From anywhere and with just a mobile phone, anyone can become an air traffic controller, or at least a virtual air traffic controller. One can follow the world traffic flow of airplanes live and find out where an aircraft is coming from and where it is headed. One just has to take advantage of the millions of pieces of data that fly across the Internet. This is the magic power of Big Data. Artificial intelligence then enters the picture to find patterns and give meaning to the massive and heterogeneous information stream. Together, these two technologies have embarked on a colossal mission far removed from their usual commercial applications: finding treatments for diseases such as cancer.
When MIT professor Regina Barzilay was diagnosed with breast cancer, she not only lost her personal life, but it also turned her research upside down. In the endless shuffling between hospitals, she realized that most of the information being recorded about patients was not being used. “Clinical decisions are often based on clinical trials, that is, on the 3% of patients participating in them. This means that the entire experience of what happens to 97% of patients is not being used. How would Amazon work if it discarded 97% of the data? I think we are sitting on a gold mine of data that we are not using,” she maintained during a visit to Madrid as a jury member of the BBVA Foundation Frontiers of Knowledge Award.
Barzilay specializes in teaching natural language to machines, teaching to read and write in our language they that only understand ones and zeros. Thus she decided to leave aside the rest of her projects and focus on teaching these smart devices to read the notes that the doctors wrote in the pathological reports, so that they could be moved to a data table where they could be searched for information. In this way, if a patient has breast cancer and has to receive a treatment, one can first check the database to see what treatments other women with the same tumour have received and how they have reacted to them. There was no reason to start from scratch. “We had better technology to recommend a lipstick than to help you to prevent breast cancer. That had to be changed,” says the MIT researcher.
Genetic Big Data
One of the most important discoveries that the extensive decades-long research into cancer has brought us is that it is not just one disease, but rather many different diseases. There is no single liver cancer, or a single type of pancreatic tumour. The origin of the cancer in each patient has its own causes. For this reason, treatments would be more effective if they were as personal as the disease. This medicine of precision is what the sequencing and analysis of the genome is directing us towards.
If one knows exactly in which gene or genes the mutation that has resulted in cancer is produced—if it has a genetic origin—the treatment may be more accurate, more certain. “It is possible to know what the molecular cause of your cancer is. It is no longer just breast cancer, but we know exactly which genes are mutated and which have to be attacked. The next challenge is to know which drugs can treat each mutation,” explains Sergi Beltrán, director of the bioinformatics unit at CNAG (National Genome Analysis Centre), the Spanish centre dedicated to this mission.
This technology has allowed the experts to apply another work methodology: to start without established hypotheses, tracing mutations in all genes. Prior to the advent of the sequencers and super computation that this technique requires, physicians had to hypothesize that a particular disease was caused by a mutation in four or five genes. The results could only be one of two: approve or refute it.
A drug discovered by artificial intelligence
This new work methodology is also being applied by Niven Narain, president and co-founder of Berg, a US pharmaceutical start-up. This company has developed a new anti-cancer drug (against pancreatic, breast, liver or brain cancer) called BPM 31510, which has been discovered by an algorithm. Berg has collected samples of cancerous and healthy tissue from 1,000 patients, and has processed all this data with artificial intelligence, which has proposed a treatment. “We have essentially reversed the scientific method. We allowed the biological data from the patients to lead us to the hypotheses,” Narain told Wired magazine. BPM 31510 will now begin clinical trials to test its effectiveness, but according to its creator, they have already saved an incredible amount of time and money by using these technologies.
In addition to the start-ups, all major technology companies have already begun to apply Big Data and artificial intelligence to the service of health. Alphabet, Google’s parent, is using machine learning to collect samples of thousands of healthy volunteers in order to understand what makes them healthy. Apple, meanwhile, is taking advantage of the data from millions of iPhone users using ResearchKit and CareKit (the latter to share information directly with their doctors). Microsoft is developing tiny sensors that can be worn on the skin to transmit biometric data to remote health monitors.
Thus, cancer research is becoming one of the areas of research that has most benefited from these new technologies, but it is not the only one. Big Data and artificial intelligence, combined with genetic analysis, allow researchers to search for and find patterns among patients with rare diseases, who may be separated by distance but carry the same mutation. The ultimate goal is to create a huge digital medical data library, a kind of Big Data of medicine, which respects the privacy of the patient but accelerates diagnosis and treatment. The cure for cancer is not yet known, but many researchers now indicate that it will be found within our data.
Beatriz Guillén for Ventana al Conocimiento