TaBlitz
04/13/2026
๐๐จ๐ข๐ง ๐๐ซ. ๐๐๐๐ฅ๐ข๐ญ๐ณ ๐๐ข๐ฏ๐ ๐๐จ๐ฆ๐จ๐จ๐ซ๐ซ๐จ๐ฐ!
Every month, we take one real formulation or production problemโsticking, picking, capping, lamination, scale-up breakdownsโand open it up.
๐๐ฆ๐ข๐ญ ๐ง๐ฐ๐ฐ๐ต๐ข๐จ๐ฆ. ๐๐ฆ๐ข๐ญ ๐ข๐ฏ๐ข๐ญ๐บ๐ด๐ช๐ด. ๐๐ฆ๐ข๐ญ ๐ข๐ฏ๐ด๐ธ๐ฆ๐ณ๐ด.
Youโll see whatโs happening inside and outside the tablet press during compaction.
Youโll watch live TaBlitz demos tracing root cause in real time.
And youโll hear expert insight connecting whatโs happening on press to why itโs happening in your formulation.
We close every session with live Q&Aโbring the question thatโs been holding your batch back and get a direct answer.
๐จ 1 day away โ donโt miss it
Join Pharma Excipients, all4nutra.com, Dr. TaBlitz, and Natoli Scientific
๐๐ฟ. ๐ง๐ฎ๐ฏ๐น๐ถ๐๐ ๐๐ถ๐๐ฒ ๐ฆ๐ฒ๐๐๐ถ๐ผ๐ป๐
๐
Tuesday, Apr. 14, 2026
โฐ 10:00 AM EDT | 4:00 PM CET
Streaming live on YouTube and LinkedIn.
๐ Set your reminder and subscribe so you donโt miss it:
https://lnkd.in/erQGPcQH
๐๐ซ๐ข๐ง๐ ๐ข๐ง๐ ๐๐๐ ๐๐ง๐ ๐๐จ๐ ๐๐ง๐ญ๐จ ๐ญ๐ก๐ ๐๐ข๐ฑ
This is where Quality by Design (QbD) truly earns its place in modern development.
Instead of reacting to problems at scale, you proactively map your critical material attributes early โ flowability, compressibility, cohesion โ and connect them directly to tablet quality targets like tensile strength, friability, and dissolution performance.
You move from trial-and-error to structured understanding.
But letโs be honest.
Design of Experiments (DoE) is powerful โ especially for uncovering interactions.
The challenge? Broad experimental ranges often consume time, material, and effort exploring dead zones that were never viable to begin with.
๐๐จ ๐ญ๐ก๐ ๐ซ๐๐๐ฅ ๐ช๐ฎ๐๐ฌ๐ญ๐ข๐จ๐ง ๐๐๐๐จ๐ฆ๐๐ฌ:
What if you could narrow the field before you ever press โrunโ?
If you're looking to reduce downstream risk and build from physics, not assumptions, letโs connect.
Book your demo today: https://lnkd.in/gHQCv72d
02/13/2026
๐๐ข๐ซ๐ญ๐ฎ๐๐ฅ ๐๐ซ๐ฎ๐ ๐๐จ๐ฆ๐ฉ๐๐ง๐ข๐๐ฌ ๐๐ซ๐ ๐๐ฎ๐ข๐ฅ๐ญ ๐ญ๐จ ๐จ๐ฉ๐๐ซ๐๐ญ๐ ๐ฅ๐๐๐ง.
But lean should never mean blind.
When you donโt own manufacturing, your leverage comes from clarity.
Clarity on your formulation.
Clarity on your risks.
Clarity on what will โ and wonโt โ scale.
Thatโs where TaBlitz changes the equation.
We help VDCs move forward with:
โ
Early, material-sparing insight
โ
Physics-based formulation confidence
โ
Predictive robustness before scale-up
โ
A stronger technical position with CDMOs
โ
A cleaner, more defensible narrative for regulators and investors
This isnโt incremental value.
Itโs structural risk reduction.
If youโre building lean, build informed.
Letโs talk. Demo here: https://lnkd.in/gHQCv72d
02/12/2026
๐๐จ๐ฌ๐ญ ๐ญ๐๐๐ฅ๐๐ญ ๐๐๐ข๐ฅ๐ฎ๐ซ๐๐ฌ ๐๐ซ๐๐งโ๐ญ ๐๐ข๐ฌ๐๐จ๐ฏ๐๐ซ๐๐ ๐ข๐ง ๐๐๐ฏ๐๐ฅ๐จ๐ฉ๐ฆ๐๐ง๐ญ.
