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The sequencing of the human genome and the subsequent availability of inexpensive, robust methods for “omics” profiling (e.g., genome-wide association studies, gene expression microarrays, and metabolomics) have led to optimism of a new era of biomarkers that would allow for a “precision medicine” approach to critical care. Unfortunately, this promise has yielded few tangible results, as the general biomedical reproducibility crisis (1–3) is particularly troublesome in critical care (4–8) and in omics biomarker studies (9–11). There are two broad problems that lead to seemingly similar studies of biomarkers in critical care producing different results. One problem is traditional nonreproducibility due to false positive biomarker selection or nonrobust statistical models. The other, more importantly, is a lack of generalizability in moving from a narrow study population into broader applications in critical care. We present here a contextual framework for addressing these problems and for assessing new biomarker studies.Many critical illnesses are defined syndromically, such as sepsis, acute kidney injury (AKI), acute respiratory distress syndrome (ARDS), and delirium. These syndromes typically have clear, though changing, clinical criteria (12–14). Still, a syndrome may arise from multiple causes; as a result, it is unclear whether all cases of the syndrome really represent the same disease. Such uncertainty raises a major problem in the field. For example, if a positive clinical trial for adults with ARDS defined by Berlin criteria has failed to reproduce in an independent population of children with ARDS also defined by Berlin criteria, was the original finding a false positive or do adults and children have a “different” version of ARDS? Our reliance on syndromic definitions and the lack of clear gold-standard diagnostics linked to pathophysiology thus makes it difficult to assess clinical trial results. In theory, if the entire clinical spectrum of a disease has a common molecular pathophysiology, then a molecular biomarker should exist that is generalizable to the disease. Thus, finding a generalizable biomarker can help to define the disease, improving both patient care and clinical trial design, and potentially moving a whole field of study forward.There are other practical reasons to search for biomarkers that are generalizable. First, requiring context-specific biomarkers for every variant on a clinical condition (e.g., a different biomarker for different sources of sepsis, or for each different cause of kidney injury) could end up requiring dozens of tests for each critical syndrome. Tests indicated for such increasingly fragmented populations will fail to overcome barriers to market entry. In addition, those that do make it may have overly specific indications for use, leaving many patients without help. Finally, since off-label uses of tests and therapies are common, if biomarkers fail to deliver similar performance in seemingly similar conditions, patients will be harmed.We thus argue that research should focus first on finding generalizable, disease-defining molecular biomarkers for syndromes in critical illness, or alternatively on showing that such biomarkers do not exist (evidence-of-absence studies). If no generalizable biomarker exists, then more context-specific biomarkers can direct the effort to accurately characterize clinically actionable syndromic subtypes. In other words, we need to clearly define a disease before we begin to divide it into subtypes. Both are necessary components of a precision medicine approach, but due to the high heterogeneity of critical illness, research of both types can be challenging.