Glen Clack on Optimizing ctDNA Platforms for Distinct Clinical Endpoints
Glen Clack

Glen Clack on Optimizing ctDNA Platforms for Distinct Clinical Endpoints

Glen Clack, Lecturer in Faculty of Health and Life Sciences Departmen at University of Exeter Medical School shared a post on LinkedIn:

Horses for courses: there is no such thing as the ‘best’ ctDNA assay, there is only the right assay for the question you are asking.
This is a point that gets lost surprisingly often in biomarker strategy discussions.

I have been reviewing the ctDNA monitoring landscape, comparing broad, platform-flexible approaches (like the multi-technology work from Caroline Dive’s group at Christie/CRUK Manchester) with highly focused tumor-informed MRD assays (like the hybrid-capture platform developed at RCSI), and the conclusion is straightforward but worth stating clearly:

These platforms are not competitors. They answer fundamentally different clinical questions. If you need rapid, serial pharmacodynamic readouts in advanced disease, cycle-by-cycle ctDNA dynamics to inform dose optimization, detect early molecular response, or identify resistance, you want a flexible, tumor-agnostic platform that can be deployed from plasma without prior tumor sequencing. Speed and adaptability matter more than limit of detection.

If you need to detect minimal residual disease at vanishingly low ctDNA fractions after surgical resection, to stratify recurrence risk or guide adjuvant therapy, you want a tumor-informed assay tracking hundreds of patient-specific variants with ultra-deep sequencing. Analytical sensitivity below 0.01% is what matters, and the longer lead time is acceptable when you are sampling quarterly, not every two weeks.

The mistake I see teams make is selecting a platform first and then fitting the clinical question around it. It should be the other way round.

Start with: What decision will this biomarker data inform? At what timepoint? In what disease setting? With what turnaround time? Then choose the assay, or combination of assays, that matches.

With ctDNA dynamics now showing strong predictive value for PFS and OS across immunotherapy, targeted therapy, and chemotherapy (and with the ctMoniTR initiative building the regulatory case for ctDNA as an intermediate endpoint), getting the assay strategy right at the protocol design stage has never been more consequential.

The technology is ready. The question is whether we are asking the right questions of it.”

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