Student Leadership in Undergraduate Nursing Research: A Qualitative Content Analysis of Roles, Challenges and Professional Growth.

Precision medicine aims to improve clinical outcomes by aligning diagnosis and treatment with biological and clinical heterogeneity, rather than relying on population‐averaged effects from heterogeneous trial populations. In many development programs, this heterogeneity is acknowledged but rarely translated into explicit strategies for identifying responsive or high‐risk subgroups, leading to diluted effect sizes and suboptimal benefit–risk profiles. While oncology has established precision medicine as a default paradigm in many indications, progress in prevalent, multifactorial diseases (cardiovascular, metabolic, autoimmune) remains uneven despite advances in multi‐omics, digital phenotyping, and AI/ML. Existing discussions often focus either on technical biomarker discovery or late‐stage regulatory issues, without connecting early hypothesis generation, trial design, companion diagnostic development, and market access into an operational framework. To date, the most convincing demonstrations of this approach have emerged in oncology. The development of therapies such as trastuzumab for HER2‐positive breast cancer, vemurafenib for BRAF V600E–mutated melanoma, and endocrine therapies for hormone receptor–positive tumors established that genetically defined patient selection can dramatically improve both clinical outcomes and the commercial success of drug development. These successes reshaped regulatory expectations, normalized the co‐development of drugs and companion diagnostics, and made biomarker‐defined indications a default strategy in many oncology drug development programs. By contrast, progress in precision medicine has been far more limited in prevalent, multifactorial diseases such as cardiovascular disease, chronic kidney disease, metabolic disorders, autoimmune conditions, and metabolic dysfunction–associated steatohepatitis (MASH). In these indications, disease biology is distributed across multiple interacting pathways, clinical phenotypes overlap, and treatment effects are often modest when averaged across unselected populations. Despite broad recognition of underlying heterogeneity, sponsors frequently face practical barriers to implementing explicit precision strategies, including difficulty defining endpoints that are both mechanistically meaningful and acceptable to regulators, uncertainty about payers' willingness to reward narrower but higher‐value indications, and a reluctance to front‐load development costs by running broader phase I–II programs followed by smaller, biomarker‐enriched phase III trials.