Most high-volume HTE datasets stop at medicinal chemistry. We’re building the ones that take you all the way to process R&D and manufacturing.
Most high-volume HTE datasets stop at medicinal chemistry. We’re building the ones that take you all the way to process R&D and manufacturing.
High-throughput experimentation (HTE) today is largely designed around med chem challenges - exploring huge substrate diversity, quickly, using convenient, high-boiling solvents like DMSO.
Fantastic for discovery. Not great for scale-up.
The problem: catalytic behaviour, selectivity, rates, and impurity profiles can shift dramatically with solvent choice. And those shifts often only appear when a project transitions from MedChem to process development - exactly when time pressure and risk are highest.
At @ReactWise, we’re changing the foundation. And this starts with using process-relevant solvents.
We’ve built screening workflows that go beyond the constraints of traditional 96-well MedChem HTE and now run material-compatible, 384-well plate screens tailored to industrial solvents and real process conditions. This allows us to capture the chemistry that truly matters for manufacturing, not just early-stage hits.
So far, we’ve generated 15,000+ industry-relevant data points, purpose-built to train models that remain predictive where it matters most - at scale.
If your data stops at MedChem, your predictions will too.
Our mission is simple: Predict from plate to plant.
That means building HTE datasets that reflect real manufacturing solvents, real processing constraints, and real catalytic behaviour, right from the earliest stages.
This is how we turn HTE from a discovery tool into a true engine for process chemistry and industrial decision-making.
More workflows, data drops, and case studies coming soon.
