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From Hit Identification to Lead Optimization: Building Scientific Continuity in Early Drug Discovery

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News provided by

Viva Biotech

27 May, 2026, 12:00 GMT

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SHANGHAI, May 27, 2026 /PRNewswire/ -- On May 20, 2026, Viva Biotech hosted a V-Experts in Conversation webinar, "Managing Complexity in Modern Drug Discovery: A Practical Approach to Integrated Screening & Chemistry." Moderated by Victoria Ouroutzoglou, Associate Director of Business Development at Viva Biotech, the roundtable featured Dr. Bing Xia, Vice President & Head of Early Discovery Platforms, and Dr. Tim Dwight, Senior Director of Medicinal Chemistry & Business Development. The discussion examined how integrated screening workflows with medicinal chemistry embeds greater scientific discipline to early drug discovery, streamlining the clearer decisions as programs advance from hit identification to lead optimization.

Hit Identification Starts with Target Context

As Dr. Bing Xia emphasized, hit identification is highly target-dependent and is not best approached as a fixed route. Strategy selection should begin with the target context, including biological validation, tractability, assay readiness, structural information, protein availability, resource constraints, and the broader IP and competitive landscape.

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 Viva Biotech's practical approaches for early target and modality assessment. By integrating DEL screening outcomes, protein science expertise, protein QC and conformational-state assessment, and an AI-powered V-DEL Friendly Index, this approach can help assess ligandability, rank targets or constructs, prioritize resources, and inform whether small molecules or linear/cyclic peptides may represent suitable modality directions. This can be especially valuable for first-in-class or less-characterized targets, where early data helps reduce uncertainty and guide resource allocation.

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.

Dr. Xia also discussed Viva Biotech's continuously updated "promiscuous frequent hits" dataset with masked target names. Built from accumulated screening experience, this internal resource supports more informed triage and helps reduce the risk of advancing misleading hits across screening campaigns.

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. Tim Dwight emphasized the importance of close coordination across medicinal chemistry, AIDD/CADD, biology, DMPK, and project teams. These cycles often operate on a weekly cadence, to align with primary assay workflows, allowing teams to generate new hypotheses, refine and select new designs, and prioritize focused compound sets.

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.

Dr. Dwight also noted that the scale of chemical change often evolves with the stage of the program. In hit-to-lead, larger scaffold or functional-group changes may be needed to remove liabilities, test tractability, and build backup series. As programs move into lead optimization, smaller SAR-driven changes often become more important for improving potency, selectivity, exposure, safety, and developability.

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, Viva Biotech supports a continuous discovery workflow, helping partners move from target understanding to validated hits and lead optimization with greater rigor, efficiency and scientific discipline.

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