Review highlights the role of predictive biomarkers in acromegaly management, indicating advances from the ACROFAST trial.
Personalized medicine has gained importance in the management of acromegaly, driven by advances in tumor classification, molecular profiling, and imaging modalities. This approach leads to achieved biochemical control more frequently and in a shorter time frame when compared to the usual trial-and-error approach using first-generation somatostatin receptor ligands (fgSRLs) as first-line drug, which is still currently recommended in most clinical guidelines. In this review, we summarize recent advances in personalized medicine for acromegaly, with a particular focus on predictive markers of surgical and medical treatment response. Moreover, we highlight the perspectives gained from the ACROFAST clinical trial, which has contributed with valuable insights into the clinical implementation of individualized therapeutic strategies. We consider that the future of research in acromegaly lies in the continued advancement and refinement of personalized medicine approaches. ACROFAST has laid critical groundwork by demonstrating how the combination of predictive biomarkers enhances therapeutic outcomes, improving the rate of biochemical remission and in a shorter follow-up period. In addition, the application of artificial intelligence and machine learning algorithms trained on multiomic and clinical datasets may be useful to improve outcomes and reduce the trial-and-error nature of current pharmacologic management of acromegaly.
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Araujo‐Castro et al. (2025) studied this question.
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