Turn grams of data into scale-up confidence. Reduce risk before it becomes cost.
A new industry approach
What if you could identify sticking risks—and even predict formulation challenges—before Phase 2 ever begins?
Traditionally, sticking issues and compaction behavior are discovered late, often after significant API has already been consumed and valuable time lost. By the time problems surface, teams are forced into reactive reformulation, extended timelines, and increased costs.
Early insight with minimal material
Using Powder Rheometer-based sticking index analysis, formulation teams can now generate meaningful, predictive data with as little as ~50 grams of material—often at the earliest stages of development. This means you no longer need full-scale blends, extended runs, or large API quantities to understand how your formulation will behave.
All that is required:
API powder
That is it. No full formulation. No scale-up. No waiting.
Quantifying sticking before it becomes a problem
At the core of this approach is a simple but powerful concept: quantifying sticking tendency as a measurable index. By leveraging fundamental powder properties—specifically angle of internal friction and wall friction—this method produces a normalized sticking index that reflects real material behavior.
This allows teams to:
Identify high-risk formulations early
Compare API vs. excipient contributions
Evaluate the impact of drug load on manufacturability
Make informed go/no-go decisions before scale-up
Instead of guessing, you are working with data.
Move testing upstream where it belongs
Sticking is no longer something you “discover” during tablet press trials. With this technology, it becomes something you design around from day one.
Early-stage screening enables:
Rapid iteration without burning API
Smarter excipient selection
Better alignment between formulation and tooling
A clear path into compaction simulation and downstream modeling
As discussed, “we no longer have to wait till Phase 2”—this can be done in discovery or early Phase 1, dramatically shifting how development programs are structured.
From insight to strategy
Even more powerful, this data does not exist in isolation. When combined with compaction simulation and material behavior modeling (such as elastic recovery and spring behavior), it creates a deeper understanding of why materials stick—not just if they will.
This opens the door to:
Predictive formulation design
Integrated development workflows
Reduced trial-and-error in later phases
A smarter starting point
The takeaway is simple: you do not need finished tablets to understand tablet performance. You just need the powder. By moving critical testing earlier—and simplifying what is required to do it—you gain faster answers, reduce risk, and build better formulations from the very beginning.
Phase 2 is too late to discover problems you could have solved in pre-clinical.
