Process Optimization in 2026: Data, Sustainability, and Robustness
Process Optimization in 2026: Data, Sustainability, and Robustness
Process development teams are under growing pressure: faster timelines, tougher sustainability targets, and less tolerance for scale-up surprises. While there is a lot of hype around AI in chemistry, we wanted to share 3 thoughts on some more analogue changes we are expecting to see across 2026, and how ReactWise is designed to support them.
1. Better use of data that already exists
Organizations are generating more experimental and process data than ever. The challenge is turning that data into something useful: understanding variable interactions, identifying bottlenecks, and learning for future campaigns. Whether using our own datasets or uploading your historic campaigns, our transfer learning algorithm - MemoryBO - exists to “warm-start” new projects by learning from related data.
2. Sustainability moving into day-to-day process decisions
What used to be a downstream consideration is increasingly part of process design. Teams are being asked to quantify environmental impact, resource efficiency, and waste reduction alongside traditional performance metrics - without allowing for a trade-off. However, we are building workflows to make it easy for teams to replace toxic or unsustainable solvents with greener alternatives, such as binary mixes, while keeping the important physicochemical properties.
3. Earlier focus on robustness and operating windows
Rather than optimizing for a single “best” point, teams are placing more emphasis on understanding feasible regions and process sensitivity - driven by processes that look great in a lab, but struggle downstream. This shift supports more reliable scale-up, smoother tech transfer, and more mechanistic process understanding.
This is exactly why we built ReactWise: using data and machine learning not just to find better optima, but to help teams understand their processes more deeply and make more confident decisions earlier.
If these challenges sound familiar, we’re always happy to share how we’re thinking about them at ReactWise.
