infrastructure from a fund of €4.3bn, with an emphasis on patient data.
Part of this focus on digital transformation, however, has rested heavily on the use of AI as part of these shifts and strategies.
Pharmaceutical giant Bayer AG, for example, has signed off on ‘Future Concept’ plans to expand and develop the technology portfolios of its Germany-based businesses by 2025.
Part of this expansion is a pledge to invest significantly in AI and data sciences, as an element of its overall $1.4bn digital transformation strategy.
The role of AI in Bayer AG’s wider vision is to create an ecosystem that enables faster, more direct access to innovations, alongside modernising and expanding research centres in Berlin and Wuppertal.
In short, as organisations across Germany’s life sciences industry look to create digital transformation strategies, AI will be a significant factor.
As mentioned above, Germany has made significant strides to keep up with the rapid pace of digitalisation as a means to truly modernise the life sciences industry.
The demand for AI is, in many ways, linked to a necessity to drive innovation in the industry.
Researchers from Heidelberg University, the German Cancer Research Center, and the European Molecular Biology Laboratory have founded a new research unit aiming to support AI research in life sciences.
This unit is part of the European Laboratory for Learning and Intelligent Systems (ELLIS), which is focused on developing new AI methods and linking technologies with data from the life sciences and making them available to the research community.
Such efforts are highly significant to a wider trend in Europe, as more countries endeavour to strengthen their competitiveness in AI research specifically.
For German life sciences organisations, this makes AI a clear driver of innovation and a competitive advantage and differentiator.
German life sciences companies are hardly short of options when it comes to technology applications.
However, AI offers opportunities across elements of life sciences, from clinical trials and disease analysis to disease identification and optimised manufacturing processes.
Put simply, AI is giving German life sciences companies the chance to explore elements of their processes that may have previously been inefficient or ineffective, whilst offering others the chance to explore new and highly specialised fields.
Bayer AG, for example, is a German pharmaceutical and life sciences company using AI in drug discovery and development.
Bayer AG’s platform, Bayer AI for Life, combined data analytics and machine learning algorithms to identify potential drug targets, optimise clinical trials and predict drug efficacy.
In Bayer AG’s case, AI is being used to better characterise disease and the appropriate patient populations whilst also allowing for clinical trials that are faster, less costly and more patient-centric.
Similarly, Merck KGaA is using AI in drug discovery, clinical trials, and manufacturing to accelerate drug discovery and optimise the manufacturing process.
Though the costs involved in using AI currently can be high, many in the industry hope that as competition emerges globally, costs will come down and open up greater opportunities in the area.
AI has a strong association with personalised healthcare, and for good reason.
There are a number of ways in which AI is catalysing personalised healthcare in a way that could significantly impact the ability to treat rare or complex diseases, such as:
Predictive analytics using a patient’s medical history, genetic testing and other sources to predict their risk of developing certain conditions, which can then be used to create personalised prevention strategies.
Wearables and medical devices powered by AI that provide real-time monitoring and feedback for patients that can be used towards personalised recommendations or health monitoring.
Reducing healthcare costs by optimising treatment plans on an individual, unique patient-by-patient basis.
AI has even been utilised to analyse patient data for diabetes management, using blood glucose levels, diet and exercise habits, and medication regimens to identify any areas that require changes in medication or lifestyle.
Though personalised healthcare is still in its early stages in Germany, AI will undoubtedly play a key role in its development in the years to come.
There has been no shortage of investment and progress when it comes to AI in German life sciences.
The next stage of AI adoption is reliant primarily on overcoming barriers around the privacy of data and the legality and ethics around the data used for AI algorithms.
As with many other regions adopting AI, Germany will have to consider how to approach the use of AI in a sustainable, ethical manner to be able to see it reach its true potential in the life sciences industry.
Regardless of the ways in which AI will adapt in German life sciences, it is clear that Germany will remain at the forefront of AI innovation in the industry, with so many leading businesses adopting AI and committing to digital transformation.
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