IBM's "Watson" health business unit will gradually reduce the drug discovery (Drug Discovery) service, which many pharmaceutical companies use to develop new drugs using AI.
The medical news magazine "Stat" was the first to report this news today, saying that due to the product "selling sales", IBM now admits failure. The company said it will continue to provide service guarantees to existing customers, but will not sell them to new customers.
IBM told IT outside the media in a statement The Register: “We have not stopped our Watson for Drug Discovery products, and we remain committed to ensuring continued success for our current customers. We will focus our resources on the Watson Health Business Unit and increase our investment in the peripheral areas of clinical development; we have found that our data and AI functions face greater market demand in this area. ”
The move hinted at the dilemma facing IBM's health business unit; Deborah DiSanzo, the head of the division, resigned after a round of layoffs last October.
IBM has previously announced several high-profile collaborative projects, but it is not entirely a collaboration in the field of drug discovery, including collaboration with Pfizer, Novartis and Illumina in cancer research, and exploring with Teva Pharmaceutical Industries. New medicine. However, IBM sources told Stat that even with those partnerships, Watson found that the project's profitability was not strong enough.
IBM is now considering “returning Watson” to focus on clinical trials rather than continuing to invest in a failed product.
An IBM spokesperson told Stat: "We are concentrating resources from the Watson Health Business Unit to increase investment in the peripheral areas of clinical development; we have found that our data and AI capabilities face greater market demand in this area. . ”
IBM's "drug discovery" service combines many tools, including search engines that scientists can use to find information about specific human genes or compounds. It also includes a knowledge network that describes the relationship between existing drugs and disease.