๐๐ก๐๐ฒโ๐ซ๐ ๐๐ข๐ฌ๐๐จ๐ฏ๐๐ซ๐๐ ๐๐ญ ๐ญ๐ก๐ ๐ฐ๐จ๐ซ๐ฌ๐ญ ๐ฉ๐จ๐ฌ๐ฌ๐ข๐๐ฅ๐ ๐ฆ๐จ๐ฆ๐๐ง๐ญ.
Traditionally, failure modes show up in one of three painful ways:
๐น During the first engineering or exhibit batch โ when confidence is high and timelines are tight.
๐น During PPQ โ the most expensive moment to learn something new about your formulation.
๐น After approval โ when a new raw material lot or seasonal humidity shift quietly pushes the process outside its undocumented limits.
By the time these issues appear, the formulation is locked, the validation plan is active, and the cost of adjustment is measured in weeks โ not hours.
๐๐ก๐๐ญ ๐ฆ๐๐ค๐๐ฌ ๐ญ๐ก๐ข๐ฌ ๐๐ฌ๐ฉ๐๐๐ข๐๐ฅ๐ฅ๐ฒ ๐๐ซ๐ฎ๐ฌ๐ญ๐ซ๐๐ญ๐ข๐ง๐ ?
In most cases, the failure wasnโt random.
It was hiding in the physics โ in the micromeritics, the compaction limits, the strain-rate sensitivity, the geometry stress distribution.
It just wasnโt evaluated early enough.
The strongest teams are no longer asking,
โDid it pass?โ
Theyโre asking,
โWhere are the edges โ and have we tested them?โ
Because robustness isnโt proven at the center of the design space.
Itโs proven at the boundaries.
And discovering those boundaries during PPQ is not a strategy โ itโs a gamble.
๐ If you want to identify your formulationโs edges before engineering batches, PPQ, or post-approval variability does it for you, letโs talk.
Schedule a demo and see how predictive robustness changes the way you approach scale-up.
Schedule your demo here: https://lnkd.in/gA2SrvjS
๐ ๐๐๐๐ฅ๐ข๐ญ๐ณ ๐๐๐ฆ๐จ ๐ข๐ฌ๐งโ๐ญ ๐๐๐จ๐ฎ๐ญ ๐ฌ๐๐๐ข๐ง๐ ๐ฌ๐จ๐๐ญ๐ฐ๐๐ซ๐.
Itโs about seeing your entire OSD workflow clearlyโfrom start to finish.
From early material understanding, through formulation and compaction, to robust gates, scale-up, and manufacturing continuityโTaBlitz supports OSD development as a single, connected workflow.
๐๐ก๐๐ญ ๐ญ๐๐๐ฆ๐ฌ ๐ฌ๐๐ ๐ข๐ง ๐ ๐๐๐ฆ๐จ:
โข How material properties translate into compaction behavior
โข How to identify manufacturability risk before scale-up
โข How to build robust, data-backed decision gates
โข How Model-Informed Drug Development (MIDD) works in practiceโnot theory
โข How reporting stays consistent across teams, CMOs, and programs
For , this means clearer gates, stronger partner alignment, and more confident investor and regulator conversations.
For pharma teams, it means fewer surprises, less rework, and better decisions earlier.
The outcome isnโt more data.
Itโs predictability by design.
If improving confidence, efficiency, and continuity across your OSD programs is a priority, the best next step is simple:
๐๐๐จ๐จ๐ค ๐ ๐๐๐๐ฅ๐ข๐ญ๐ณ ๐๐๐ฆ๐จ ๐๐ง๐ ๐ฌ๐๐ ๐ฐ๐ก๐๐ญ ๐๐ง๐-๐ญ๐จ-๐๐ง๐, ๐๐๐ญ๐-๐๐ซ๐ข๐ฏ๐๐ง ๐ญ๐๐๐ฅ๐๐ญ ๐๐๐ฏ๐๐ฅ๐จ๐ฉ๐ฆ๐๐ง๐ญ ๐๐๐ญ๐ฎ๐๐ฅ๐ฅ๐ฒ ๐ฅ๐จ๐จ๐ค๐ฌ ๐ฅ๐ข๐ค๐: https://lnkd.in/g5UgjDYv
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