From AI validation to microstructure imaging, AAPS PharmSci 360 speakers pushed toward faster drug development backed by stronger evidence. Here are PharmTech's biggest takeaways.
|Articles|November 2, 2003
- Pharmaceutical Technology-11-02-2003
- Volume 27
- Issue 11
Routine Sample Size for a Retest Procedure
Author(s)Jeffrey D. Hofer
This article discusses a straightforward approach that scientists may use to descide how many nonsuspect restest results are required to provide sufficient evidence to overcome an initial suspect result.
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Articles in this issue
about 23 years ago
FDA Will Drive Changes for Contract Businessabout 23 years ago
In the Spotlight--Decemberabout 23 years ago
Novemember 2003about 23 years ago
FDA Seeks Risk-Based Inspection Programabout 23 years ago
November 2003about 23 years ago
Clearing Regulatory Hurdlesabout 23 years ago
Improving Protein Capture for Transgenic Drug ProcessingAdvertisement
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The FDA approves asundexian, the first factor XIa inhibitor, cutting stroke risk 26% and setting a regulatory benchmark for factor XI drug developers.
Panelists on the PharmTech AI Pulse Check weigh a December AI playbook, EMA/MHRA moves, PCCP accountability gaps, and MCP-ready regulatory guidance.
France’s 2030 Health Initiative is driving growth in biotechnology, health innovation, biomanufacturing, and digital health.
CPHI Award winner, Pauline van der Wijst-Janssen, PhD, product development manager and global technical lead at DFE Pharma, explains excipient variability and excipients’ role in continuous manufacturing.
Pauline van der Wijst-Janssen, PhD, of DFE Pharma, won the CPHI Pharma Award for Future Leader. In this interview with PharmTech, she provides advice for scientists looking to advance to leadership roles.
Coverage from AAPS PharmSci 360 and CPHI Milan featured discussion about impurities, devices, and supply resilience. This week also included topics such as AI accountability, oral peptides, and new licensing deals.
No operator touches a CAR-T batch before demonstrating proficiency. Generative AI users should meet the same standard, and a higher one, because an AI error does not stay inside one batch.
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