Persist AI Raises $12M and Launches Cloud Lab Platform to Transform Pharmaceutical Formulation Speed

AI-Driven Robotics Transforms Pharmaceutical Formulation: Persist AI Secures $12M to Scale Cloud Lab Platform

In a West Sacramento laboratory, a robotic system precisely measures mere milliliters of liquid and milligrams of pharmaceutical compounds—amounts that would have been considered impossibly small for effective testing just years ago. This miniaturized precision represents a fundamental shift in how drug formulations are developed, potentially slashing years off the time it takes to bring medications from laboratory discovery to patient use.

Persist AI, the company behind this technological breakthrough, announced today the launch of its Cloud Lab platform alongside a $12 million Series A funding round. The oversubscribed financing was led by Spero Ventures with participation from a diverse group of investors including Eli Lilly & Company, Shimadzu Future Innovation Fund, MBX Capital, and several others.

The Formulation Bottleneck in Drug Development

While artificial intelligence has revolutionized many aspects of pharmaceutical research, formulation development—the critical process of transforming active drug molecules into stable, deliverable medications—has remained stubbornly analog and resource-intensive.

"Every drug that reaches the market depends on an optimal formulation," said Sara Eshelman, General Partner at Spero Ventures. "While the industry has heavily invested in AI and predictive tools across the drug development pipeline, formulation has remained a blind spot—until now."

Traditional formulation testing requires substantial quantities of materials—often 1,000 milliliters of liquid and several grams of compound per test—and typically allows pharmaceutical scientists to evaluate only 10-15 formulations monthly. This creates a significant bottleneck in drug development, particularly for novel therapies where material availability is limited and time-to-market pressures are intense.

Miniaturization Meets AI Prediction

Persist AI's platform approaches this challenge through a combination of AI prediction models and extreme miniaturization. Their robotic systems can perform tests with just 1 milliliter of liquid and a few milligrams of material—representing a reduction of approximately 99% in material requirements compared to conventional methods.

The company recently demonstrated this capability in a project with an unnamed major pharmaceutical client, where they identified an optimal long-acting injectable formulation in just two months—a process that traditionally requires a year or longer. During this accelerated timeline, Persist's platform built and tested 700 formulations, vastly outpacing traditional capabilities.

"AI is enabling pharma to discover new molecules faster than ever. But a molecule that has poor shelf life cannot become a drug product that sits on a shelf," explained Karthik Raman, CEO of Persist. "Our mission is to convert these novel molecules into products, such as tablets and injections that patients can use."

Democratized Access Through Cloud Platform

The newly launched Cloud Lab represents a significant advancement in democratizing access to these capabilities. Through a web interface, pharmaceutical researchers can remotely control Persist's robotic laboratory facilities to test AI-predicted formulations without significant capital investment in specialized equipment.

The platform currently supports multiple formulation types including long-acting injectables, tablets and capsules, topical formulations, and standard injectables. According to the company, it can work with diverse modalities from small molecules and peptides to antibodies and antisense oligonucleotides.

Industry analysts note that this approach could be particularly valuable for smaller biotechnology companies developing specialized therapies where material conservation is critical and development timelines directly impact fundraising milestones.

"The ability to run 700 formulation experiments in two months versus the traditional 20 or so represents a sea change in development capabilities," remarked one pharmaceutical development consultant who requested anonymity due to client relationships in the sector. "More importantly, the material efficiency could make previously uneconomical formulation approaches viable."

Market Position and Growth Trajectory

Persist AI operates in a rapidly expanding sector. The global AI in pharmaceutical market is estimated at approximately $1.47 billion in 2025 and projected to exceed $10.4 billion by 2032, growing at a compound annual rate exceeding 32%. Meanwhile, the chemistry, manufacturing, and controls services outsourcing market—which encompasses formulation development—stands near $10.3 billion in 2024 with steady growth projected.

The company's approach combines elements from several converging technology trends: predictive AI modeling, laboratory automation, cloud-based research access, and experimental miniaturization. This positions Persist at the intersection of multiple high-growth markets.

However, Persist faces competition from established laboratory automation providers like Chemspeed Technologies, which offers modular high-throughput systems, and cloud laboratory providers such as Strateos and Emerald Cloud Lab. Newer entrants like Intrepid Labs are also pursuing the AI-driven formulation development space with significant venture backing.

Chris Shelner, COO of Persist, emphasized their ongoing technology development: "Persist AI has assembled a talented chemistry, engineering, and software team that develops exceptional automated solutions for formulation development workflows. We continue to improve our automation in addition to expanding capacity and workflow scope."

Capital Deployment and Future Plans

The $12 million funding round will support several strategic initiatives. A portion will be directed toward building a GMP (Good Manufacturing Practice) manufacturing system for long-acting injectables, through a collaboration with Nivagen Pharmaceuticals in Sacramento, California. This expansion into GMP-compliant manufacturing represents a significant step toward commercialization of products developed on the platform.

Additional capital will be used to expand the robotic laboratory capacity and to develop more comprehensive datasets for training Persist's AI models. The company plans to broaden the range of formulations its platform can predict, build, and test.

Persist AI appears to be gaining commercial traction, reportedly serving multiple top-10 pharmaceutical clients alongside several smaller biotechnology companies developing treatments for chronic diseases. Industry observers estimate the company's annual revenue around $2 million with a team of approximately 29 employees growing at 26% year-over-year.

Regulatory and Implementation Challenges

Despite the promising technology, Persist and its pharmaceutical partners face regulatory considerations in implementing AI-driven formulation data in Chemistry, Manufacturing, and Controls submissions to agencies like the FDA and EMA. Regulators must evaluate how data generated through miniaturized, high-throughput methods translates to commercial-scale manufacturing.

Additionally, pharmaceutical companies typically undergo extensive validation processes before adopting new technologies for critical development workflows, which could impact the speed of industry-wide adoption.

"The challenge isn't just developing the technology but convincing large pharmaceutical companies to shift critical workflows to an external AI-robotic platform," noted a pharmaceutical industry analyst. "This requires extensive validation, potentially long pilot phases, and sometimes risk-sharing agreements."

Outlook for the Industry

As drug development increasingly focuses on complex biologics, targeted therapies, and specialized delivery systems, formulation development has taken on greater importance in the pharmaceutical value chain. Innovations that accelerate this process while reducing material requirements could significantly impact overall development economics.

Persist AI's approach suggests a future where pharmaceutical development becomes increasingly distributed, with specialized technology providers handling discrete parts of the development process through cloud-accessible platforms. This model could potentially reduce capital expenditures for pharmaceutical companies while accelerating development timelines.

For patients and healthcare systems, these advancements could translate to faster availability of new therapies and improved medication delivery systems, particularly beneficial for chronic conditions requiring long-term medication adherence.

As Persist AI deploys its newly secured capital and expands its platform capabilities, the pharmaceutical industry will be watching closely to see if this approach to formulation development becomes the new standard or remains a complementary tool in the drug development toolkit.