Irina Oshchepkova
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Recent activity by Irina Oshchepkova-
Percepta: Using predicted properties to anticipate food‑effect risk conceptually
DescriptionOral drugs can show different exposure with and without food. While Percepta does not model food effects directly, predicted solubility, lipophilicity, and ionization can contribute to a...
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Percepta: Using predicted properties to guide prodrug design ideas
DescriptionProdrugs are often designed to improve solubility, permeability, or stability. Percepta predictions can help evaluate whether a prodrug candidate may address property issues of the paren...
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Percepta: Using property predictions to prioritize analogs for synthesis
DescriptionIn early design stages, many virtual analogs may be proposed. Percepta predictions help narrow down the list to compounds more likely to meet project property criteria.SolutionGenerate a...
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Percepta: Using predicted lipophilicity for chromatographic selectivity ideas
DescriptionDifferences in lipophilicity among related compounds often correlate with selectivity in reversed‑phase LC. Percepta logP/logD predictions can provide preliminary insights into expected ...
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Percepta: Interpreting hERG inhibition and cardiotoxicity alerts
DescriptionSome Percepta ADME/Tox modules predict potential hERG channel inhibition or cardiotoxicity risk based on structural features and data‑driven models. These predictions are screening tools...
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Percepta: Using predicted plasma protein binding in early risk assessment
DescriptionPredicted plasma protein binding (PPB) indicates how much drug is unbound (free) vs bound in circulation. Highly bound compounds may have altered pharmacokinetics. Percepta can provide P...
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Percepta: Screening for CNS penetration potential using predicted properties
DescriptionCentral nervous system (CNS) penetration relates to multiple properties, including lipophilicity, polarity, and ionization at physiological pH. Percepta predictions can be combined quali...
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Percepta: Using predicted properties to flag potential formulation challenges
DescriptionEarly prediction of solubility, lipophilicity, and ionization can highlight compounds that may be challenging to formulate (e.g., very low solubility, extreme logP). Percepta helps ident...
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Percepta: Predicting and interpreting skin permeability (logKp)
DescriptionPercepta can estimate skin permeability (logKp), which reflects how readily a compound passes through skin. These predictions are useful in dermal exposure assessment and topical formula...
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Evaluating structural alerts for toxicity
DescriptionSome Percepta toxicity models use structural alerts (toxicophores) to flag potentially problematic substructures. These alerts are qualitative and should be interpreted alongside broader...