USE CASES | ADETERA SYSTEMS IN PRACTICE

Scientific questions. Practical research outcomes.

These selected, anonymized examples show how tailored PlateX analysis and CardiX modeling helped research teams examine difficult signals, compare scenarios and focus their next development decision. They represent only a small part of ADETERA’s work; our projects and applications extend well beyond the cases shown here.

PLATEX | FIVE SELECTED CASES

Assay data and signal analysis.

From noisy measurements and overlapping events to historical plate data, these cases show how tailored analysis can make experimental recordings more useful for a research decision.

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PLATEX | ANONYMIZED CASE STUDY

Make a difficult assay usable for further research.

A difficult kinetic assay became usable for the next research stage, with consistent controls and stable calibration responses.

Case at a glance
Challenge
Nominally matched wells produced inconsistent peak statistics after separation and alignment.
Approach
Characterize the intensity-dependent noise and apply a tailored adaptive correction.
Outcome
Repeat controls and calibration supported a usable measurement and analysis workflow for further investigation.
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The illustration is a conceptual reconstruction, not experimental data.

Conceptual four-scene reconstruction of inconsistent well-level peak statistics, intensity-dependent skewed noise, adaptive correction and consistent repeat controls.

PLATEX | ANONYMIZED CASE STUDY

Compare main pulses and after-pulses independently.

Separate waveform collections and statistics gave the client a clearer basis for examining both event populations across drug concentrations.

Case at a glance
Challenge
Noise and overlapping responses obscured smaller after-pulses and produced compound peaks.
Approach
Adaptive denoising, proprietary reconstruction and aligned event collections separated the analytical questions.
Outcome
The client could examine main-pulse and after-pulse waveforms and statistics independently across concentrations.
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The illustration is a conceptual reconstruction, not experimental data.

Conceptual sequence of overlapping main pulses and after-pulses, adaptive denoising, model-informed waveform reconstruction and separate event analysis.

PLATEX | ANONYMIZED CASE STUDY

Make legacy plate data usable again.

A fragmented archive became an organized analytical resource that the research team could use to compare its historical studies.

Case at a glance
Challenge
Plate coordinates and well contents varied, while event assessment relied largely on manual inspection.
Approach
Dynamic plate mapping, adaptive denoising and specialized event detection organized signals by the relevant experimental groupings.
Outcome
The client could compare historical studies by section, family and concentration.
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The illustration is a conceptual reconstruction, not experimental data.

Conceptual sequence of a fragmented multiwell recording archive, dynamic plate mapping, adaptive denoising and event detection, and cross-study comparison.

PLATEX | ANONYMIZED CASE STUDY

Use cellular evidence to focus the next study.

Reconstructed cellular action potentials helped the team assess concentration-related features and define further investigation.

Case at a glance
Challenge
A noisy cardiomyocyte assay recorded a proxy related to membrane potential, rather than action potentials directly.
Approach
Tailored denoising and model-informed reconstruction supported assessment of duration and repolarization features.
Outcome
The analysis guided follow-up questions; separate hERG measurements retained their own provenance, and CardiX simulation was a possible later stage.
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The illustration is a conceptual reconstruction, not experimental data.

Conceptual sequence of noisy cardiomyocyte proxy recordings, tailored denoising, reconstructed action potentials and cellular feature assessment, with separate hERG-current evidence.

PLATEX | ANONYMIZED CASE STUDY

Guide candidate follow-up with usable burst statistics.

Event and burst statistics helped a research team focus drug-candidate priorities when conventional filtering distorted useful signal structure.

Case at a glance
Challenge
Extreme noise prevented reliable statistical confirmation of activity suggested by other evidence.
Approach
Proprietary statistical denoising was assessed on a group with known results before analysis of client recordings.
Outcome
The client obtained event and burst statistics that informed drug-candidate priorities.
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The illustration is a conceptual reconstruction, not experimental data.

Conceptual sequence of ion-channel bursts obscured by extreme noise, statistical denoising, known-result assessment and burst statistics for candidate follow-up.

CARDIX | FOUR SELECTED CASES

Cardiac modeling and the next investigation.

These model-based comparisons explore cellular variability, multichannel effects, co-medication questions and candidate prioritization. Each interpretation remains tied to the available inputs and modeling assumptions.

Explore CardiX
CardiX Validation Report

CARDIX | ANONYMIZED CASE STUDY

Compare one drug question across three virtual cell families.

A structured cellular comparison helped focus the client’s next concentration-dependent investigation.

Case at a glance
Challenge
A hERG potency result alone could not describe how different baseline cellular contexts would respond.
Approach
Applied the modeled hERG effect across selected concentrations and three separately defined virtual-myocyte families.
Outcome
A comparison of modeled cellular responses supported follow-up study questions without assigning clinical risk.
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The illustration is conceptual, not experimental data or a clinical prediction.

Conceptual hERG concentration input and separate baseline cell profiles feeding three virtual cardiac cell families, followed by comparative modeled responses.

CARDIX | ANONYMIZED CASE STUDY

Examine the cardiac question beyond hERG alone.

A side-by-side model comparison helped the team focus the channel and cellular evidence needed next.

Case at a glance
Challenge
A hERG-only interpretation could leave relevant multichannel effects unexplored.
Approach
Compared concentration-dependent hERG-only and combined hERG, calcium and sodium scenarios in a cellular model.
Outcome
The modeled differences informed follow-up questions without treating multichannel action as inherently protective.
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The illustration is conceptual, not experimental data or a clinical prediction.

Conceptual comparison of hERG-only and combined hERG, calcium and sodium inputs leading to different modeled cardiac action-potential patterns.

CARDIX | ANONYMIZED CASE STUDY

Investigate a reported concern in the context of co-medication.

A structured comparison turned the client-reported concern into hypotheses and priorities for further investigation.

Case at a glance
Challenge
Earlier hERG and assay findings did not resolve a concern reported during first-in-human development.
Approach
Compared individual-drug and co-medication scenarios under the available channel and concentration assumptions.
Outcome
The analysis focused follow-up hypotheses without proving clinical causation or predicting patient outcomes.
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The illustration is conceptual, not experimental data or a clinical prediction.

Conceptual retrospective workflow connecting a reported development concern with individual-drug and co-medication cellular-model comparisons and follow-up questions.

CARDIX | ANONYMIZED CASE STUDY

Select the next experiment from five AI-proposed candidates.

A computational comparison helped the early-discovery team select one candidate for its next laboratory experiment.

Case at a glance
Challenge
Five AI-proposed candidates had predicted hERG potency but no laboratory hERG measurements.
Approach
Compared modeled cellular effects across the client’s anticipated concentration range, treating potency predictions as uncertain inputs.
Outcome
One candidate was selected for laboratory testing; no safe dose or validated safety conclusion was assigned.
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The illustration is conceptual, not experimental data or a clinical prediction.

Five conceptual AI-proposed candidates with predicted hERG inputs and concentration scenarios compared computationally, with one selected for laboratory testing.

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Bring us the question behind your next decision.

Tell us about your data, workflow and the result your team needs. We can discuss the analytical question and the appropriate scope of work.

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