Translational Medicine Platform

Move every translational program forward, defensibly.

Inflexa runs the analyses that drive a translational decision: responder stratification, biomarker discovery, mechanism of action, and target prioritization. Every conclusion arrives with PubMed-cited literature and a complete audit trail.

Analytics

Method choices that fit your cohort.

An analysis agent reads the existing literature for your biology, evaluates the shape of your dataset, and designs a multi-step plan with method choices you can inspect and override. The agent does not run a single canned pipeline. It reasons about which pipeline applies to your biology and your cohort structure.

When multiple methods are applicable, the agent runs all of them and surfaces only the findings that hold up across approaches. Multi-method consensus separates signal from statistical artifacts, especially in underpowered translational cohorts where analytical choice can change the conclusion.

Coverage spans bulk and single-cell transcriptomics, proteomics, metabolomics, and multi-omics integration. Every step is traceable: method, parameters, intermediate results, and the agent’s reasoning are all captured in the provenance record.

PROTECT: Pediatric UC Responder Analysis
12 steps
RNA-seq QC + cohort audit
transcriptomics
Confounder-adjusted DE
transcriptomics
IPTW + causal sensitivity
statistics
Immune deconvolution
immunology
GSEA pathway enrichment
transcriptomics
Co-expression hubs
network
Mechanism-anchored targets
integration
Druggability + chemistry
therapeutics
Signature-reversal repurposing
therapeutics
Pediatric safety review
therapeutics
PK/PD + clinical context
therapeutics
Final dossier
integration

Click a step to see details

Reporting

Reports your translational team can actually use.

Tell Inflexa what story you need to tell: responder stratification, biomarker association, survival by signature, pathway breakdown. The platform assembles a navigable, interactive report in the same conversation as the analysis, with no exporting and no reformatting.

Reports are designed for iteration. Ask for a different visualization, pull in additional context, or tighten the interpretation. Every version is preserved with its provenance intact. Share directly with translational leadership, clinical collaborators, or external partners.

Each section of the report is linked back to the analysis steps and source data that produced it. When a reviewer asks why a finding appears, the answer is one click away.

INFLEXA
Summary
Study Design
Arab Cohort
Differential Expression
Pathways
Dose-Response
Immune
TF Activity
Pathway Networks
Genomics
Survival
Synthesis
Limitations

Generated by Inflexa on February 20, 2026 at 9:00 PM

Survival & Prognosis

HR=1.05p=0.84
Total Effect (Null)
1.2%(2/167)
Signature Overlap
0.652
EA C-index
37–48%
TF SHAP Share
HR=1.05p = 0.837

Total ancestry effect on survival is null

After adjusting for subtype, age, and stage, African ancestry does not confer a survival advantage or disadvantage (OS endpoint, n=957, 137 events). Breast cancer survival disparities are largely explained by clinical factors, not ancestry-specific molecular features.

SHAP Feature Importance: Ancestry-Specific Survival Models

Top 20 features by mean |SHAP| value for each ancestry-specific CoxPH model. Colors indicate feature group.

TF activity
Pathway
Immune
Checkpoint
Genomic

EA Model (C-index = 0.652)

NT5E
0.234
PAX7
0.173
Macrophages
0.146
(HM) Estrogen resp.
0.134
EHF
0.113
FOXA2
0.106
PTF1A
0.102
MSX2
0.101
LAG3
0.099
(HM) KRAS sig. down
0.098
GFI1
0.092
(HM) UV resp. up
0.083
Neutrophils
0.082
HDAC5
0.081

Mean |SHAP|

AA Model (C-index = 0.408)

(HM) PI3K Akt mTOR
0.510
Th2 cells
0.364
LAG3
0.290
KDM5C
0.252
GRHL2
0.215
HEY1
0.154
FOXP1
0.154
(IPA) ERK MAPK Sig.
0.151
(HM) Angiogenesis
0.133
(HM) KRAS sig. down
0.130
iDC
0.130
(HM) Reactive O₂
0.129
ADORA2A
0.127
KCNIP3
0.121

Mean |SHAP|

AA model is dominated by PI3K–Akt–mTOR (SHAP=0.510), while EA spreads importance across TF and checkpoint features. NT5E (CD73) is the top EA feature, consistent with adenosine-driven immunosuppression.

