Turn a solubility-enabling concept into a physically stable, manufacturable formulation. We connect drug–polymer interactions, phase behavior, supersaturation, process history, and storage risk so that polymer and drug-load choices are supported by evidence—not screening volume alone.
Establish whether an amorphous route addresses the actual exposure limitation and identify the failure modes that could erase the benefit.
Rank polymers by complementary evidence rather than a single solubility parameter or docking score.
Define a useful composition window that balances payload, molecular mobility, phase separation, and manufacturability.
Determine whether the dispersion creates and sustains a useful solution concentration under biorelevant conditions.
Match material behavior to spray drying, hot-melt extrusion, or solvent-based preparation constraints.
Challenge the selected system under humidity, temperature, and processing stress before scale-up locks in the formulation.
A credible ASD decision considers whether the drug and polymer mix, whether the polymer suppresses nucleation and growth, whether supersaturation is maintained, and whether the preparation route creates a robust material. The bars below illustrate the dimensions we score; they are not project data.
Translate dose, crystalline solubility, permeability, exposure gap, and dosage-form constraints into a measurable ASD objective.
Combine interaction models, phase behavior, thermal evidence, and targeted experiments to identify compositions worth making.
Assess how solvent removal, melt history, cooling rate, and moisture change homogeneity, residual crystallinity, and molecular mobility.
Compare dissolution, precipitation, and physical-stability evidence, then nominate a formulation with explicit risks and follow-up controls.
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.
Bhugra proposed a reduced-crystallization-temperature method and demonstrated polymer ranking with nifedipine dispersions, illustrating why an ASD screen should directly probe crystallization suppression rather than rely only on nominal miscibility.[1]
View publicationHigginbotham and co-workers showed that polymer molecular weight can strongly affect calculated solvation free energies and therefore apparent drug–polymer compatibility. The study supports sensitivity analysis before simulation results are used to eliminate candidates.[2]
View publicationThe right ASD study is sized around the exposure problem, available API, and the decision that must be made next.
No. Miscibility can support homogeneity, but crystallization inhibition, supersaturation maintenance, moisture response, processability, and dosage-form performance also determine whether a polymer is useful.
We use dose and product constraints together with phase behavior, glass transition, mobility, dissolution, and stability evidence. A high payload is only valuable if the material remains stable and performs.
Yes. We compare thermal stability, solvent options, viscosity, residence-time sensitivity, residual-solvent risk, and the microstructure each route is likely to create.
We combine solid-state characterization with stress conditions relevant to moisture, temperature, processing, and storage. Kinetic observations are interpreted separately from equilibrium miscibility.
The report provides a ranked polymer and composition set, supporting evidence, process implications, failure modes, validation experiments, and a clear go/no-go or next-study recommendation.
Share your API structure, dose, solid-state evidence, solubility data, and process constraints. We will define a focused plan for polymer selection, drug-load optimization, and stability confirmation.
Submit your project details below, and our team will respond within 24 hours.
Talk to our technical team about your project!
I Want To Talk