From Hit Identification to Lead Optimization: Building Scientific Continuity in Early Drug Discovery
Hit Identification Starts with Target Context
As Dr.
When high-quality structural information is available, fragment-based drug discovery or virtual screening may provide efficient entry points. When a reliable functional or cellular assay has been established, HTS remains a powerful route for assessing biological activity across large compound collections. For more challenging targets, affinity-based approaches such as DEL, ASMS, or SPR can help address early questions around druggability, particularly when protein availability or assay readiness is limited.
The discussion also highlighted V-DEL-facilitated target triage as one of
Validated Hits Require More Than Primary Activity
Primary screening readouts are only the starting point. To advance a hit with confidence, teams need a layered validation workflow that combines purity and liability checks, dose-response confirmation, orthogonal assays, selectivity and counter-screening, cytotoxicity assessment, and biophysical binding studies. This process helps distinguish actionable hits from false positives, nonspecific binders, and assay artifacts.
DMTA Cycles Require Clear Hypotheses
After hit validation, the design–make–test–analyze cycle becomes a central operating framework for advancing compounds. From the medicinal chemistry perspective, Dr.
Structure-based design, ligand-centric SAR analysis, molecular descriptors, FEP, MD simulations, ADMET prediction, and AI/ML-supported modeling can all contribute to compound prioritization. The objective is not to generate designs in isolation, but to test defined hypotheses and determine which directions should continue, pause, or be replaced.
Integration Supports Scientific Discipline
Clear go/no-go criteria are essential to prevent programs from continuing without sufficient evidence of tractability, efficacy, or developability. Assay enablement, protein construct quality, target modulation, in vivo efficacy, therapeutic index, scaffold-specific toxicity, DDI risk, cross-species PK, early CMC considerations, and nomination criteria can all influence program decisions.
In this context, integration is less about placing multiple capabilities under one roof, and more about connecting the right data, expertise, and decision points at each stage of discovery. By integrating protein science, structural biology, screening, medicinal chemistry, AIDD/CADD, biology, and DMPK,
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