Potent APIs Amplify Carryover Risk: AAPS PharmSci 360 2026

At AAPS PharmSci 360 in New Orleans, which occurred from October 25-28, Subathra Ramamoorthy, MS, RPh, associate principal scientist, Veranova, explains how forced degradation design and trace-level impurity profiling produce analytical methods that hold up at registration.

Ramamoorthy cautions against treating forced degradation as a checklist exercise. “First of all, we would have to understand the molecule,” she says. Knowing the molecule’s physicochemical properties and degradation pathways guides which stress conditions to apply and how severe and long each should be. Too much stress produces secondary degradants that don’t reflect real manufacturing or storage conditions. Too little stress fails to challenge the method. Specificity goes beyond chromatographic resolution to include peak purity, with high-resolution mass spectrometry brought in when needed. These are the same gaps FDA reviewers have flagged as commonly cited deficiencies in forced degradation data.

“When it comes to high potent programs, that makes everything harder at once,” Ramamoorthy says. Compounds in occupational exposure bands 4 and 5 are handled inside isolators, often with very little material available. At that scale, contamination or carryover shows up directly in the results, so blanks and system suitability matter as much as sample preparation. Limits for mutagenic impurities and nitrosamines push detection into the parts-per-billion range, which means analysts must control for matrix effects. Elemental impurity analysis brings its own risks, including labware contamination and erratic mercury recovery in inductively coupled plasma–mass spectrometry.

On thresholds, Ramamoorthy points to well-established frameworks. These include the International Council for Harmonisation’s (ICH’s) M7 lifetime limit and its often-overlooked allowance for shorter treatment durations, ICH S9 for advanced cancer therapies, the carcinogenic potency categorization approach for nitrosamines, and the route-specific exposure limits in ICH Q3D. “What matters is how transparent we are when we represent this framework,” she says.