Oppilotech Partners with Kiin Bio to Utilise Virtual Scientist Platform for Oncology Programme

Accelerating strategic decision-making through AI-driven disease prioritisation

Oppilotech Ltd is a UK-based biotech company developing COMET, a computational systems biology platform that uses machine learning to model complex biochemical networks in high resolution. COMET provides mechanistic insights into biological processes, helping scientists identify viable drug targets and determine the optimal therapeutic modality, whether inhibition, PROTACs, or molecular glues.

In collaboration with Dr. Simon Cook's group at the Babraham Institute, Oppilotech used COMET to model the MAP Kinase network, a pathway that regulates cellular proliferation and inflammation. This work led to the discovery of a novel target and early evidence that a PROTAC approach could be particularly effective.

The next challenge, however, was strategic: with the target implicated across multiple cancers and inflammatory diseases, which disease indications should Oppilotech pursue first?

Prioritising disease indications across oncology and inflammation

Identifying the right lead indication is one of the most difficult and resource-intensive steps in drug development. It requires a detailed integration of data across:

• Literature evidence on gene-disease associations

• Functional and mechanistic details

• Clinical trial registries

• Epidemiology and patient population data

• Commercial and competitive intelligence

With funding milestones approaching, Oppilotech needed to make fast, confident decisions, without the time and resource demands of weeks of manual research.

Solution: AI-powered disease prioritisation with KiinOS

To accelerate this process, Oppilotech partnered with Kiin Bio to leverage the Virtual Scientist Platform (KiinOS), a modular AI system that unifies over 100 specialised tools across biology, chemistry, and competitive intelligence.

Using our vResearchScientist and vBusinessAnalyst Virtual Scientists, Oppilotech integrated and analysed multi-source data to:

• Map gene-disease associations and patient population sizes across oncology and inflammation

• Evaluate clinical activity and competitive intensity, both within and beyond the PROTAC field

• Rank 20 disease indications by biological relevance, opportunity, novelty, and feasibility

• Continuously update analyses as new scientific or clinical data emerged

This combination of mechanistic context and commercial intelligence created a dynamic, data-driven roadmap for Oppilotech's oncology expansion.

Results: From weeks of research to hours of insight

In just a few hours, instead of the weeks or months traditional manual analysis would require, KiinOS delivered an integrated, prioritised assessment of 20 diseases.

Together, Kiin Bio and Oppilotech achieved:

• Rapid hypothesis generation and target characterisation across multiple disease types

• Actionable prioritisation of lead oncology and inflammation indications

• Full visibility into current and emerging competitive landscapes

• Scalable framework to evaluate future targets and new modalities

• Automated intelligence feeds to track new clinical, commercial, or mechanistic findings

Kiin Bio used their platforms to provide us with deep insights into different cancer and inflammatory indications, the competitive landscape for the different diseases, and a tangible route forward to rank and select our lead indications, saving us months of manual analysis.

Ajay Mistry,
CEO, Oppilotech

Transforming the path from discovery to decision

By combining COMET's mechanistic precision with KiinOS's AI-driven intelligence, Oppilotech gained a clear, evidence-based rationale for its lead oncology focus areas.

This collaboration accelerated prioritisation, de-risked early R&D investment, and gave Oppilotech the confidence to focus resources where biological rationale, patient opportunity, and competitive advantage converge.