Turning biological insight into better clinical development decisions

Patients with the same diagnosis can have very different disease trajectories and responses to treatment. For drug developers, this creates a difficult question: how do we identify the people whose biology best matches the treatment being studied? 

Biomarkers can help answer that question. These measurable biological signals can guide patient selection and help researchers understand what happens during treatment. However, their value depends on more than scientific promise. A test must also work reliably within the realities of recruitment, laboratory operations and patient care. 

For sponsors and contract research organisations, the opportunity is to plan biomarker science and trial delivery together. Glycomics, the study of the sugars attached to proteins and other molecules, offers a useful example of why this matters. 

What Glycomics Can Add 

Glycans influence how proteins function and how the immune system behaves. Their patterns can change with inflammation and disease, offering an additional way to investigate biological differences between patients. 

This is particularly relevant in chronic inflammatory conditions, where a shared diagnosis may conceal different underlying processes. Studying glycan patterns could help researchers identify meaningful patient groups, investigate disease progression or explore changes during treatment. 

These possibilities require careful validation. A pattern associated with disease does not automatically predict treatment response. Researchers must establish what a proposed biomarker measures, what decision it is intended to support and whether it adds useful information to existing assessments. 

That distinction matters commercially as well as scientifically. Investment in a biomarker should be linked to a defined development question, such as identifying patients at greater risk of progression or investigating who might benefit from a particular therapy. 

A Smaller Trial Can Require More Screening 

Selecting patients using biomarkers is often called trial enrichment. Depending on the study, it can help researchers detect a treatment effect with fewer participants. FDA guidance describes approaches that select people at higher risk of an outcome or more likely to respond to treatment. 

Consider a hypothetical therapy intended to prevent arthritis. If very few participants would develop arthritis during the study, demonstrating prevention becomes difficult. Identifying people at greater risk could make the question easier to answer. 

However, finding those people may require testing many who will not qualify. A smaller enrolled population can therefore involve a larger screening programme. The relevant business question is whether the scientific benefit justifies the total screening effort. Budgets should include sample collection, transport, testing, repeat visits and recruitment delays. Teams should also consider whether a narrowly selected population will limit how broadly the results can be applied. 

Designing the Science and the Workflow Together 

I am working closely with Dr Ashfaq Ahmad, a senior assay development scientist at Ludger, on evaluating candidate glycan biomarkers and developing assays for potential use in clinical trial enrichment. We consider both together because they affect patient selection, the testing workflow, and the time and cost of screening. 

A blood test may appear straightforward, but the journey from patient to recruitment decision involves several steps. The clinic must collect the right sample, arrange suitable storage and transport, and receive a result in time to act. 

A test that takes hours to perform can still take days to reach the clinical team. Transport schedules, laboratory batching and repeat analysis can all affect turnaround. An unusable sample may mean another appointment and blood draw. At Ludger, glycan analysis and advisory services include glycan profiling and detailed characterisation, alongside measurements such as sialic acid and monosaccharide analysis. Such capabilities support the investigation of glycosylation; using a result to select trial participants requires additional evidence for that specific purpose. 

Sponsors, CROs, clinical teams and specialist laboratories should agree these requirements before recruitment begins. The laboratory is a contributor to trial design, with practical knowledge that can expose unrealistic assumptions early. Patient experience also belongs in this discussion. People who do not qualify have still given their time and samples. Clear explanations of what screening involves, when results will arrive and what those results mean can help make participation more manageable. 

Moving From Research to Usable Products 

The same thinking applies when developing new tests. At Avenna, we are developing glycomic blood biomarker tools for inflammatory diseases, including work on the Immunofrailty platform, with the aim of supporting earlier detection and treatment personalisation. 

These are development objectives. Each intended use needs appropriate evidence before a test can guide clinical decisions. The challenge is to translate a research finding into a repeatable measurement, an interpretable result and a workflow that fits its intended setting. A complex laboratory method may be appropriate for discovery. Wider use may require a simpler format, consistent performance across laboratories and a clear account of what clinicians should do with the result. 

Evidence should also reflect the people and settings in which the test will be used. Performance observed in one research cohort may not carry over to another population. Independent validation and comparison with current practice help establish whether the additional measurement changes a useful decision. Product development should therefore begin with the decision the test will support. It should address sample requirements, reliability, affordability and the evidence needed for the intended clinical and regulatory pathway. 

Learning From Staged Testing 

Sometimes the best approach combines tests. The AHEAD 3–45 Alzheimer’s prevention study design uses a blood biomarker to help identify people who should proceed to a PET brain scan. The scan then assesses whether their brain amyloid level meets the trial’s requirements. 

This illustrates how an initial test can reduce the need for more demanding procedures. However, the design paper does not establish realised cost savings. Teams must also consider whether the first test could exclude people who would have qualified. 

For CROs and sponsors, the lesson is to evaluate the complete recruitment pathway. Biomarkers can help make clinical programmes more informative, but success depends on reliable testing, realistic delivery plans and evidence that the selection strategy answers the study’s question. Building those elements together gives precision medicine a practical route from biological insight to better development decisions. 

Sources for Editorial Review 

Supporting references are separate from the article word count. Company references support factual descriptions of current services and development work, rather than evidence of clinical performance. 

Glycans in Immunologic Health and Disease 

https://pubmed.ncbi.nlm.nih.gov/33577348/ 

FDA Enrichment Strategies for Clinical Trials guidance March 2019 

https://www.fda.gov/media/121320/download 

The AHEAD 3–45 Study Design of a prevention trial for Alzheimer’s disease 

https://doi.org/10.1002/alz.12748 

Ludger Glycan Analysis and Advisory Services 

https://www.ludger.com/glycan-analysis-services/ 

Avenna Research and Development 

https://avenna.com/research-projects/ 

Avenna Immunofrailty Live Project 

https://avenna.com/immunofrailty/