Field notes, guides and case studies on stability, degradation, nitrosamine toxicology and method validation — the thinking behind a predictive-first lab.
How the FDA body-surface-area Km ratio converts an animal dose to the Human Equivalent Dose, and how the safety factor turns it into a defensible Maximum Recommended Starting Dose for a first-in-human trial.
Read the article →How Random Forest algorithms reason over chemical topology, and why 2048-bit Morgan fingerprints trained on curated Hansen/ECVAM datasets beat legacy methods on ROC-AUC.
Why deep-learning models fail regulatory scrutiny without mechanistic explanations — and how ICH M7's dual expert-rule-plus-statistical architecture keeps AI-assisted toxicology defensible.
Salt, polymorph and hygroscopicity choices made in preformulation quietly pre-programme your degradation profile — how to see the liabilities in silico before you commit the crystal form.
The ICH Q3A(R2)/Q3B(R2) dose-scaled threshold ladder, where the ICH M7 mutagenicity overlay overrides it, and how to justify each limit before an assessor asks.
A modified-release product's clinical behaviour lives in its release curve — how the f2 similarity factor turns that formulation fingerprint into a defensible, biowaiver-ready control strategy.
Why waiting for a three-month stability pull to start method development is a business risk — and how to map the separation space before the first blank.
The three structural classes that lose the 1.5 µg/day safe harbour — and the process and excipient triggers that quietly generate them.
A retrospective look at the Zantac/NDMA recall: what a 43-second in silico scan would have flagged on Day 1.
A risk-based read of the Class 1–5 framework, and how a dual-methodology in silico assessment lets you defensibly skip the wet lab.
Decoding the Carcinogenic Potency Categorization Approach — and why manual α-hydrogen counting is a costly place to make an error.
Breaking down the wall between computational chemistry, formulation and the analytical lab with a single source of molecular truth.
Repeatability, intermediate precision, %RSD and the ANOVA F-test — the statistics that prove your stability data isn't just analytical noise.
Recovery studies, the three-level spiking protocol, and correcting impurity quantitation with Relative Response Factors.
The AMBD and RMBD deficits, the five failing modes behind missing mass, and what regulators actually expect you to investigate.