This is part I of a two-part blog series recapping the 2018 BIO International Convention.
At the 2018 BIO International Convention last week, it was clear what’s provoking scientific minds in industry and academia — or at least those of the Guinness-world-record-making 16,000 people in attendance. Artificial intelligence, machine learning and their implications for tailor-made medicine bubbled up across all BIO’s educational tracks and a majority of discussions about the future state of biotechnology. Panelists from Boston Children’s Hospital also contributed their insights to what’s brewing at the intersection of these burgeoning fields.
Isaac Kohane, MD, PhD, former chair of Boston Children’s Computational Health and Informatics Program, spoke on a panel about how large-scale patient data — if properly harnessed and analyzed for health and disease trends — is a virtual goldmine for precision medicine insights. Patterns gleaned from population health data or electronic health records, for example, could help identify which subgroups of patients who might respond better to specific therapies.
According to Kohane, who is currently the Marion J. Nelson Professor of Biomedical Informatics and Pediatrics at Harvard Medical School (HMS), we will soon be leveraging artificial intelligence to go through patient records and determine exactly what doctors were thinking when they saw patients.
“We’ve seen again and again that data abstraction by artificial intelligence is better than abstraction by human analysts when performed at the scale of millions of clinical notes across thousands of patients,” said Kohane.
And based on what we heard at BIO, artificial intelligence will revolutionize more than patient data mining. It will also transform the way we design precision therapeutics — and even vaccines — from the ground up. …
Over-prescribing has long been thought to increase antibiotic resistance in bacteria. But could much bigger environmental pressures be at play?
While studying the role of climate on the distribution of antibiotic resistance across the geography of the U.S., a multidisciplinary team of epidemiologists from Boston Children’s Hospital found that higher local temperatures and population densities correlate with higher antibiotic resistance in common bacterial strains. Their findings were published today in Nature Climate Change.
“The effects of climate are increasingly being recognized in a variety of infectious diseases, but so far as we know this is the first time it has been implicated in the distribution of antibiotic resistance over geographies,” says the study’s lead author, Derek MacFadden, MD, an infectious disease specialist and research fellow at Boston Children’s Hospital. “We also found a signal that the associations between antibiotic resistance and temperature could be increasing over time.”
During their study, the team assembled a large database of U.S. antibiotic resistance in E. coli, K. pneumoniae and S. aureus, pulling from hospital, laboratory and disease surveillance data documented between 2013 and 2015. Altogether, their database comprised more than 1.6 million bacterial specimens from 602 unique records across 223 facilities and 41 states. …
Ed. note: This morning at 8:15 EDT, Isaac Kohane, MD, PhD, will tell the audience at TEDMED 2013 about his goal of using every clinical visit to advance medical science.
To preview his talk, we’ve updated a past Vector story about SHRINE, a system Kohane helped develop to allow scientists to use clinical data from multiple hospitals for research.
Clinical research really comes down to a numbers game. And those numbers can be the bane of the clinical researcher. If there aren’t enough patients in a study, its results could be statistically meaningless. But getting enough patients for a study, particularly for rare diseases, can be a daunting challenge.
As we’ve discussed before, clinical research really comes down to a numbers game. But getting enough patients for a study, particularly for rare diseases, can be a daunting challenge. Similarly, it can be hard to tell whether observations made in just two or three patients, say a possible new medication interaction or a new diagnostic presentation, are part of a trend – one that’s worth grant money to study.