Find the interactions that can become degradants, potency loss, phase change, or manufacturing trouble—before broad formulation work consumes API. CD ComputaBio combines structure-based risk prediction with targeted mixtures, fit-for-purpose stress conditions, and orthogonal analytics to turn compatibility data into excipient and formulation decisions.
Prioritize excipients using API functional groups, known reactive impurities, excipient chemistry, route, and expected use level.
Build binary or compact multicomponent studies that can distinguish an excipient effect from API autodegradation.
Use stability-indicating chemical analysis and solid-state methods to separate degradation from physical interaction.
Translate a confirmed interaction into practical options rather than a simple compatible/incompatible label.
We assess the reaction pathway, realistic exposure, analytical detectability, and formulation consequence together. The result distinguishes a screen alert from a confirmed incompatibility and identifies what can be changed. The illustrative bars are not project results.
Map API liabilities against excipient functional groups, reactive trace impurities, moisture, oxygen, light, and process exposures; then rank test priorities.
Run controlled binary or compact formulation studies with relevant ratios, matched controls, and conditions selected to accelerate plausible pathways.
Use stability-indicating and orthogonal solid-state evidence to identify the mechanism, estimate formulation relevance, and recommend an excipient, process, or packaging action.
The schematics below are original method-to-decision summaries created for this page; they do not reproduce publication figures or represent CD ComputaBio project results.
Marothu and colleagues found markedly different bisoprolol losses across stressed excipient mixtures. The result illustrates why chemical compatibility must be measured with a stability-indicating method and interpreted excipient by excipient.[1]
View publicationA 2001 study evaluated a rapid calorimetric procedure and recommended a two-step strategy: use calorimetry to rank compatibility risk within excipient classes, then confirm a small number of model formulations with HPLC-based accelerated stability studies.[2]
View publicationCompatibility studies are most useful when their ratios, stresses, controls, and analytics reflect a defined formulation question.
No. A thermal event may reflect melting, dissolution, moisture loss, or a physical interaction rather than chemical degradation. DSC is a useful screen, but important alerts should be confirmed by stability-indicating and orthogonal methods.
Not automatically. The ratio should amplify the intended risk while remaining interpretable. We consider expected formulation level, contact probability, excipient function, and whether a worst-case ratio is scientifically useful.
Moisture can mobilize reactants, change microenvironment pH, plasticize solids, or activate hydrolysis. Water-spiked and dry samples can help distinguish moisture-enabled pathways.
Yes. Trace peroxides, aldehydes, metals, moisture, and particle properties can vary by grade and supplier. High-risk ingredients may need grade-specific testing or incoming-material controls.
We assess whether the signal is relevant at formulation exposure and propose practical controls such as grade selection, concentration limits, antioxidants, chelators, pH modifiers, barrier coatings, processing changes, or packaging.
Send the API structure, known degradants, candidate excipient list, intended use levels, process, and available analytical methods. We will return a risk-ranked, material-conscious study plan.
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