Big Data collection and analysis, supported by artificial intelligence and machine learning technologies, are experiencing a major expansion, revolutionizing several industrial sectors, particularly the pharmaceutical and health industry. “Predictive analysis” is perhaps the most attractive field of application nowadays, along with digital checkups and diagnosis systems. Being able to anticipate illnesses and treatments of tomorrow, starting with information on symptoms gathered today, is the new frontier for the healthcare industry.
Forseeing disease from the search engine
Recently brought to public light -and also reported by the German newspaper Süddeutsche Zeitung – the case in which Microsoft proposed a correlation between user searches of specific disorders and / or symptoms on search engines and the identification of areas with a high incidence of cancers . The research analyzed the data of nearly 10 million anonymous users: in 5-15% of cases, US scientists were able to diagnose the disease. Scholars have put together search terms with past user searches to identify who may have a tumor and still doesn’t know or is not sure. The used algorithm did not show real use under real conditions, but the potential was clear and it triggered a heated discussion in amongst professionals in the area, as noted in a journal on Journal of Oncology Practice.
In fact, the issue raises many questions. Microsoft researchers argue that a web-based diagnosis is simple and convenient, but they also recognize that the psychological impact of these warnings often results in conflicting results. Early diagnosis does not always meet expectations, especially in the case of very serious illness, where patients won’t live long. They will probably know more about their fate, but perhaps it is best to doubt if it’s are not at a medical report based on scientific data.
Merck and Palantir: two “colossi” in the quest for Big Data
Certainly, predictive analyses can help diagnose and treat. Californian Data Analysis giant, Palantir Technologies Inc., has recently concluded an unprecedented agreement with the German pharmaceutical company Merck KGaA to develop and distribute new cancer medicines faster and more efficiently. Specifically, the agreement anticipates three areas of use for Big Data: in drug research and development, from a collaborative analysis and data collection platform to create more effective and customized medicines faster for specific pathologies; Improving patient experience by generating large-scale data collection of those involved in therapies, personalizing treatments and increasing their effectiveness; In the distribution and supply chain of medicines, for the agile handling of drug storage worldwide.
Project trials will be followed in real time throughout the prototype cycle, reducing the risk of harm associated with unwanted effects. And the information will be made available to external subjects and departments, encouraging the emergence of further research and knowledge exchange.
If certified scientific studies have not yet been created, there is no doubt that the relationship between Big Data and Pharma can bring great results. The revolution has only just begun.