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The RefinedScience platform combines unique institutional access to clinical data and patient tissue with AI analysis tools and biological validation — all on one integrated system.

The RefinedScience Platform

Most platforms in TechBio optimize on one dimension: faster target generation, larger datasets, or better models. The problem is that these capabilities operate in isolation from the patient biology that determines whether a drug actually works.

RefinedScience is different because our capabilities are integrated. Clinical outcome data is linked to single-cell molecular profiles. Molecular profiles are validated in real human tissue. Validation results inform patient stratification models. And all of it is grounded in longitudinal data from patients who were actually treated — not cell lines, not synthetic cohorts, not bulk averages.

The result is a platform that doesn’t just generate hypotheses — it generates biological evidence that holds up in the clinic.

AI tool preview

Ophira

Single-cell datasets contain millions of cells and thousands of measured genes. Ophira makes that complexity navigable — a clinically annotated explorer that lets any researcher pan, zoom, recolor, and filter a full atlas.

Visualize with cell maps and expression plots

Recolor the cell map by cell type, gene, or clinical variable and pan through millions of cells at full speed. Search any gene to pull up dot plots, violin plots, heatmaps, and cell proportion charts.

Query across modalities, datasets, and clinical variables

Work with RNA expression and surface protein data in the same view. Metadata is organized into curated, human-readable groups — cell annotations, sample info, and clinical variables — providing patient context.

Cohort explorer

Build cohorts from clinical and sample metadata, explore their composition interactively, then apply a cohort as a filter — every plot instantly re-scopes so you can compare groups directly.

Cell maps and expression plots generated from the public AML single-cell RNA-seq dataset (Zeng et al., Blood Cancer Discov 2025), accessible from Zenodo

Deep Clinical Data Infrastructure

Structured longitudinal patient data

Treatment history, outcomes, toxicities

Real-world and trial-linked datasets

External control capabilities

Single-Cell & Multimodal Molecular Profiling

Primary human tissue

Single-cell multi-omics

Organoid validation

High-resolution disease characterization

Advanced Analytics & AI Integration

Predictive modeling

Risk stratification

Hypothesis generation

AI-assisted data abstraction

Knowledge graph interrogation

Embedded Scientific Expertise

Clinical leadership

Translational scientists

Data scientists

Regulatory-aware decision framing

Functional Testing

Clinical leadership

Translational scientists

Data scientists

Regulatory-aware decision framing

Better biology at every stage compounds into a higher probability of approval.

The earlier a partner engages, the greater the compounding benefit across the full program arc. We are not a point solution for a single stage of development. We are a biology partner for the full journey.

Target Identification and Validation

Identify and validate biologically meaningful targets using integrated clinical outcomes and high-resolution human tissue data.

Identify targets using single-cell data linked to longitudinal patient outcomes, not bulk averages or not cell-line artifacts. Candidates are confirmed to be expressed on the specific cell populations that drive disease progression and relapse in actual patients.

Patient Stratification Refinement

Define clinically relevant patient subpopulations by linking molecular heterogeneity to real-world treatment response. Generate stratification hypotheses at the discovery stage where they’re cheap to test, not at Phase II, where they’re expensive to learn.

External Control Analyses

Build regulator-ready external control arms using propensity-matched analysis against our real-world longitudinal datasets.

Indication Expansion

Uncover new therapeutic opportunities by mapping molecular signatures to adjacent disease populations with shared biology.

Asset Repositioning

Re-evaluate existing assets through integrated human data to clarify responder populations, refine strategy, and improve development decisions.

ADC Target Discovery

Systematic identification of ADC targets in AML using single cell surface antigen mapping, tumor-initiating cell models, and functional validation in primary tissue.

Trial Design Optimization

Strengthen trial design through data-informed endpoint selection, inclusion criteria, and predictive risk stratification. Sharpen enrollment criteria, strengthen biomarker strategies, and build correlative science programs grounded in real patient biology. Our risk modeling and synthetic trial simulation capabilities let you test assumptions before committing trial resources.

Better biology at every stage compounds into a higher probability of approval.

The earlier a partner engages, the greater the compounding benefit across the full program arc. We are not a point solution for a single stage of development. We are a biology partner for the full journey.

Built for Oncology. Designed to Scale.

Our platform integrates clinical and molecular data in a way that is extensible across disease areas, creating long-term optionality while maintaining near-term scientific focus.

From Insight to Development-Stage Assets

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The essential data layer for AI-driven medicine

Let’s build the evidence that moves your program forward.

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