- Efficiently predict the most stable crystal forms, starting from the 2D structures of the drug candidates, and generate thermodynamic stability ranking of different structures
- Proactively identify alternative low energy crystal structures and avoid polymorphic transformation during development, manufacturing, and storage
Optimize your drug formulation process with structure-based insights and efficient screening of formulation parameters
A smart, strategic drug formulation can efficiently advance your drug development projects and inform downstream processes. Advances in molecular modeling and machine learning are enabling atomistic-level insights to improve drug formulations and the ability to evaluate large numbers of candidate materials and formulations prior to experiments.
Schrödinger offers a range of computational solutions for advancing small molecule formulation, from crystalline or amorphous forms to selection of materials and excipients for processing, stability, and delivery.
Identify the most stable crystal polymorph to derisk your drug formulation
Predict solubilities of drug candidates
- Accurately predict solubility of amorphous and crystalline forms to encourage the discovery of a soluble API and to delineate the potential solubility boost from non-crystalline forms using FEP+
- Identify instances where pure drug solubility can exceed the expected solubility due to the formation of small drug aggregates
Understand drug stability and reactivity
- Predict glass transition temperature and water uptake in amorphous materials, including amorphous solid dispersions
- Evaluate drug stability with respect to various degradation channels
- Calculate bond dissociation energy to evaluate chemical stability
Characterize and optimize complex formulations
- Gain insight into the complex requirements and behaviors of lipid-based and polymer-based formulations, including amorphous solid dispersions
- Evaluate the impact of different polymers or polymer residues on the release solubilization and aggregation of the API
- Predict key properties such as miscibility of ingredients, molecular interactions in solution, and drug release profiles
Optimize drug process development and manufacturing
- Predict crystal morphology to anticipate powder flow challenges
- Calculate Young’s and shear moduli to aid in the optimization of tableting conditions
- Understand solubility in non-aqueous solvents
Learn in silico drug formulation methods with our hands-on online certification course
Level-up your skills by enrolling in our online course, Molecular Modeling for Materials Science: Pharmaceutical Formulations.Learn More
Learn more about the key computational technologies available to progress your research projects.
High-performance free energy calculations for drug discovery
Complete modeling environment for your materials discovery
High-performance molecular dynamics (MD) engine providing high scalability, throughput, and scientific accuracy
Efficient modeling tool for organic crystal habit prediction
Efficient coarse-grained (CG) molecular dynamics (MD) simulations for large systems over long time scales
Quantum mechanics solution for rapid and accurate prediction of molecular structures and properties
Software and services to meet your organizational needs
Deploy digital drug discovery workflows using a comprehensive and user-friendly platform for molecular modeling, design, and collaboration.
Leverage Schrödinger’s computational expertise and technology at scale to advance your projects through key stages in the drug discovery process.
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