Case studies · For Research & Industry
Make the research question more precise
Composite scenarios showing how research and industry teams can scope evidence, model and feasibility questions, with limitations documented from the start.
Illustrative composite scenarios
These are fictional composites that explain process and potential outputs. They are not real KPCIRC cases, testimonials or clinical or research outcomes.
Illustrative composite case 01
Build a structured molecular-evidence map
- Starting question
- How can a cohort’s molecular reports be organised consistently before looking for patterns?
- Available information
- Reports from a research cohort, with heterogeneous formats and evidence citations.
- The challenge or gap
- Findings, evidence sources and uncertainty must be organised consistently, with clear separation between observation and interpretation.
- Relevant KPCIRC pathway
- Research collaboration drawing on biomarker intelligence and evidence-curation methods.
- Analytical or review process
- Define a data dictionary. Separate observed report fields from clinical interpretation and research hypotheses. Document source provenance and uncertainty. Agree de-identification, access and permitted-use arrangements.
- Intended output
- An evidence matrix, an assumptions log and an analysis-ready schema within the project scope.
- Limitations and unresolved questions
- The evidence map alone does not establish causality, clinical actionability or treatment benefit.
- Appropriate next action
- Propose the cohort question and data context through the research enquiry.
Illustrative composite case 02
Explore a mutation-informed biological-model question
- Starting question
- Can a specific hypothesis about selected tumour-associated alterations and candidate compounds be tested in an appropriate investigational model?
- Available information
- A defined hypothesis, the relevant genomic evidence and a shortlist of candidate compounds.
- The challenge or gap
- The question needs narrowing, measurable endpoints and predefined controls before any model work is meaningful.
- Relevant KPCIRC pathway
- Research collaboration; OnKommon AVATAR may be discussed where the project fits its investigational fruit-fly workflow.
- Analytical or review process
- Refine the hypothesis, select a narrow question, connect genomic evidence with experimental design and measurable endpoints, predefine controls and document the model’s limitations.
- Intended output
- A scoped research plan, a candidate-comparison framework and a limitations statement.
- Limitations and unresolved questions
- A response in a model is not proof of efficacy, safety or likely response in a person.
- Appropriate next action
- Discuss scope and suitability with the research team.
Illustrative composite case 03
Assess trial-feasibility questions in a biomarker-defined group
- Starting question
- How well does a biomarker-defined group align with the criteria of several trial protocols?
- Available information
- A biomarker-defined group and a set of trial protocols whose criteria differ, with some fields missing.
- The challenge or gap
- Criteria are expressed differently across studies, and missing fields make alignment hard to judge.
- Relevant KPCIRC pathway
- Research collaboration using NLP-enabled trial-matching methods.
- Analytical or review process
- Normalise key terms. Map criteria as potentially satisfied, contradicted or unknown. Flag fields requiring human or site verification. Document the protocol retrieval date and recruitment caveats.
- Intended output
- A transparent feasibility matrix and a list of protocol questions to validate.
- Limitations and unresolved questions
- A research-level match does not mean an individual meets eligibility or can enrol.
- Appropriate next action
- Share the protocol set and group definition through the research enquiry.