Embedding Clinical Context from Day 1 Featured in King’s College London SCPS Newsletter Supported by Venture Builder Incubator, University of Edinburgh Embedding Clinical Context from Day 1 Featured in King’s College London SCPS Newsletter Supported by Venture Builder Incubator, University of Edinburgh
De-risking biomedical discoveries

Embedding
Clinical Context
Into the R&D Process.

We are building CATALYST, a proprietary platform that ensures biomedical discoveries are on the path to clincial readiness from day 1. Currently focused on solid cancers, CATALYST integrates clnical context directly into the research workflow.

ACCESS CATALYST
Latest Platform Activity

King’s College London

Featured in the SCPS newsletter for embedding clinical context in oncology research.

News Feature

CATALYST Platform

Benchmarking gene signatures across 12,400+ cohorts to ensure clinical translatability.

Platform Build

VBI Edinburgh

Scaling automated technical due diligence within the Venture Builder Incubator.

VBI Cohort 6

Clinical Context in the R&D Process

Ensuring Research Stays on the Track of Clinical Readiness

01

Hypothesis Generation

Guide biological starting points using our clinical atlas, ensuring the research begins with a patient-relevant foundation.

02

Experimental Design

Structure experiments to reflect real-world patient heterogeneity, ensuring preclinical results are ready for the clinic.

03

Continuous Evaluation

Constant benchmarking of lab results against the clinical atlas to maintain a defensible path to translation.

CATALYST Solves For:

Academic Labs

Making lab discoveries translatable by refining pre-clinical research with clinical context from the earliest stages.

Early Startups

Building clinically translatable assets. Strengthen technical due diligence for Series A/B rounds by proving patient relevance.

Big Pharma

Verifying asset value and translatability during acquisition by testing clinical applicability across patient cohorts.

Under Development

Derisk Bio Academy

Industrial Skills Semester 2026

Series 01 • April 2026

Biomarker Discovery & Multi-Omics

Dataset discovery, bulk & single-cell RNA-seq analysis, and clinical meta-analysis pipelines.

Python / R / Scanpy
Series 02 • TBD

High-Dimensional Cytometry Analysis

RNA-to-Protein mapping, automated clustering with FlowSOM, and rare cell population discovery.

FlowJo / R / HCA
Series 03 • TBD

Spatial Biology & AI Pathology

AI cell segmentation, Tumor Microenvironment (TME) analysis, and cell-cell interaction networking.

QuPath / Cellpose / AI
Series 04 • TBD

Point-of-Care Diagnostics

Metabolomics discovery, LFA device logic design, and analytical validation for FDA/ISO standards.

LC-MS / LFA Design

Build an Interview-Ready Portfolio

No coding background required. Students and professionals will build an end-to-end project and publish a reproducible analysis report by the end of each weekend.

Foundation for Solid Cancers

Clinical Data Resources & Proprietary Models

200+
Datasets
6000+
Samples
300+
Cohorts
10+
Proprietary Models
10+
Collaborations
5+
Data Types

Scientific Proof of Approach