Stop wasting resources on compounds destined to fail
90% of drug candidates fail in clinical trials. This leads to billions of dollars and thousands of hours wasted on drugs that never advance. CAS BioFinder empowers your medicinal chemists with the predictive screening tools, SAR data, and drug optimization capabilities to invest their valuable time and resources in only the most promising candidates.
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Begin your ligand research with stronger results
Your medicinal chemistry team can spend weeks searching disconnected literature sources to create a promising candidate set for HTS. CAS BioFinder cuts that time drastically by allowing you to search through and filter thousands of ligand-target-disease combinations in seconds—all from our expert-curated data. This results in a more precise, curated candidate list in a fraction of the time before you get to the lab.
- Prioritize approved drugs and non-approved compounds by druglikeness, commercial availability, and potency, and explore relevant biomarkers to judge effectiveness.
- Dig into known and likely metabolites to identify toxicology risks early.
- Keep up to date with clinical trial data to ensure freedom to operate and learn from others’ results.
- Explore approved drugs and scaffolds for easy repurposing opportunities.
Five data barriers to safer small molecule drug development
Advancing small molecules from idea to candidate hinges on speed, clarity, and early high-stakes decisions. Our white paper maps out five data challenges slowing your R&D endeavors to help you identify friction points, explore actionable solutions, and uncover a path to design decisions in small molecule drug discovery.
Optimize candidates faster with integrated drug discovery data
Medicinal chemistry should not happen in isolation. It requires detailed pathway information, disease mechanisms, and biomarker contexts that all contribute to effective drug optimization. Ensure your team has access to the right data and tools to inform smarter optimization decisions.
- Predictive screening tools to evaluate safety risks before you invest R&D resources on them.
- MMPA heat maps to help you experiment with R-group substitutions to see the effects of small changes and identify activity cliffs.
- Two- and three-dimensional chemical space graphs to reveal trends and outliers related to your candidate list.
Give your candidates a stronger route to success from candidate selection to preparation for clinical trials.
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