Causal Mediation: Ancestry → Survival

Indirect effect of ancestry on OS through each mediator (n=957, 137 events).

TReg
ind = −0.089p=0.030
Significant
PD-1
ind = n/ap=0.064
Marginal
AMPK
ind = n/ap=0.918
Not significant

Prognostic Signature Divergence

Of 165 unique prognostic genes, only 2 (1.2%) are shared between EA and AA, the most extreme divergence at any molecular layer.

82
EA only
85
AA only
2
Shared
SharedGNG4RPS6KA6

Top Prognostic Genes by Ancestry

CoxPH coefficient and hazard ratio. Direction indicates risk-up vs risk-down.

EA Signature

n=726, 101 events, C=0.652

GeneCoefHRDirPIGR-0.14510.865L1CAM+0.14461.156LOC100130148-0.14000.869

Showing 3 of 82 genes

AA Signature

n=106, 13 events, C=0.408

GeneCoefHRDirEN2+0.07251.075PEG3+0.06091.063TMSB15A+0.05971.061

Showing 3 of 85 genes

Provenance

Defensible by design.

Every conclusion in an Inflexa dossier rests on three foundations a reviewer can audit without talking to you: PubMed-grounded literature, an immutable record of every step, and a walkable map from raw input to final figure.

Literature evidence chains

Targeted PubMed queries against each programme's hub genes, transcription factors, and pathways. Every claim links to its supporting PMID, tiered from basic biology to preclinical to clinical.

Full audit trail

Every action (input, method, parameters, output) is logged the moment it occurs and sha256-verified. Entries are immutable, and reproducibility is built in.

End-to-end lineage

Click any conclusion and walk back through transformation steps to the source data. Every intermediate artefact is versioned and content-hashed.

Literature evidence chain
CXCL13 · 3 claims · PubMed
  • Basic biologyPMID 19620293

    CXCL13 is expressed by T follicular helper cells and drives B-cell recruitment in inflamed tissue.

  • PreclinicalPMID 28842433

    CXCL13 blockade reduces B-cell infiltration and attenuates colitis severity in murine UC models.

  • Elevated CXCL13 associates with treatment non-response in pediatric UC cohorts.

Audit log
9 artifacts · sha256 verified
ArtifactTimestampIntegrity
  • final_recommendation.md
    T4S2/output
    4/19/26, 9:02 PM
    1eae4274
  • molecule_grid_top_candidates.png
    T4S2/figures
    4/19/26, 9:02 PM
    28331cb7
  • scaffold_ranking.csv
    T4S2/output
    4/19/26, 9:02 PM
    492baa68
  • comparison_table.csv
    T4S2/output
    4/19/26, 9:02 PM
    47498e57
Data lineage
T1S1 · run 6382f44e…
de_analysis.R
T1S1/scripts
GSE126848_counts
Storage · 1.3 MB
acquire_pde4.py
T1S1/scripts
45.4s
volcano_NASH_vs_healthy.png
T1S1/figures · 752 KB
volcano_NASH_vs_NAFLD.png
T1S1/figures · 364 KB
Featured case study

From Confounded Cohort to Druggable Hypotheses

A translational deep-dive into pediatric UC non-response: 206 patients, three actionable programmes, one major disqualification, and a novel anti-CXCL13 target.

PROTECT cohort206 patientsmulti-omicsresponder analysis
Translational priority rankingPROTECT cohort · n=206

After PK/safety/readiness penalties, rosiglitazone falls despite top biology; sodium butyrate rises to #1.

ScorePioglitazoneTofacitinibRosiglitazoneUpadacitinibMesalamine [bench]Sodium butyrate00.20.40.60.81Biology (S9)Translational (S11)
S11 = biology (0.25) · PK/PD (0.20) · clinical evidence (0.25) · safety (0.20) · readiness (0.10)
Your storage, your data (BYOS)
Full provenance for every result
Literature-grounded methods
Enterprise-grade security
HIPAA and GDPR ready
Ready When You Are

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Tell us about a translational dataset you care about. We’ll scope a paid discovery collaboration in 2–3 weeks and run a full analysis.