The use of artificial intelligence and machine learning is almost commonplace in the biotech and pharma industry as multiple companies are harnessing the power to aid in drug discovery and development. This week more companies have announced advancements in their AI programming.
This morning, San Francisco-based Notable Labs announced it secured $40 million in a Series B funding round to use its artificial intelligence platform to advance cancer drug development. The company’s approach is aimed at predicting which types of patients are most likely to respond to a drug in as little as five days. The process is designed to help physicians make more informed decisions about which clinical trials will be effective with patients and can also benefit the likelihood of a trial’s success by matching the right patients to the right trial. Notable noted that in a recent clinical trial, its process achieved an 84% overall accuracy rate in predicting patient response to drugs or drug combinations.
Notable Labs was founded by De Silva, a former analyst at noted biotech investor Peter Thiel’s Clarium Capital, nearly five years ago. De Silva said the concept for the company came out of his experiences caring for his father, who was diagnosed with glioblastoma multiforme. None of the approved medications benefitted the elder De Silva and his father was not eligible to participate in any clinical trial due to the advanced form of the disease. De Silva said that all of the treatment solutions for his father were sort of a “one-size-fits-all” approach. He wanted to find a way to focus on personalized treatment for individual cancer patients, and Notable Labs was born.
De Silva said the company is ready to scale the results Notable has so far generated to expand its AI platform to other cancer types.
“Patients with aggressive cancers are in a race against time, but if we can use technology to identify the best drug or drug combination at the time of diagnosis, there is a much better chance those therapies will work,” he said in a statement.
Notable’s funding round was supported by B Capital Group and LifeForce Capital, along with Industry Ventures. This round brings Notable’s total funding to more than $55 million.
Notable isn’t the only AI-focused company advancing its programs. Computational pathology-focused Paige published an article in Nature Medicine describing an AI system for computational pathology that achieves clinical-grade accuracy levels. The paper outlines how a series of novel algorithms created using datasets ten times larger than those that have been manually curated performed better and also are more generalizable. In its announcement, Paige said the significance of this development hinges on the fact that curating datasets can be prohibitively expensive and time-intensive. By eliminating the need to curate datasets, Paige can now develop many more highly accurate algorithms that can be built into clinical decision support products to help pathologists around the world drive better patient care.
GlaxoSmithKline has also made a move this week to support its AI program. Bloomberg reported that the U.K. pharma giant poached Genentech veteran Kim Branson to oversee the use of AI in the finding of novel targets for potential medicines. GSK first turned to the use of AI in 2017 with a strategic drug discovery collaboration with Exscientia. Under the terms of that particular collaboration, Exscientia is using its AI capabilities and combining them with GSK’s drug discovery expertise in order to discover novel and selective small molecules for up to 10 disease-related targets.
In the interview with Bloomberg, GSK Chief Executive Officer Emma Walmsley said harnessing the big data capabilities of AI will enable the company to predict better targets for potential drugs and which patients are more suited to those drugs in clinical trials, much like Notable indicated. Walmsley said the AI capabilities boos the chance of “improving the productivity of an R&D organization.”
Last week, AI startup Kyndi secured $20 million in Series B funding that will be used to expand the company’s engineering and sales teams to meet growing customer demand in government, financial services and life sciences. Kyndi is developing the first “Explainable AI platform.” Unlike traditional “black box” AI solutions, the Kyndi platform scores the provenance and origin of each document it processes, while helping organizations quickly find difficult-to-locate information within collections of documents – without requiring large, labeled data sets to train the system, the company said in its announcement.