Most tablet failures aren’t surprises. They’re just discovered too late.
When are you catching the errors?
After the batch is run.
After the DoE is finished.
After scale-up doesn’t behave the way R&D expected.
By the time the problem shows up, the formulation is locked, the material is spent, and the only options left are rework, delays, or expensive troubleshooting.
That’s the reality most development and manufacturing teams are living with today.
The Cost of Finding Out the Hard Way
When failures are discovered late, they don’t just slow teams down — they quietly drain budgets and confidence. Wasted API and excipients add up quickly, additional DoE cycles stretch timelines, and repeated pilot or engineering batches consume both material and resources. Scale-up delays can mean missed manufacturing windows, while repeated setbacks erode trust with internal teams, partners, and clients. And in most cases, the root cause isn’t complex or unexpected — it’s simply something that was never measured early enough.
How TaBlitz Changes the Outcome
TaBlitz flips the workflow.
Instead of discovering problems after material is consumed, TaBlitz helps teams predict manufacturability upfront using:
Real micromeritics data.
Measured compression behavior.
Tabletability and strain-rate sensitivity.
Geometry and bulk density constraints.
Explainable, physics-based models.
With as little as 100 grams of material, TaBlitz can show you:
Whether a formulation will cap, laminate, or stick.
If target tablet size and weight are physically achievable.
How performance will change at production speed.
Where scale-up risk actually lives.
This isn’t trial-and-error. It’s formulation intelligence.
See the Failure Before It Costs You
If you’re still learning about your formulation by running batches, you’re paying to discover what can be predicted upfront. Using data in place of guesswork helps teams reduce wasted material, shorten development timelines, and move into scale-up with confidence instead of uncertainty.
Because the best failures aren’t fixed faster — they’re never run at all.
