patient-derived tumour samples screened
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compounds and combinations evaluated
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From patient-derived tumours to actionable oncology decisions
From patient-derived tumours
to actionable
oncology decisions
PreComb’s high throughput and automated platform accurately predicts drug-response of different drugs, doses and combinations.
A simple bridge from patient-relevant biology to oncology decisions
01
Patient-derived biology
Diverse tumour material provides the biological foundation for clinically relevant assessment.
02
Longitudinal functional profiling
Standardised, automated screening captures response and adaptation dynamics over time.
03
Decision-ready insight
Cross-model learning enables predictive, comparable outputs that inform development
Why translational
decisions remain uncertain
Key oncology drug development decisions are often made before durable response,adaptation, and resistance dynamics become visible in standard preclinical models.
Early discovery systems can be fast but lack patient-relevant complexity, while later in vivo work is slow, expensive, and difficult to scale. This forces teams to make compound prioritisation, indication strategy, and combination design decisions without sufficiently interpretable translational evidence.
As oncology pipelines grow more complex and combination strategies become the norm, early uncertainty increasingly translates into scientific risk, financial exposure, and downstream trial failures.
What this platform enables for oncology decision-making
Use functional response dynamics across patient-derived models to support earlier go / no-go decisions.
Earlier candidate prioritisation
Use functional response dynamics across patient-derived models to support earlier go / no-go decisions.
Clearer indication expansion decisions
Surface differential response patterns across tumour types and patient cohorts to inform indication and stratification choices.
Rational combination design
Assess synergy and resistance dynamics early to guide combination strategy before costly downstream commitment.
Improved translational decision confidence
Generate outputs aligned with development decision logic rather than isolated experimental endpoints.
Applications supported
Decision contexts the platform supports
Candidate prioritisation
Indication expansion and selection
Combination strategy development
Drug repurposing and repositioning
3DTwin® Dynamic Drug Response Screening
Patient-derived 3D microtumour screening generates longitudinal, functional drug response profiles under clinically relevant conditions. The platform is designed to support high-confidence translational oncology decisions early in development.
What this enables
- Earlier and more confident compound prioritisation
- Clearer indication selection across tumour contexts
- More informed combination strategy decisions
How we work
- Two stage project structure with go / no-go decision:
1 Model set up → go / no-go
2 Screening at scale
- Flexible engagement models: Fully managed service, self-serve, or hybrid.
Study design, model configuration and collaboration setup are defined per project.
Candidate prioritisation
Biologics
Immuno-oncology
CAR-T
Radiotherapy
Chemotherapy
Candidate prioritisation
Biologics
Immuno-oncology
CAR-T
Radiotherapy
Chemotherapy
Operational maturity and scientific scale
Scale, reproducibility and scientific credibility across translational oncology.
Javad Nazarian
- Professor, University of Zurich,
- Head of DMG Research Center,
- University Children’s Hospital Zurich
“One of the biggest challenges in cancer research is bridging the gap between preclinical testing and real patient outcomes. PreComb’s approach addresses this challenge by providing patient-relevant, functional models that allow us to test therapies in a way that truly mimics human biology.”
Discuss your
translational use case
Explore how PreComb’s platform can suppor decision-making across your oncology programmes.
