Q&A with Eugene Rakhmatulin on Challenges & Opportunities in Brain Health Research
Chief Technology Officer Eugene Rakhmatulin has launched a new department at Cohen Veterans Bioscience (CVB) dedicated to developing solutions to manage complex data collection, integration, and analysis. He has more than two decades of experience in information technologies, including more than 15 years in the life sciences industry.
We spoke to Eugene about his innovative work at CVB, what’s ahead in the future of technology, and what it means for the brain research field.
What do you enjoy most about being part of the Cohen Veterans Bioscience team?
I really like the focus on science, research and finding solutions to specific problems. This has been a welcome departure from for-profit corporations where money is the goal and not the means.
Which of CVB’s initiatives or research programs do you find most exciting and why?
I find all of them exciting. But of course, I’m the most excited about the ones with a challenging technology component, such as the Early Signal Platform for decentralized trials using wearable devices and home sensors; and BRAINCommons, a cloud-native collaborative research and sharing platform.
What technological advancements are revolutionizing brain health today?
Access to large and diverse datasets and decreasing computing and storage costs in combination with machine learning advancements allows scientists to come up with and validate their hypothesis in-silico faster than ever. Wearable sensors, including many consumer-level devices, enable the collection of continuous streams of data outside of the lab environment.
What do you think is the most prominent technology challenge in your work?
I think the biggest challenge is data and knowledge management. There is a lot of data available both in the public domain and privately. However, it varies in quality, type, file formats, data models, terminologies used, etc. Because of that, it’s hard to find knowledge and even harder to analyze.
This is not just a CVB issue, or even a life sciences industry-specific challenge. Everyone has the same problem and there is no universal solution so far. Short of inventing a viable AGI (Artificial General Intelligence) platform, I don’t think this problem will be solved on a large scale anytime soon. All we can do is concentrate on the domain of interest (in our case, brain health) and integrate as much data and knowledge as possible using knowledge graphs, common ontologies, data models, and both automated and manual curation.
Our organization is developing novel platforms that we expect to improve data and knowledge management across the brain health research ecosystem, including the BRAINCommons, the repository of high-quality data using common data models mentioned earlier, which we expect could significantly accelerate discovery and advancements in the field. The platform is not only a solution to enable CVB to share multi-modal data across our scientific programs; it will connect the entire brain research community. Users will have the ability to find and share data within and between disease areas to explore the full potential of data with the platform’s analytical tools and machine learning capabilities.
What technological advancements have the potential to revolutionize brain health in the future?
I’m looking forward to advancements in wearable sensor technologies with more sensor types, more portability, and a much longer battery life. Something like a truly wearable high-resolution EEG device would really benefit research studies related to brain health.