Precision medicine is moving healthcare towards therapies matched to a patient’s biological profile. Biomarkers are central to that shift because they can identify disease, predict treatment response, assess likely outcomes and measure whether a therapy is producing the intended biological effect.
Better patient selection can improve clinical efficiency. Rather than treating large, mixed patient populations, developers can focus on patients most likely to benefit from a specific therapy. That can support clearer trial design, stronger biological rationale and more targeted use of development capital.
Different biomarkers serve different roles. Diagnostic biomarkers confirm or classify disease. Predictive biomarkers help identify patients who may respond to a particular therapy. Prognostic biomarkers provide information about likely disease progression, while pharmacodynamic biomarkers show whether a drug is affecting its intended biological pathway. Examples include HER2 testing in breast cancer, PD-L1 expression in immunotherapy, genomic classifiers used in prostate cancer and circulating tumour DNA used to monitor treatment response.
Biomarker discovery is also becoming more data-driven. Researchers are combining genomic, transcriptomic, proteomic and metabolomic information to identify disease patterns that may not be visible through traditional methods. Machine learning and artificial intelligence can analyse these complex datasets and help identify patient subgroups, treatment signals and disease characteristics.
The quality of the underlying samples remains a critical factor. Variability in the collection and handling of blood, tissue or saliva can weaken biological signals and reduce the reliability of biomarker findings. Strong sample controls therefore remain an important part of reducing development risk.
Rare diseases are one of the clearest areas where precision medicine and biomarker-led development can converge.
The rare disease treatment market has been projected to reach approximately $587 billion by 2034, while orphan drugs are expected to account for around 20% of global prescription drug sales. Although each rare disease affects a relatively small patient population, more than 7,000 rare diseases have been identified collectively.
Rare disease programmes now represent a meaningful share of pharmaceutical research activity. Investigational therapies for rare diseases have been estimated to account for around 29% of global pharmaceutical pipelines by 2026. Large pharmaceutical companies have also increased their exposure through acquisitions, partnerships and internal development.
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