Amazon launches AI platform to cut drug discovery time from 18 months to weeks

Amazon launches AI research tool to speed early-stage drug discovery

April 14 (Reuters) - Amazon's (AMZN.O), opens new tab cloud unit on Tuesday launched Amazon Bio Discovery, an artificial intelligence application designed to speed early-stage drug discovery by allowing scientists to run complex computational workflows without writing code. Drugmakers and technology companies have stepped up efforts to use AI to accelerate drug development. Amazon Web Services said in a blog post that Amazon Bio Discovery gives researchers access to a library of specialized biological foundation models that can generate and evaluate potential drug molecules, along with an AI agent that helps users select models, ⁠set parameters and interpret results. Researchers can send shortlisted candidates to integrated lab partners for synthesis and testing, with results routed back into the system to guide the next round of design. "(It) would take, 18 months to come up with 300 potential drug candidates. Now, scientists can quickly create 300 candidates within a couple of weeks," Rajiv Chopra, vice president of healthcare AI and life sciences at AWS, said in an interview with Reuters. Chopra said the rapid rise of drug-discovery models has turned computational biologists who can ⁠translate lab goals into machine-learning pipelines into a bottleneck. AWS said Bayer (BAYGn.DE), opens new tab, the Broad Institute and Voyager Therapeutics (VYGR.O), opens new tab are among early adopters, and 19 of the top 20 global pharmaceutical companies already use its cloud services. In a collaboration with Memorial Sloan Kettering Cancer Center, AWS said the platform ⁠used multiple models to generate nearly 300,000 novel antibody molecules and narrow them to 100,000 candidates for lab testing by partner Twist Bioscience (TWST.O), opens new tab, compressing work that can take months into weeks. Chopra said ⁠the service is intended to augment, not replace, scientists and contract research organizations. AWS will offer a free trial with five experimental units before introducing subscription tiers. AWS, Boston ⁠Consulting Group and Merck (MRK.N), opens new tab will also unveil an AI platform at AWS's Life Science Symposium aimed at improving clinical trial site selection, a common bottleneck in drug development. Reporting by Sahil Pandey and Puyaan Singh in Bengaluru; Editing by Tasim Zahid Our Standards: The Thomson Reuters Trust Principles., opens new tab

The Drug Discovery Process Is Cumbersome. Amazon Wants to Fix It With AI

The process of discovering new drugs and bringing them to market is notoriously slow and inefficient. Amazon Web Services is hoping to use AI to streamline this process, it announced Tuesday. Amazon Bio Discovery is the tech giant's new AI-powered agentic application designed to help scientists design and test drugs more quickly. The new application is set to give scientists access to multiple specialized AI models called biological foundation models, trained on vast biological datasets. "AI agents make powerful scientific capabilities accessible to all drug researchers, not just those with computational expertise," said Rajiv Chopra, vice president of AWS Healthcare AI and Life Sciences. "These AI systems can help scientists design drug molecules, coordinate testing, learn from results, and get smarter with each experiment. This combination of cutting-edge AI and the robust, secure infrastructure AWS has built for regulated industries allows scientists to accelerate antibody discovery in ways that weren't possible before." The new platform is intended to help identify models that scientists can use to generate and evaluate potential drug molecules to accelerate antibody therapies during the early stages of drug discovery.

Jefferies Comments on Amazon launch of Bio Discovery By Investing.com

Investing.com -- Amazon (NASDAQ:AMZN) introduced its Bio Discovery offering on Tuesday, providing researchers with access to over 40 AI biology models for drug discovery work. The new platform combines computational design with wet-lab validation, allowing bench scientists to access tools that can accelerate research without requiring direct computational expertise. Users can access the AI models, upload custom models, or use third-party licensed models through the platform. Amazon Bio Discovery includes integrated lab partners such as Ginkgo Bioworks (NYSE:DNA) and Twist Bioscience (NASDAQ:TWST) to enable wet-lab validation. The company announced the offering during its AWS Life Science Symposium on Tuesday. The antibody design workflow, validated by Sloan Kettering with 300,000 targets yielding 100,000 candidates, includes four steps. Users can evaluate models and build workflows by selecting from the catalog of AI biology models. The platform then guides users through antibody-design choices with AI agents, delivering recommendations without requiring code writing. The system returns AI-generated summaries with pre-filtered antibody candidates that have passed optimization and liability checks. Selected candidates can be sent directly to integrated lab partners with real-time cost and turnaround time estimates. Results automatically flow back into the platform for comparison against predictions. Jefferies analysts noted that projects previously waiting in queues can move forward immediately, and more accurate workflows may allow computational biologists to support additional programs. This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.

Amazon launches AI platform to accelerate drug discovery

Amazon, through its AWS subsidiary, has unveiled Amazon Bio Discovery, an artificial intelligence platform designed to expedite the early stages of pharmaceutical research. The tool enables scientists to execute complex workflows without programming, leveraging a library of biological models capable of generating and evaluating candidate molecules. An AI agent assists users in model selection, parameter tuning, and result analysis, amid intensifying competition surrounding the integration of AI in healthcare.