Biomarker understanding first lessons from drug development for IgA-driven autoimmune and fibrotic diseases.

The concept of personalized medicine and its significant benefits for patients and society was introduced over three decades ago. The Human Genome Project (initiated in 1990 and completed in 2003) greatly accelerated the development of precision medicine. In many cancers, defined biomarkers are used to select patients for therapy. For example, KRAS mutations are used to guide treatment with Sotorasib, while tumor expression of (wild type) human epidermal growth factor receptor 2 and 3 (HER2 and HER3) are used to select patients for trastuzumab and cetuximab, respectively. Nonetheless, the clinical adoption of companion diagnostics to facilitate a patient-centric approach in inflammatory diseases remains disappointing. One key reason why the development of companion diagnostics may be delayed autoimmune and fibrotic diseases can be the timing when clinical development teams inform R&D teams about relevant biomarkers or companion diagnostic to select patients, disease monitoring or treatment termination decisions. For clinical practicality, it is highly preferred to measure a biomarker in the systemic circulation, as blood samples can be obtained relatively easily in most diseases. However, discovering systemic biomarkers during clinical development has proven extremely challenging. Here, we describe an alternative approach, which we have used to select the most appropriate target for IgA driven autoimmune and fibrotic diseases. In this specific context, autoantigen-specific assays to determine autoantibody serum levels are widely available for a variety of indications. A detailed analysis of the biological pathways that affect the biomarker can uncover multiple potential therapeutic targets, allowing selection of the most optimal target from a clinical development perspective. Identification of a relevant biomarker before clinical development is initiated, enabling patient stratification in early clinical studies. Selection of the appropriate patient population based on biomarker presence reduces the number of patients needed and consequently, clinical development costs. Moreover, such a patient stratification approach minimizes the risk of including patients who are unlikely to respond, thereby avoiding unnecessary adverse events. This approach was applied during the selection of an anti-CD89 antagonist monoclonal antibody for IgA-mediated autoimmune and fibrotic diseases, serving as an illustrative example of this novel strategy.