3D Printing in Pharma with Lactose
3D printing brings a whole new dimension to Lactose
Are you ready for the future? 3D Powder bed printing enables to transform the pharmaceutical industry for the better. However only limited expertise on excipient usage in powder bed printing is available. We at DFE pharma also experienced these starting up problems and we are therefore happy to share the first findings of the use of lactose in powder bed printing in our 15 pages whitepaper. Let this be a start of sharing and generating knowledge on powder bed printing together.
This free whitepaper takes the first steps towards that goal, by sharing the findings of our detailed study of lactose as an excipient in the 3D printing of pharmaceuticals. Carried out in partnership with the Netherlands Organisation for Applied Scientific Research (TNO), the project shows that lactose – and collaboration – can yield results.
The whitepaper covers: Lactose Learnings and Evidence Building on 3D Printing in Pharma and you learn about:
- The challenges and opportunities: Tablets are the mainstay of pharmaceutical delivery, but people can find them difficult to take and manufacturers face production challenges. 3D printing could be the solution, but only one 3D printed medicine has been FDA-approved so far. So what’s stopping us?
- Where we stand: Powder bed printing is replacing fused deposition modelling as the 3D printing method of choice in pharmaceuticals. But what is it, how does it work, and what makes it superior?
- Preparing for the future: As techniques evolve, a significant data gap is opening up. Why is this happening and how do we address it? Could collaboration be the answer?
- What we discovered: Working with TNO, DFE Pharma tested 20 lactose grades with the primary objective of developing a lactose with sufficient flow, wetting and binding to be used effectively in the powder bed 3D printing of pharmaceuticals. What were the results and does lactose have a place?
- How to collaborate: This free whitepaper takes the first steps towards creating a centralised dataset that we believe will accelerate progress. We intend to continue our research in this area. Will you join us?
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