Platform

RNA QR codes two scores per sample

The platform turns whole-transcriptome data into a compact image and two quantitative scores: how far disease has moved a cell's gene network, and how far an intervention moves it back.

The same method runs on public repositories (GEO, TCGA, Connectivity Map) and on partner datasets, so discovery work can start before any new experiment is commissioned.

Illustration: an RNA QR code as a grid of active and inactive modules

Summary

~20,000 genes compressed into 80+ modules (metabolons) by Pairwise RNA Co-expression Analysis (PRCA).
Each sample becomes a 9 × 9 RNA QR code: one square per module.
Disruption Index (TI) measures how much disease has broken the network.
Restoration Index (RI) measures how much a drug or natural compound restores it.
Every approved drug can be re-scored on the same scale, against any indication with transcriptome data.

I. How an RNA QR code is read

From transcriptome to two scores

1. Transcriptome

Bulk RNA-seq or microarray expression data from disease, control and treated samples form the starting matrix.

Input: expression matrix (genes × samples).

2. Modules and RNA QR code

PRCA computes r ² for gene pairs across samples and groups co-expressed genes into metabolon modules. Each module is marked active or inactive and mapped into a 9 × 9 grid.

Output: RNA QR code (RQC) with >80 modules.

3. Disruption and restoration

Modules that change between healthy and disease samples contribute to the Disruption Index (TI). Modules that move back toward the healthy pattern under an intervention contribute to the Restoration Index (RI).

TI = disrupted modules / tracked modules.
RI = restored modules / disrupted modules.

Illustrative example; real codes track more than 80 modules. TI, originally called the Tumor Index, is read as a disruption index outside oncology.

Illustration: expression data flowing into a grid of RNA QR codes — Illustration. Pairwise co-expression collapses the transcriptome into module states; each sample becomes one code.

II. Compound-agnostic validation

One code, one scale, any intervention

This is not strictly a pharmaceutical platform. The code does not know whether a compound is synthetic or natural; it scores the network effect, on one scale, so the evidence stands on its own.

The platform reads the transcriptome, not the label. Pharmaceutical compounds, botanical extracts and natural products are all scored by their effect on the same network.

Same input. Disease models before and after the intervention, measured by RNA-seq or microarray.
Same code. The RNA QR code is generated by the same PRCA method regardless of what was applied; the compound never appears in the calculation.
Same score. RI = restored / disrupted modules, so drugs and natural compounds can be ranked on a single axis.

Validation here means measurement: how much an intervention restores disrupted modules in a defined model. It is not an endorsement of safety, nor of clinical efficacy.

Research-stage; not reviewed by the FDA.

Illustration: RNA QR code tiles compared on one scale — Illustration. Approved drugs, natural compounds and lifestyle interventions are scored on the same disruption/restoration scale.

III. Platform applications

Five high-impact use cases

RNA QR codes form a platform, not a single-indication assay. Every approved drug can be re-scored where quality transcriptome data exists.

1. Clinical-trial enrichment

Use pre-treatment RNA QR codes to identify likely responders and enrich trials for those patients, reducing noise and wasted spend.

2. Drug-efficacy ranking

Apply multiple candidates to a model, compute RI for each and rank by restoration score instead of waiting for long survival endpoints.

3. Drug repurposing

Compare a disease RNA QR code to a library of drug-response QR codes. High similarity suggests similar network effects and identifies candidates for follow-up.

4. Personalized combinations

For a given patient, match the tumor QR code to interventions whose response codes best counteract the disrupted modules, subject to standard-of-care and safety constraints.

5. Longitudinal monitoring

Regenerate the QR code after each treatment cycle; track RI over time to see whether the network is being durably restored or drifting toward resistance.

IV. Software

AlphaExpression platform

AlphaExpression is the cloud environment where PRCA computations, QR code generation and TI/RI analytics run. It is designed for research teams and contract labs.

Secure upload of expression matrices from academic or industry studies.
Automated computation of metabolon modules, RNA QR codes and TI/RI scores.
Dashboards for cohort-level comparisons and enrichment strategies.
API endpoints for CRO and pharma integration.

Early-access collaborations are available for oncology, autoimmunity and neuroscience programs.

Contact: [email protected]