hERG Liability
Prediction Service
Identify potential KCNH2/hERG channel blockade early, compare analog risk, and prioritize the compounds and experiments most likely to clarify cardiac safety liability.
hERG Liability Prediction Services
Each service can be used independently or combined into a staged workflow that moves from broad compound screening to detailed analog review and experimental planning.
The workflow begins with the safety question or development decision, not with a predefined modeling package.
Library-Level hERG Triage
Rank virtual or designed compounds before synthesis and prevent high-risk chemotypes from consuming downstream resources. Blocker probability, series-level risk map, test-priority shortlist.
Analog and Series Risk Review
Separate useful medicinal chemistry signals from unsupported extrapolation by reviewing matched analogs and local chemical context. Nearest neighbors, matched-pair contrasts, confidence notes.
Interpretable Liability Mapping
Translate model outputs into structure-linked hypotheses without presenting fragment associations as guaranteed fixes. Atom contribution maps, physicochemical drivers, redesign hypotheses.
Electrophysiology Follow-Up Planning
Use risk and uncertainty together to select the smallest informative experimental panel. Patch-clamp priorities, positive/negative controls, advance/redesign/test tiers.
Custom Model Development
Incorporate proprietary hERG assay data into a validated, project-specific scoring model. Assay-aware curation, model validation, reproducible scoring package.
Safety Dossier Support
Provide structured hERG risk assessments and interpretative summaries for regulatory submissions, with clear distinction between prediction, evidence strength, and experimental need.
Iterative Lead Optimization
Integrate hERG predictions into medicinal chemistry design-make-test cycles. Rapid feedback on analog designs, matched-pair analysis, and synthesis prioritization.
Turn a model signal into a defensible next move
A score alone cannot tell a project team whether to advance, redesign, or test. We pass every hERG signal through a connected evidence relay so that each result arrives with its context intact.
The output is not a binary label, but a traceable decision narrative linking model response, chemical precedent, uncertainty, and the next experiment.
Consensus classifiers and potency models establish the initial liability signal without hiding model disagreement.
Nearest neighbors, matched pairs, and scaffold history show where the prediction sits in known chemical space.
Applicability, assay coverage, model agreement, and structural alerts reveal when a result should be treated cautiously.
Advance, redesign, deprioritize, or confirm—each route is paired with the most informative follow-up action.
Translate compound safety questions into a modeling plan
hERG risk assessment becomes more efficient when the specific development decision or safety concern is connected to a computational approach.
Common drug development questions
Consensus hERG risk and uncertainty triage with risk-tiered patch‑clamp priority list.
Matched‑analog and local chemical‑space comparison with supported structural hypotheses.
Applicability‑domain and model‑agreement review with confidence‑qualified interpretation.
Assay‑aware data curation and model validation with reproducible scoring package.
Risk + uncertainty + structural interpretation to select the most informative next step.
Computational responses
The modeling strategy is selected according to the specific safety question and the evidence needed to make a development decision.
One channel, five very different prediction territories
hERG evidence changes with chemical maturity. Our analysis adapts the question, evidence standard, and decision output to the territory each molecule occupies.
Known pharmacology
Anchor the project against well-characterized blockers and non-blockers to expose assay and model bias.
Decision role: calibrateActive lead series
Read local SAR across close analogues and identify which substitutions move risk in a reproducible direction.
Decision role: rankVirtual redesigns
Challenge proposed modifications before synthesis and separate robust improvements from model-sensitive guesses.
Decision role: redesignUnfamiliar scaffolds
Map domain distance and uncertainty explicitly when a novel core lacks close experimental precedent.
Decision role: de-riskEmergent structures
Screen predicted metabolites, degradants, and transformation products for liabilities absent from the parent molecule.
Decision role: extend coverageConnect molecular structure to safety decisions
hERG liability spans multiple modeling scales. QSAR and machine‑learning models provide broad screening, molecular docking and dynamics offer structural insight, and consensus approaches balance sensitivity with specificity.
