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Partners to design ai-based gene editing therapies for Rett. The Rett Syndrome Research Trust (RSRT) is teaming up with Profluent Bio to use artificial intelligence (AI) to design personalized gene-editing therapies for Rett syndrome. Profluent will leverage its AI tools to engineer molecules that can correct mutations in the MECP2 gene, the most frequent cause of Rett syndrome. RSRT has awarded Profluent $1 million to fund the partnership. "Our AI is built to navigate a vast design space and find solutions that are out of reach with manual protein engineering methods, resulting in personalized mutation-specific genomic medicines that are an ideal match for each Rett patient," Peter Cameron, PhD, Profluent's senior vice president of gene editing and translation, said in a company press release. "Together with RSRT, we're excited to turn progress in the lab into impact for patients." Rett syndrome is caused mainly by mutations in the MECP2 gene, resulting in less production of a working protein with the same name that plays an important role in brain development and communication between brain cells. Gene editing tools, such as CRISPR/Cas9, are used in research and clinical settings to remove, add, or modify pieces of DNA with the goal of treating genetic diseases. Focusing on mutation. Base editing uses modified versions of the CRISPR system to make precise changes to a single building block (nucleotide) in the MECP2 gene. Profluent said its AI models will be used to develop base editors that target mutations often found in Rett syndrome patients. Profluent will initially focus on the T158M mutation, which changes the amino acid sequence in the MeCP2 protein from threonine to methionine. Amino acids are the proteins' building blocks. The new editors will fit inside a harmless adeno-associated virus (AAV) and make room for systems that prevent them from accidentally causing edits in the brain beyond the intended one. "This collaboration is about people first - Rett families are trusting us with a challenge that affects them 24/7," said Hilary Eaton, PhD, chief business officer at Profluent. "Profluent is committed to using AI as the equalizer and democratizing the field of gene editing; whether a patient has a rare or common disease, they deserve access to safe, high-quality treatments." The company presented data on Protein2PAM, an AI, deep learning model capable of engineering Cas proteins that could be used to develop customized base editors for Rett, at the Rett Syndrome Genetic Medicines Summit, held in September in Boston. "Families in our community face seizures, loss of speech, and profound disability," said Monica Coenraads, CEO of RSRT. "They are counting on us to push the science forward. We believe Profluent's frontier AI can accelerate the development of custom editing solutions for our patients with serious unmet medical need." Last year, RSRT launched a program, Roadmap to Cures, aimed at raising $40 million to bring three genetic medicines to clinical trials by 2028. Andrea Lobo, PhD Andrea Lobo holds a PhD in cell biology/neurosciences from the University of Coimbra-Portugal, where she studied stroke biology. As a research scientist for 19 years, Andrea participated in academic projects in multiple research fields, from stroke, gene regulation, cancer, and rare diseases. She has authored multiple research papers in peer-reviewed journals.

Profluent has raised $106 million to expand its AI models for biology in drug development and agriculture. Founded by Ali Madani, who previously worked on AI for biology at Salesforce, Profluent's technology allows scientists to specify desired protein properties in human language and receive a DNA recipe to create them. Madani partnered with Alexander Meeske from the University of Washington to develop this innovative approach.

Jeff Bezos is backing an AI startup aiming to make proteins programmable. Profluent has raised $106 million to scale up use of its AI models for biology in drug development and agriculture. Ali Madani started thinking about how AI could be programmed for biology in 2020, years before the launch of ChatGPT. The machine learning scientist was working at Salesforce, which that year launched a moonshot project, called ProGen, to design novel proteins with generative AI. "The same architecture used for English, you can use for biological languages like proteins," he told Forbes. He left Salesforce in 2022 and teamed up with Alexander Meeske, head of a research lab at the University of Washington, to bring that promise to life. Now, his Emeryville, California-based startup Profluent's AI models enable scientists to explain the properties they want in a protein in human language (like stability or ease of manufacturing), and then output a DNA recipe to create that protein. Madani, who has a Ph.D. from the University of California, Berkeley and was the lead author of a Nature Biotechnology paper on ProGen, believes focusing on proteins could unlock groundbreaking new drugs. Proteins are large molecules that are significantly more complex than the small molecules that are the basis of many existing drugs, but allow for newer treatments like gene therapies. And he hopes it also will lead to breakthroughs in agriculture, where researchers hope to create more resilient and sustainable crops. "The proposition of making biology programmable is going to enable blockbuster drugs, and solutions across therapeutics, diagnostics and agriculture - and it's going to require a lot of capital," Madani said. To that end, Profluent said Wednesday that it had raised $106 million in new venture funding led by Jeff Bezos's Bezos Expeditions and Altimeter Capital, bringing total investment to $150 million. With the new financing, Profluent's valuation is approaching $1 billion. Its commercial partners include Revvity, an $11 billion (market cap) biotech; Corteva Agrisciences, the agricultural spinoff of DuPont; and VC-backed Ensoma, which is working on treatments for genetic diseases and cancer. Companies like Recursion have been trying for years to bring AI to drug discovery, though the efforts have proven more difficult than researchers had originally hoped. But with 90% of new drugs failing and the cost to develop new ones running in the billions, an increasing number of companies are working on tackling the problem with AI-enabled protein design. Profluent is up against heavyweights like Isomorphic Labs, the spinoff of Google's AI research lab DeepMind, and startups like Xaira Therapeutics, which emerged from stealth last year with $1 billion in funding. Profluent's goal is not just to use AI to find existing proteins, as is typically the way existing drug development is done, but to custom-design completely new proteins for a patient's needs. To date, Profluent has created a database that it calls Protein Atlas, comprising 115 billion unique proteins, which it says is the largest such protein data resource in the world. All that data, combined with more compute power, should help it build bigger, better models - a concept known as "scaling laws." Earlier this year, Profluent said that it had demonstrated scaling laws work for models that design proteins. Last week, it introduced a new foundation model, called Profluent E-1, that provides evolutionary context. "One of the reasons Jeff [Bezos] was interested is that we have discovered scaling laws" apply to biology, Madani said. "As you gain more and more data, the models get better and better." Investor Jamin Ball, a partner at Altimeter Capital, who first met Madani about 18 months ago, and got to know him on walks around a bio conference in San Diego last year, said there's "a massive, massive, massive opportunity" in the ability of scientists to go from happenstance in drug discovery to bespoke design. "We think the next frontier in AI will be biology and drug discovery," he said. "We are still really early," Madani said, comparing the current state of AI-enabled biology to the early days of the Internet. "If we can have a machine that can truly make biology programmable, we will have a conveyer belt of blockbuster solutions."