Zeneth is our expert, knowledge ‑based in silico software for predicting forced degradation pathways of organic active pharmaceutical ingredients (APIs). It provides valuable mechanistic understanding of how an API may degrade under stress conditions such as temperature, pH, water, oxygen, peroxide, light, metal ions, or radical initiators. Excipients and their impurities can also be explored to understand potential API–excipient interactions using the extensive excipient database in Zeneth.

At the heart of Zeneth is its curated knowledge base of degradation patterns. When a user provides an API structure and selects relevant environmental conditions, Zeneth evaluates the structure against these patterns and generates predicted degradants wherever a match is found. Each degradant is accompanied by structural details, calculated properties such as exact mass and formula, and is placed into a clear multi‑generation prediction tree which reveals how each degradant may arise from the parent compound.

Users can filter these pathways, interrogate specific transformations, or search for degradants based on mass, formula, or formula loss. Zeneth also highlights mechanistic and observable intermediates, giving a rich view of the underlying chemistry and enabling deeper scientific understanding.

To support clear visual interpretation, Zeneth includes a feature. Researchers can select degradants of interest from within a prediction tree, and Zeneth automatically generates a clean, structured diagram showing the key pathways radiating from the parent structure. Additional pathway metadata, such as condition triggers and likelihood scores, is integrated directly into the diagram. Spider diagrams can be exported as high quality .svg‑ files for use in reports, slides, or further editing.

What’s New in Zeneth: Enhancements that strengthen predicting forced degradation

Recent developments have expanded the scientificknowledge in Zeneth, visual clarity, and workflow accuracy.

Aligned and consistent predictions

Zeneth provides standardised prediction defaults designed to closely mirror typical forced degradation‑ conditions. This helps reduce variation between users and ensures that in silico predictions more closely reflect experimental environments expected in regulatory contexts.

More nitrosamine insight

Zeneth offers enhanced nitrosamine related assessment tools, including the ability to highlight structural motifs associated with nitrosation ‑risk. Key functional groups, such as N‑N=O, C=N‑O, and C‑N=O, are visually flagged within predicted degradants to support rapid identification of potential nitrosamine hazards.

Zeneth can also evaluate compounds using pre‑configured settings for conditions known to lead to nitrosation reactions. This streamlines assessments and helps reduce the possibility of human error.

Greater degradant‑property knowledge

Zeneth predicts an expanded set of physicochemical properties for degradants, supporting analysts in understanding degradant behaviour during chromatography, aiding the development of stability‑indicating methods.

Complementing this, new property calculators, including a pKaH estimator to identify the most reactive atom when multiples are present, and a chromophore atom‑count calculator to guide wavelength selection, provide practical value during method design and troubleshooting.

Enhanced excipient knowledge for formulation support

The excipient database (that aligns with Lhasa’s Vitic nitrites database) has continued to grow and now includes scientific commentary for a substantial number of excipients, adding context on potential incompatibilities and degradation risks to strengthen early formulation decisions.

Broader knowledge base and workflow improvements

Zeneth incorporates new transformations, additional excipients, and more member-donated experimental evidence, enriching the scientific robustness of predictions. Usability refinements and the ability to run multiple API evaluations in parallel further streamline day‑-to‑-‑day work.

Extra capabilities worth knowing (to enhance predicting forced degradation)

Degradant context in the information panels

Beyond structures and scores, degradant cards and detail views provide the triggering conditions for each step and let you drill into transformation descriptions and intermediate involvement. These contextual cues help explain why a degradant forms and support stronger mechanistic narratives in reports.

Filtering and structure elucidation‑ tools

Zeneth supports targeted filters, such as exact/substructure searches, condition triggers, likelihood thresholds, and intermediate categories, to help you identify unknowns, including matching unidentified masses detected experimentally.

Multi‑component predictions for compatibility

When evaluating compatibility, Zeneth can consider multiple APIs (with or without excipients) in the same prediction to understand interactions and combined degradation pathways that may only emerge in mixtures.

How these advancements support your work

Together, these updates enhance the capability of Zeneth to:

• Provide clearer, more defensible forced degradation rationale, thanks to consistent, regulatory aligned prediction defaults that map onto common stress‑ testing‑ conditions.
• Highlight and manage nitrosamine related‑ risks with improved visual cues and streamlined, pre‑configured assessment pathways.
• Support formulation decisions earlier through expanded excipient insights and easy access to scientific commentary.
• Strengthen analytical method development via additional property predictions and calculators (e.g., pKaH, chromophore) that guide wavelength selection and prioritise likely reactive centres.
• Accelerate structure elucidation and investigative workflows using filters and mass searches across the degradant predictions.

Looking forward to the future of predicting forced degradation

Zeneth continues to evolve as part of our wider purpose to advance regulatory-aligned chemical safety science. Ongoing research with industry partners and growing community contributions will keep improving predictive accuracy, benchmarking and visual interpretation tools, ensuring the software remains aligned to real world forced degradation and impurity risk assessment needs.