project-idea

MuxDx Planner: A Multiplex Antibody Panel Designer for Lung Cancer Diagnosis

A single multiplexed antibody panel can now deliver comprehensive lung cancer diagnosis — tumor classification, biomarker assessment, and clinical features — from one tissue section, avoiding the tissue exhaustion that plagues sequential IHC testing.

Designing a multiplexed antibody panel for cancer diagnosis is currently an ad hoc process requiring deep domain expertise, iterative optimization, and access to expensive imaging systems. A panel design assistant tool would lower the barrier by guiding users through the key decisions: which markers to include (based on the diagnostic questions to be answered), which fluorophores to pair with which antibodies (based on spectral compatibility), and what controls to include.

The tool would have a library of published validated panels — including the lung cancer panel from this paper — that users can browse, adapt, or use as starting points. For new panel designs, it would check fluorophore spectral overlap, suggest antibody pairs with validated co-staining compatibility, and generate a structured protocol template and materials list.

A companion 'tissue budget' calculator would let pathologists input their expected biopsy fragment size and compare sequential IHC versus multiplexed approaches in terms of tissue consumption, number of tests completable, and estimated time-to-diagnosis. This could help justify the capital investment in multiplex imaging platforms at clinical labs.

Who Is This For?

Pathologists, translational researchers, and core facility staff setting up multiplex imaging workflows for cancer diagnostics.

Skills & Tools Needed

Web development
Fluorophore spectral database integration
Antibody marker database curation
Basic pathology and IHC knowledge
UX design for scientific tools

Feasibility

medium — The core functionality (panel library + spectral compatibility checker) is buildable with existing public data; the challenge is making it comprehensive and clinically trustworthy enough for adoption.

Inspired by: Single-section multiplexed imaging enables comprehensive lung cancer diagnosis

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