In the pharmaceutical industry, digitization is pushing new developments that will directly affect patients: technologies such as artificial intelligence, machine learning and cloud platforms can play an important role in clinical trials, drug development, and their commercialization and distribution play.
For example, Medidata offers cloud-based clinical trial solutions. Customers include almost all major pharmaceutical companies – “18 of the top 25 companies in the industry use our platform for their studies,” said Christian Hebenstreit, Medidata’s Managing Director and Senior Vice President EMEA. He talked to LEAD about the tech trends in the pharmaceutical industry.
LEAD: What technological innovations are there in the pharmaceutical industry?
Christian Hebenstreit: As a cloud provider, we mainly deal with data that is collected in clinical trials. Clinical trials are conducted by pharmaceutical companies as prescribed by the authorities before they can sell a new drug. At the moment, the data volume in the pharmaceutical sector is growing significantly in this area – the data volume of the past year has been higher than the previously recorded data volume.
And this trend will continue over the next few years: Thanks to new innovations such as smartwatches and fitness bracelets, you can capture more and more data – in real time. In addition, studies with ever greater number of participants are collected. This results in a plethora of data that needs to be processed. Algorithms and AI can then help evaluate the data weasel and detect anomalies. This allows the results to be analyzed faster and more accurately. And all of this could speed up the process of approving new drugs.
What new possibilities arise from this?
Pharmaceutical companies that use our platform can share with each other the – anonymous – data they collect. This is currently accepted by about two-thirds of our customers. Because they have access to a plethora of data that they can use for their studies.
What I find particularly exciting: This also creates the opportunity to work with synthetic Kotrollgruppen. In clinical trials in humans, it is usually the case that there is a control group that receives a placebo or marketed drug instead of the new drug. Now you can virtually visualize a control group using historical data. This will give all study patients the new drug and no one has to worry about getting a market-ready drug for a placebo, which I think is ethically better, especially in studies on serious illnesses.
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In addition, pharmaceutical companies are better at researching rare diseases. Investing in so-called rare diseases is often too expensive for drug manufacturers – they can quickly put billions in the sand. With a large data pool and the help of AI, the trials can be conducted cheaper and more efficiently. As a result, in addition to cancer and diabetes research, more can be done in the area of rare diseases and, hopefully, new treatment methods will soon be developed.
What is also beneficial in the research of rare diseases: With the new technologies, data can be collected effortlessly even if the subjects are scattered or living in rural areas.
“With a large data pool and the help of AI, the trials can be conducted cheaper and more efficiently.”
What needs to be taken into account when digitizing in this industry?
Two points: It is often said that the pharmaceutical industry is suffering from an innovation backlog and is reacting too slowly to the new technologies. I see it in a very different way: it is precisely this industry that is particularly open to innovation – because if manufacturers do not regularly launch new medicines and react quickly, they are out. And new technologists can help them prepare for the future.
The authorities are also trying to stop new technologists from getting in the way. Rather, they push companies to focus more on new technologies such as AI so they can work more efficiently and develop new medicines faster.
What about privacy?
Data protection is important to us and data is anonymized during distribution. However, within the DSGVO the pharmaceutical sector plays a special role: Data location and the right to forget are not possible for study participants. Yes, the data is needed for the clinical studies, as it would be useless without the complete results of all patients.
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And the competition?
Since the market is regulated, there are competitors, but the number remains manageable. We are fine, we are growing and we are not afraid.
What new developments are outside the research area?
Research and commercialization will be more closely connected – especially in data science. In this way, you can also work with real-time data during marketing and decide at an early stage how to launch a product on the market. I also think that we need a different payment system – such as value-based pricing, which could play a major role in the pharmaceutical sector. For example, the health insurance company would only pay for a drug if the patient also gets well.
What about other innovations like Blockchain?
Of course we also discuss that. At the moment, we do not see any point of reference for clinical studies, where other topics such as machine learning are more relevant. It will certainly soon be used in other areas of the pharmaceutical industry, such as logistics.
What’s in it for the patients?
Better medicines will come to market in a shorter period of time. The studies will be more granular, the treatment better – in the near future, a lot will happen in this area.
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