Our platform integrates curated hERG activity data, interpretable models, chemical‑neighborhood analysis, and uncertainty context to support decision‑ready reporting.
Broad AI screening narrows the candidate space before higher‑cost structural or experimental work is performed. Every prediction is reported with applicability‑domain and confidence context.
Classification and regression models using fingerprints, physicochemical descriptors, and graph representations.
Combine multiple algorithms to balance sensitivity, specificity, and agreement‑based confidence.
Compare each candidate with training‑set chemical space and flag unsupported chemotypes.
Atom contribution maps, matched‑analog analysis, and physicochemical driver identification.
Assay‑aware data curation, protocol harmonization, and risk‑tiered confirmation planning.
Different safety questions require different modeling strategies
These examples illustrate how a project can be structured around a specific development decision or experimental bottleneck.
Which compounds are most likely to block hERG?
Structure standardization → consensus scoring → risk‑tiered shortlist with applicability‑domain and confidence flags.
Output: prioritized synthesis list and testing recommendations.Which analog changes improve cardiac safety?
Matched‑analog review → contribution mapping → redesign priorities with structural hypotheses.
Output: analog‑ranking table and suggested modifications.How to allocate patch‑clamp capacity effectively?
Risk + uncertainty → panel design → confirmation plan with positive/negative controls and acceptance criteria.
Output: prioritized experimental plan and control selection.Can proprietary data improve prediction accuracy?
Assay‑aware curation → model validation → consensus scoring with project‑specific calibration.
Output: validated internal model and reproducible scoring package.From safety question to decision‑ready report
The workflow is customized around the compound series, available data, and the specific decision the client needs to make.
Define the Question
Identify the safety decision: triage, analog comparison, experimental planning, or regulatory support.
Curate Data
Standardize structures, hERG assay values, protocol metadata, and project thresholds.
Run Models
Apply consensus QSAR/ML, applicability‑domain analysis, and structural interpretation.
Review Evidence
Examine predictions, nearest neighbors, matched analogs, and confidence flags together.
Deliver Decision
Provide risk tiers, testing priorities, redesign hypotheses, and recommended next steps.
Results designed for development decisions
The final package combines candidate rankings, structural interpretation, calculated datasets, and a targeted experimental plan.
hERG blocker probability, risk tier, and potency estimate or interval.
Applicability‑domain flags, model agreement, and nearest‑neighbor evidence.
Atom contribution maps, matched‑analog comparisons, and physicochemical drivers.
Risk‑tiered compound ranking with clear advancement, redesign, or test recommendations.
Patch‑clamp priorities, controls, acceptance criteria, and decision tree.
Calculated datasets, model outputs, plots, structures, and documentation.
Planning a hERG liability project
Does a low predicted hERG risk replace patch‑clamp testing?
No. The prediction is an early triage tool. Regulatory and development decisions require fit‑for‑purpose experimental electrophysiology and broader cardiovascular assessment.
Can assay values from different protocols be combined?
They can be reviewed together, but protocol, temperature, cell system, endpoint, and qualifier differences must be retained and may require stratification or separate models.
Can you explain which atoms or fragments drive risk?
Yes. We can provide model contribution maps, matched‑analog comparisons, and physicochemical interpretation, while clearly distinguishing association from causal mechanism.
Can proprietary hERG data improve the model?
Often yes, especially for a coherent chemical series measured under a consistent protocol. We first assess label quality, range, chemical diversity, and sample size.
How are uncertain predictions handled?
Candidates outside the applicability domain or with model disagreement are flagged explicitly and generally prioritized for experimental resolution rather than overinterpreted.
What information is needed to start a project?
Helpful inputs include structures, development stage, chemical series, exposure context, risk thresholds, available hERG assay values, and the decision the study should support.
Which compounds need cardiac safety attention?
Share your compound structures, development stage, and safety questions. CD ComputaBio can develop a customized hERG liability prediction workflow that delivers decision‑ready evidence.
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