Profluent Seeks to Revolutionize Drug Development With AI-Powered Protein Design

Profluent Seeks to Revolutionize Drug Development With AI-Powered Protein Design

In the previous year, Salesforce launched a project called ProGen, with the goal of employing generative AI for designing proteins.  The project could revolutionize the discovery of medical treatments by making them more cost-effective, according to a blog post from January 2023. Although ProGen's findings were documented in the journal Nature Biotech, demonstrating the AI's capacity to create artificial protein structures in 3D, the project didn't make a significant impact commercially.

When Ali Madani, a key player in the ProGen initiative, founded Profluent, this scenario changed. With Profluent, he hopes to put research lab-developed protein-generation technology to practical use in the pharmaceutical sector. In an interview with TechCrunch, Madani outlined his vision for flipping the conventional medication development process, beginning with the needs of patients and therapies to create specialized treatment plans.

During his time working in the research division of Salesforce, Madani made comparisons between the "language" of proteins and the structure of natural languages like English. He discovered that artificial intelligence (AI) is capable of creating and predicting proteins, which are sequences of amino acids that carry out a variety of biological tasks.

Profluent is working with University of Washington assistant professor of microbiology Alexander Meeske to expand the application of this idea and include gene editing. Madani addresses the limitations of using natural proteins and enzymes to treat hereditary illnesses and the possibility of using Profluent to create gene editors that are tailored to the specific requirements of each patient.

Generative AI has long been used to predict protein structures; firms such as Nvidia, Meta, and DeepMind are leading the way in this field. Profluent seeks to set itself apart by advancing gene-editing and protein synthesis technologies through the use of vast databases containing over 40 billion protein sequences. The company plans to expedite the development of genetic therapies by forming partnerships with outside organizations.

According to Madani, this strategy might drastically cut down on the time and money needed for medication development, which is often an expensive and time-consuming process. He emphasized the possibility of a change in the development of medicine from accidental discoveries to deliberate design.

Berkeley-based Profluent, which employs twenty people, has gotten a $35 million investment increase and the backing of prestigious venture capital firms. In order to achieve Profluent's ambitious objectives of advancing medical treatments, Madani is concentrating on improving AI models and growing collaborations.

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