Precision medicine is one of the most talked about trends in healthcare. The promise is improved health outcomes and patient satisfaction, gained through an understanding of individual variability in genes, environment, and lifestyle. Recent commentators suggest that many of the technologies required to realize this goal already exist—and predict much wider application can be achieved by 2030.
At the heart of a precision medicine approach is data—huge amounts of data.
Single-cell technologies have positioned themselves at the forefront of biomedical research. These platforms allow researchers to bypass the uncertainties of bulk data and instead interrogate biological systems at a level of detail that was previously unreachable. But the value of these systems risks being impaired by bottlenecks in data analysis
Paradigm4’s Marilyn Matz and Zachary Pitluk discuss the challenges of integrating data from heterogeneous sources and how the company’s plaform and apps combine the cutting edge of computer science and a sensibility geared toward the unique needs of pharma and biopharma to provide end-to-end solutions.
The past few years have seen several flashy demonstrations of how artificial intelligence (AI) algorithms may transform biomedical research, particularly with respect to drug discovery.
