The scientific process isn’t predictable, it’s time consuming, and it’s not guaranteed to succeed. A new product may take 10’s, 100’s or even 1000’s of iterations requiring seemingly endless cycles of formulating - testing - sampling - reformulating - retesting - resampling to eventually develop a new formulation or a new molecule that meets market or customer needs.
For years, the industry has talked enthusiastically about the potential for artificial intelligence to accelerate new and derivative product development. It has the potential to facilitate assessment of material compatibility and manufacturability as well as speed our understanding of cause-and-effect relationships between ingredients and technical or functional performance or structure-property relationships.
Every company has a “pursue AI” or “product innovation” initiative being tracked by their board of directors. But it’s harder that just adding an AI layer on top of everything you currently do.
Most labs teams grapple with lots of single-purpose tools which create data silos populated with incomplete and inconsistently labeled data.
Trying to run AI on disconnected, “dirty” data results in low predictive value.
You need a predictive chemistry model built off of your specific and nuanced functional and technical requirements, formulations, test results, analyses and customer feedback data – without abstraction or watering down.
This requires a fuller platform that helps you collect AI-ready data as your teams work that can feed this interconnected data directly into AI models and produce recommendations and predictions in a closed loop.
Learn about Alchemy’s Integrated Predictive Chemistry Platform.
"I love Alchemy’s vision for predictive formulation, mobile lab reporting, voice memos, notes - all of it! Capturing all of our current chemistry data digitally gives us the right foundation to be able to take advantage of all the new capabilities Alchemy is building."