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PRODUCT · SERVICE PLATFORM

PortraiTARGET

Smarter target discovery for ADCs, RPTs, and bispecifics — powered by spatial biology

PortraiTARGET™ leverages spatial transcriptomics, AI modeling, and multi-scale validation to unlock novel targets and design smarter therapies — from tumor-selective ADCs to dual-targeting degraders.

MODALITY COVERAGE
ADC · RPT · Bispecific · Degrader
ANALYSIS DEPTH
Spatial transcriptomics + AI + Microscopic-PK
OUTCOME
De-risked, tumor-selective targets

WHY PORTRAITARGET

Bulk-RNA misses what the tissue tells you.

Standard pipelines treat tumors as a single bag of cells. PortraiTARGET reads the actual spatial architecture — neighborhood context, payload reach, off-target risk — and turns it into actionable target intelligence.

  • 01

    Spatial-first target intelligence

    Intra-tumoral expression, neighborhood context, and whole-body toxicity in one analysis. Tumor-selective targets surface where bulk-RNA averages would have hidden them.

  • 02

    Physics-aware drug design

    Microscopic-PK modeling of vessel density, internalization kinetics, and linker cleavage — payload delivery is simulated before any molecule is synthesized.

  • 03

    De-risked at every step

    Multi-scale validation — from spatial co-localization in tissue to dose maps in vivo — catches efficacy and safety risks while they are still cheap to fix.

WHAT IT DOES

From spatial data to a viable target

Six analyses on one platform — covering target selection, payload optimization, and dose prediction across modalities.

  • Target selection

    Molecular-to-Spatial Target Mapping

    Maps intra-tumoral expression, neighborhood context, and whole-body toxicity to surface actionable, tumor-selective targets.

  • Heterogeneity check

    ITEM Analysis

    Intra-Tumoral Expression Mapping evaluates spatial heterogeneity and pinpoints targets with consistent tumor expression and minimal off-target spillover.

  • ADC efficacy forecast

    Bystander Effect Quantification

    Mean Target-High Distance (MTHD) identifies spatial configurations where low-expressing cells benefit from neighboring high-expressing regions — forecasting ADC response.

  • Modality pairing

    Optimized Payload Strategies

    Match ADC linkers to cleavage-enzyme zones, model RPT spread by vasculature & hypoxia, and identify dual-target zones co-localizing with E3 ligase for degraders.

  • Payload delivery

    Microscopic-PK Dynamic Concentration Maps

    Physics-based modeling of vessel density, target abundance, and internalization kinetics produces high-resolution temporal maps of payload delivery — and the share of tumor cells exceeding IC50.

  • RPT dosimetry

    Radiation Dose Prediction

    Estimates absorbed radiation dose (Gy) in tumor tissues for agents like Lu-177, accounting for vessel proximity, receptor targeting, and microenvironmental barriers.

MODALITIES

Built for the modalities reshaping oncology

Spatial biology is modality-aware by default — the same platform decodes ADCs, RPTs, bispecifics, and degraders without rebuilding the analysis stack.

  • ADCs

    Tumor-selective targets, linker-payload pairing against cleavage-enzyme zones, and bystander-effect forecasting via MTHD.

  • RPTs

    Radiopharmaceutical therapies modeled by vasculature and hypoxia distribution, with absorbed-dose maps for Lu-177 and similar agents.

  • Bispecifics

    Dual-target spatial co-localization analysis to design engagers that fire only where both signals are present.

  • Degraders (DACs)

    Identifies dual-target zones co-localizing with E3 ligase — refining degrader delivery and selectivity.

USE CASES

Use PortraiTARGET to:

Five concrete outcomes our partners pursue with the platform.

  • Discover novel tumor-specific targets

    Surface targets standard bulk-RNA pipelines miss, validated against intra-tumoral spatial context and whole-body toxicity signals.

  • Design ADC/RPT payload strategies

    Use real tissue spatial data — not idealized assumptions — to pair payloads, linkers, and isotopes with the spatial biology of the actual tumor.

  • Build co-development-ready assets

    Identify clinical indications and biomarkers for patient stratification, with pre-validated efficacy and safety metrics ready for partnership.

PARTNER WITH PORTRAI

Co-develop the next ADC, RPT, or degrader.

Portrai partners with biotech and pharma teams to apply PortraiTARGET to internal candidate lists and build smarter, safer therapies — with a physics-aware drug design approach.