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Bleiben Sie auf dem Laufenden über die neuesten Nachrichten von Instem.
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Why Scientific Organizations Are Re-Evaluating Oracle-Based Research Platforms
Modernizing infrastructure without disrupting scientific workflows
Why Applicability Domain Matters in (Quantitative) Structure-Activity Relationship (Q)SAR Models: Supporting Interpretation in Mutagenicity Assessments
Understand how applicability domain affects QSAR prediction confidence and why chemical coverage matters when assessing pharmaceutical impurities under ICH M7.
Inspection Week Shouldn’t Feel Like A Fire Drill
Regulatory inspections shouldn’t require weeks of searching for records, rebuilding audit trails, and pulling teams away from their day-to-day work. This blog explores why organisations are moving from reactive inspection preparation to continuous compliance, and...
Beyond the PPD Label: Clearer Language for Stronger Clinical Trial Transparency Submissions
In this blog, we discuss PPD, what different agencies actually care about, and how to navigate CTT language in an ever-changing regulatory landscape.
What’s New in eQCM 10.0.1?
With the release of eQCM 10.0.1, Instem is introducing tighter document control and audit trail integrity for regulated environments.
Introducing Blur™ 2.10: Faster, More Precise Clinical Trial De-Identification
With the release of Blur™ 2.10, Instem is introducing a broad set of enhancements across CSR anonymization, data de-identification, risk simulation, administration, performance, and security.
Mutagenicity Assessment Under ICH M7: Scientific Principles Supporting Pharmaceutical Impurity Risk Assessment
Mutagenicity assessment is the critical first step in pharmaceutical impurity risk evaluation, and this blog explores the scientific principles underpinning robust ICH M7 assessments, from complementary QSAR methodologies and Ames study data to applicability domain...
Stärkung der CMC-Bereitschaft durch In-silico-Erkenntnisse
Die Vorbereitung auf die CMC-Zulassung beginnt schon lange vor der Einreichung des IND-Antrags. Erfahren Sie, wie eine frühzeitige datengestützte Entscheidungsfindung, prädiktive Toxikologie und vernetzte Arbeitsabläufe Risiken reduzieren, die Datenqualität verbessern und die Vorbereitung auf die behördlichen Anforderungen während des gesamten Arzneimittelentwicklungsprozesses vereinfachen können.
