As Strong explained, in the post-World War 2 era, exposure to thousands of chemicals in our everyday lives have changed our body systems leading to measurable molecular change.
By Harsha Baruah
Data analytics in healthcare does not just save money, it also saves lives. Whether it is to run clinical trials for a miracle cancer drug, track treatment procedures or ensure precise diagnostics solutions, scrutinising millions and millions of bits of data is a given. No wonder then that when Melissa Strong, founder and CEO of biotechnology firm Indiomics, set off to identify exposure to which everyday chemicals could lead to critical illnesses, she turned to data analytics for an answer.
As Strong explained, in the post-World War 2 era, exposure to thousands of chemicals in our everyday lives have changed our body systems leading to measurable molecular change. Her field of study, epigenetics, is a big user of analytics and machine learning, culminating in personalised dashboards of volunteers on their exposure levels and their impact.
Strong and several other experts from the healthcare segment had gathered at the recent SAS Global Forum 2019 in Dallas organised by Carey, North Carolina-based SAS Institute, to share real-world stories of the impact of advanced analytics, AI, machine learning, computer vision and natural language processing.
“There’s a renewed focus on data and analytics today, driven by increased computing power, a more connected world, and powerful technologies like AI and machine learning,” said Jim Goodnight, CEO, SAS Institute. “Our challenge is to make use of all data to solving the biggest issues.”
SAS is one of the world’s leading business analytics software vendors. Geert Kazemier, professor of surgery and director of surgical oncology at the Amsterdam University Medical Center (UMC), illustrated to the audience how data analytics can be used in the treatment of cancer. SAS has partnered with Amsterdam UMC to use computer vision and predictive analytics to improve care for cancer patients. He said that the level of patient-specific geometry in medical images that is available as a result, was not available before using the software.
SAS’ computer vision team has been working to extend the SAS platform for medical image analytics and using it to develop applications that can help oncological teams. This provides an environment where users can build applications that convert medical image data into insights, to make radiologists’ work easier. The application can capture highly detailed 3D geometries of liver and lesions from the data provided by Amsterdam UMC. The results can help tailor cancer treatments for individual patients.
Additionally, SAS’s Viya platform supports applications that can almost automatically go from raw images to objective metrics that may be used in the clinic, thus saving radiologists’ time. It provides an objective response assessment metric to help radiologists treat patients.
Continuing with how software and analytics can be used in the sphere of public health, SAS COO Oliver Schabenberger spoke of how authorities in New Hanover County in North Carolina are using software to counter the opioid crisis there, saying that analytics can provide data that can help protect children.
Apart from helping in research and diagnosis, the use of software also helps cut down on costs. Explaining how machine learning can be used to save pharma manufacturers’ costs, Randy Guard, SAS’ CMO, marketing, explained how traditionally, in the case of a defect, a manufacturer had to recall an entire lot of medicine. With the deployment of machine learning, however, it is now possible to identify the particular units and pull only those back, hence cutting down on costs.
Pfizer’s Chris Boone, vice-president of real-world data and analytics, spoke on the legal and ethical challenges for big data analytics in the biomedical context.
(The writer was in Dallas on the invitation of SAS Institute)