How data lakehouses are vital to fuelling AI and the future of medicine

The pandemic has not only highlighted the importance of speed for medical discoveries, but also how data science and artificial intelligence (AI) can aid this acceleration. For example, machine learning in medicine has taken significant strides in recent years, with drug molecules discovered through AI used in human trials. Despite this, a recent report from the Alan Turing Institute revealed that difficulties with data collection, use, storage, processing and integration with different systems, namely the lack of a robust data architecture, hindered efforts to build helpful AI tools in response to the pandemic. To tap into the full potential of AI, organisations, especially in healthcare and pharmaceuticals, need to get their data in order. While great efforts have been placed into the likes of drug and medical discovery, particularly in light of recent events, it can be a lengthy, complex and costly process. Not to mention, its low success rates – only a couple of years ago, the overall failure rate of drug development was reported to sit at 96%.