Startup Leucine reaps $7M in series A funds to advance AI digital twin platform for manufacturing

Startup Leucine reeled in $7 million in series A funding that will be used scale up its AI-generated digital twin platform designed to help drug manufacturers more easily navigate the complex landscape of regulatory compliance.

The New York City-based company, which was founded in 2019, is focused on using digital twins in its Compliance Cloud platform to alleviate drug development workflow bottlenecks caused by paper-based records and legacy systems, the company said in an Oct. 16 press release.

The funding round was led by Ecolab with participation from existing investors Pravega Ventures, Axilor Ventures and Techstars.

Digital or virtual twins are computerized copies of real-world objects or processes. Experts can use live, digital copies to garner real-time insights on a range of topics.

“Paper-based manufacturing records are the industry's Achilles' heel, fueling not only regulatory nightmares but also ballooning production costs and inefficiencies,” Vivek Gera, Leucine’s founder and chief executive, said in the release. “The legacy solutions are no better, with their extremely long implementation cycles and rigid, siloed applications that leave manufacturers in a lurch.” 

Leucine’s platform works as a digital twin of a drugmaker’s production floor using AI capabilities designed to digitize pharma manufacturing workflows and generate insights that allow production to remain compliant, operate faster and be more cost-effective. It is based on large language models that can quickly digitize paper-based operating procedures into digital formats.

The company said the platform can be implemented in eight weeks at a site.

In October 2022, Sanofi announced it would use Dassault Systèmes’ simulated 3D spaces to optimize production that uses digital twins.The Dassault platform creates a digitized environment that Sanofi said would allow it to experience the manufacturing systems under development and their operations virtually, thus letting the drugmaker establish its processes before they are deployed.

Digital twin simulations are also currently being used by drug developers and clinicians to understand how a patient and/or a therapy may perform in real-life situations.