SciBite’s artificial intelligence (AI) software platform is designed to help pharmaceutical researchers and other life-science professionals parse through their data to unlock useful insights. According to the company, the platform pairs machine learning with ontology-based semantic capabilities.

James Malone (JM), SciBite’s chief technology officer, spoke with Outsourcing-Pharma about the progress of AI use and understanding in the pharma industry, and how the company’s AI technology seeks to build upon previous technological capabilities.

OSP: Please talk a bit about the evolution of AI’s use in life sciences—how long it’s been present, how its understanding and application has changed in the industry, and what might lie ahead?

JM: There is a broad spectrum of approaches in AI, some of which have been used for a long time in life sciences. For instance, knowledge engineering using ontologies to describe metadata, expert systems for helping triage symptoms online, and machine learning for image analysis.

Most recently the innovation in deep learning, combined with availability of big data and powerful compute, has provided huge improvements in the performance of some of these approaches. This is particularly true of areas such as language comprehension where they now represent the state of the art. It is likely these approaches will be increasingly combined into software in the near future and that scientists will benefit from the innovation without having to become deep learning experts.