Beyond the $12M: Revolutionizing Drug Formulation Development at Persist AI

We're fundamentally changing how quickly drugs go from molecule to product for patient use

At Persist AI, we're excited to announce our $12 million Series A funding round here. But this milestone represents much more than capital, it's validation of a vision to fundamentally transform how drug formulations are developed and delivered to patients.

The Hidden Bottleneck in Getting Medications to Patients

Most people don't realize that developing a drug formulation—the specific way a medication is packaged and delivered to the body—can take 8-12 years of painstaking work. This process accounts for roughly 20% of total drug development costs and is largely conducted through manual trial and error.

When we looked closely at this challenge, we saw a critical opportunity. While AI has begun transforming many aspects of drug discovery, formulation development remains stuck in methodologies that haven't fundamentally changed in decades. Scientists mixing ingredients in beakers, testing batch after batch, and struggling to scale up successful lab tests to commercial manufacturing.

The True Need: Moving Beyond Manual Trial and Error

The pharmaceutical industry is experiencing tremendous pressure to reduce development timelines and costs. Yet formulation development remains a stubborn bottleneck for several reasons:

1. Process complexity: Formulation isn't just about mixing ingredients, it's about precisely controlling how materials interact through specific processes. Minute changes in process can dramatically alter results.
   

2. Scale-up challenges: A formulation that works perfectly in a small lab batch often fails when scaled to commercial manufacturing volumes. This leads to costly delays and redevelopment work.
   

3. Material constraints: Early-stage drug development typically has very limited quantities of active pharmaceutical ingredients available for testing, severely restricting the number of formulation attempts possible.
   

4. Data limitations: Without systematic data collection across thousands of formulations, it's nearly impossible to build reliable predictive models.

   
   

What We're Building: An AI-First Platform for Formulation Development

Our approach at Persist AI addresses these challenges through an integrated platform built on three foundational pillars:

1. Custom Automation for Chemistry, Not Just Biology

Most lab automation is designed for aqueous (water-based) samples used in biology. We've built custom robotics specifically designed to handle organic solvents and complex materials used in pharmaceutical formulations. This allows us to generate formulation data 30x faster than traditional methods.

As one formulation scientist told us, "At most, groups I've worked with can make 20 formulations in a month." Our platform can produce over 1,000 formulations monthly, systematically exploring the formulation space with precision and consistency impossible to achieve manually.

2. Miniaturization with Scale-Up Built In

We use microfluidics technology to miniaturize formulation development, requiring minimal drug material while creating precisely controlled particles. What makes our approach unique is that our microfluidic system is designed for seamless transition from small-scale discovery to large-scale manufacturing, eliminating the traditional scale-up challenges that delay drug development.

One of our early customers spent six months with another contract research organization without success. We achieved their target formulation in just 28 days using our platform.

3. AI That Learns From Our Unique Data

The data generated by our robotics is special—it's comprehensive, structured, and linked to manufacturing process parameters. This allows us to build AI models that can predict crucial properties like drug loading and release characteristics with remarkable accuracy.

Our initial models show strong predictive power across small molecules, antibodies, and proteins, particularly significant because the industry has struggled to build long-acting injectables for complex biologics.

Our robotic lab for formulation development generates high quality data for training AI models

Beginning with the Most Complex Challenge: Long-Acting Injectables

We chose to start with long-acting injectables (LAIs): formulations that can release medication in the body for up to a year from a single injection. These represent the most complex injectable formulation type, with clear value for both patients and pharmaceutical companies.

For patients, LAIs mean fewer injections, better compliance, and fewer side effects. For pharma, they provide strong market differentiation and protection from generics. Yet despite these benefits, relatively few drugs are available as LAIs due to the formulation challenges involved.

By making LAI development faster and more predictable, we're not just incrementally improving an existing process, we're enabling an expansion of the entire market. Drugs that were previously impractical to formulate as LAIs due to time or material constraints can now be reconsidered.

Why This Matters Beyond Business

The implications of our work extend far beyond corporate efficiency. When formulation development is accelerated, patients get access to medications years earlier. When the process becomes more predictable, pharmaceutical companies can pursue complex formulations for a wider range of therapies.

The FDA is actively supporting continuous manufacturing efforts and approaches that reduce animal testing, both core aspects of our platform. Our ability to precisely control particle size also aligns with growing regulatory emphasis on quality by design.

What's Next: Manufacturing Scale and Cloud Access

With our Series A funding, we're deploying a cGMP-compatible manufacturing line to fulfill customer contracts, while continuing to build our cloud lab platform. This will allow pharmaceutical companies of all sizes to access our capabilities, democratizing advanced formulation development beyond large pharma.

We're also expanding our team with key hires in automation engineering, process development, and machine learning to accelerate our vision.

A Personal Note

As founders with backgrounds in automation and pharmaceuticals, we've experienced firsthand how outdated methods limit innovation in drug development. We built Persist AI because we believe patients shouldn't wait an extra decade for better drug delivery systems simply because the industry lacks modern formulation tools.

Our $12 million Series A isn't just funding—it's fuel for a mission to make advanced drug delivery systems more accessible, predictable, and efficient. We're proud of what we've built and excited about where we're headed.

The formulation bottleneck has persisted for too long. It's time for a new approach.