A primary motivation behind launching ReactWise was to reduce the time between discovery and delivery of life-saving medications to critically ill patients.

A primary motivation behind launching ReactWise was to reduce the time between discovery and delivery of life-saving medications to critically ill patients.

To this day, drug manufacturing remains a critical bottleneck for commencing clinical trials.

The public rarely hears about this part of the pharmaceutical pipeline.

Most of the attention — and investment — goes into drug discovery: identifying the right biological target, designing a molecule, and screening for hits.Thanks to AI, robotics, and large-scale data platforms, discovery has become faster, smarter, and more automated than ever before.

But discovery is just the beginning.Before a molecule can move into the clinic, it needs to be manufactured at scale - consistently, efficiently, and without impurities in accordance with regulatory standards.And this is where another real bottleneck lies.

For each new candidate drug, a dedicated team of chemists must figure out how to synthesize it not just once, but hundreds of times, under tightly controlled conditions, at increasing scales.

This step, known as process development, involves optimizing:Reaction conditions such as solvent, temperature, concentration, catalysts, and time.And often requires tens to hundreds of experiments.

Most of this work is still painfully manual. It relies on the intuition of chemists, historical precedent, and trial-and-error experimentation.In many cases, promising molecules are delayed not because they’re ineffective or unsafe - but because the process to make them isn’t ready.

This isn’t a failure of talent. It’s a failure of tooling.

Even though valuable data is generated during optimization campaigns, it’s often not reused effectively.Experimental insights live in spreadsheets or notebooks, disconnected from previous projects, previous teams, and even from the instruments that produced them.

There’s a better way.With advances in machine learning, high-throughput experimentation, and predictive modeling, we now have the technological capability to accelerate process development dramatically.

We can use algorithms to guide experimentation, visualize trade-offs, and prioritize the most informative experiments - helping chemists get to the optimal process faster, and with fewer dead ends.But these tools haven’t reached the people who need them most. And that’s the next frontier.

We don’t need to wait for a moonshot invention. We need to empower chemists with the tools of the 21st century.

At ReactWise, we’re doing just that.We’re building an AI co-pilot for chemical process development - one that integrates seamlessly into the workflows of bench chemists and helps accelerate the transition from discovery to the clinic.Because every day saved in the lab could be a day gained for a patient waiting for a cure.