Precision monitoring of cancer
treatment
response and drug
resistance.

Our flagship precision AI platform
tracks how individual cancers respond
to treatment over time.

Detect Early

Precisely catch early drug resistance signals before clinical failure

Contextualize Cases

Instantly compare active patients to similar historical profiles

Identify Pathways

Reveal the exact biological mechanisms driving treatment failure

Forecast Timing

Estimate precisely when therapy resistance is likely to occur

Guide Adjustments

Equip oncology teams with data driven treatment adjustment decisions

Improve Survival

Extend and save lives through earlier, proactive clinical intervention

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DNA precision analysis

Precision Understanding of
Resistance Mechanisms

Keti Flow analyses molecular and clinical patterns associated with tumor evolution in breast, ovary and ovarian malignancies. It identifies likely resistance pathways including adaptive signaling changes and therapy escape mechanisms.

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Precision treatment failure detection

Precision Detection of
Treatment Failure

Keti Flow detects these early transition signals with precision. This enables clinicians to identify loss of treatment effectiveness long before standard imaging or symptom based evaluation can pick it up.

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The Platform Actively Supports
Clinicians In Answering:

01

What specific biological changes are reducing treatment effectiveness?

02

Is resistance driven by mutation, pathway adoption or tumor heterogeneity?

03

Is the current therapy still biologically valid for this patient?

04

When exactly should treatment be escalated or switched?

Patient case analysis

Precision Learning From Prior Patient Cases

Keti Flow continuously learns from anonymized historical patient treatment datasets to improve future predictions and clinical recommendations. By matching current patients to previously treated cases with similar biological and clinical profiles, the system provides high confidence precision context.

Doctor reviewing patient data
01

Probability of resistance based on similar historical patients

02

Expected time to resistance under the current therapy protocol

03

Treatment strategies that previously improved survival outcomes in similar cases

04

Intervention timing patterns associated with optimal patient recovery