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Background: Tumour immunoprofiling captures tumour-microenvironment interactions and enables precision medicine. Multiplex immunofluorescence (mIF) imaging can provide comprehensive quantitative and spatial information for multiple immune markers. However, application at scale to clinical trial samples sourced from multiple institutions is challenging due to pre-analytical heterogeneity. Methods: We analysed 12'592 tissue microarray (TMA) spots from 3'545 colorectal cancers (CRC) sourced from more than 240 institutions in two clinical trials (QUASAR 2 and SCOT) stained for CD4, CD8, CD20, CD68, FoxP3, pan-cytokeratin and DAPI by mIF. TMA cores were multi-spectrally imaged by digital pathology and analysed by cell-based and pixel-based marker analysis. We developed and validated an adaptive thresholding method to account for inter- and intra-slide intensity variation in TMA analysis, compared the numerical results between analysis approaches and validated against the current gold standard of single-plex chromogenic immunohistochemistry (IHC). Results: Adaptive thresholding at a slide and spot level effectively ameliorated inter- and intra-slide intensity variation enabling high-throughput analysis of mIF-stained TMA cores by digital pathology and improving the image analysis results compared to methods using a single global threshold. Comparison of our mIF approach with CD8 IHC data derived from subsequent sections indicates the validity of our method (Spearman's rank correlation coefficients (SCC) between 0.63 and 0.66, p-value << 0.01). Evaluation of correlation between cell-based and pixel-based analysis results confirms equivalency (SCC > 0.8, p<< 0.01, except for CD20 in epithelium region) of both analytical approaches for precision immunoprofiling by mIF. Conclusions: This study reports an analytical approach to the largest multiparameter immunoprofiling study of clinical trial samples to date and establishes an adaptive thresholding method to account for inter- and intra-slide variation introduced by pre-analytical heterogeneity. This approach can enable the application of mIF immunoprofiling of clinical trial TMA datasets at scale.