AI's potential in the pharma life cycle - PMLiVE

From the acceleration of regulatory submissions - by identifying data gaps that have led to delays or rejections in the past - to the transformation of the conduct of clinical trials and patient safety monitoring, artificial intelligence (AI) has substantial potential to change the way life sciences organisations operate. AI and machine learning have risen rapidly up the business agenda in a wide range of industries - during the last year in particular. On the basis that computers can analyse and interpret data far more quickly and holistically than humans can, market innovators are staking their reputations on the breakthroughs that those analyses and interpretations will enable - ranging from improved customer self-service to advanced problem-solving in such areas as health diagnosis and predictive maintenance. It isn't just that machines return results at higher speeds or that they can work around the clock; machines also learn extremely efficiently so that their performance improves exponentially over very short periods of time. Those are some of the reasons that science documentaries and news reports have begun focusing on the potential for AI and machine learning to facilitate, for instance, earlier medical diagnoses - particularly in complex or baffling cases.