Pauric Bannigan, Intrepid Labs, explains where AI speeds formulation decisions, why data is the bottleneck, and how active learning trains models with far less data.
News|Articles|March 15, 2016
- Pharmaceutical Technology-03-15-2016
- Volume 2016 eBook
- Issue 1
Optimizing Tablet Compression
Author(s)Frederick Murray
The author discusses key process parameters and shows how a process optimization template can be used to improve this key operation.
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The author discusses key process parameters and shows how a process optimization template can be used to improve this key operation.
from Pharmaceutical Technology’s 2016 Solid Dosage Drug Development and Manufacturing eBook.
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over 10 years ago
Excipient Quality and Selectionover 10 years ago
Filling the Analysis Gap in the Move to Continuous Processingover 10 years ago
Modeling and Simulation Move Downstreamover 10 years ago
Unifying Excipient Databasesover 10 years ago
Establishing a New Performance Standard for HPMC CapsulesAdvertisement
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Stephanie Johnson, Pfizer, explains how off-platform triggers, single-owner risk registers, and traceable prior knowledge keep protein formulation programs on track.
Stephanie Johnson, Pfizer, discusses how platform formulations moved 2 Pfizer protein programs to IND in 8 months by redistributing, not removing risk.
Vibha Jawa, PhD, chief scientific officer at EpiVax, explains why the need for animal studies varies by modality and what it takes for organ-on-chip and other human-relevant models to replace these studies in IND-enabling toxicology work.
Sanjay Konagurthu, PhD, senior director of Science and Innovation at Thermo Fisher Scientific, explains what teams need to do to ensure the usefulness of AI and what strides have been made with AI in regulatory submissions.
The new initiative aims to apply traceable AI and science to expand care worldwide by translating discovery into tools that accelerate drug development.
Sanjay Konagurthu, PhD, senior director, Science and Innovation at Thermo Fisher Scientific, provides an update on the progress of AI and machine learning used in drug delivery.
Shubhajit Paul, a senior research fellow in Boehringer Ingelheim’s Department of Material Analytical Sciences, spoke with PharmTech at AAPS PharmSci 360 to explain how tabletability prediction can be improved for roller-compacted formulations.
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