Biomarkers in drug development
A biomarker is a characteristic measured as an indicator of a biological process, a disease process or a response to an intervention. In developing and using a medicine, biomarkers serve purposes from selecting patients to minimising toxicity. A validated biomarker can be used for regulatory approval, and clinical biomarkers can be identified by combining patients' omics data with their clinical data.
What a biomarker is
A biomarker is a defined characteristic that is measured as an indicator of normal biological processes, pathological processes, or responses to an exposure or intervention. Biomarkers take many forms, including molecular, histologic, radiographic and physiologic ones.
As of 2021, much recent research had been devoted to genomic biomarkers. ICH E15 defines them as biomarkers that can measure the expression, function or regulation of a gene and serve as indicators of normal biological processes, pathogenic processes or responses to therapeutics or other interventions. Genomic biomarkers include pharmacogenomic biomarkers, which are variations of DNA or RNA characteristics related to drug response. Drug response includes drug absorption and disposition (pharmacokinetics) and drug effects (pharmacodynamics, efficacy and adverse effects), so pharmacogenomic biomarkers are becoming increasingly important for drug discovery, drug development and clinical practice.
What biomarkers are used for
Biomarkers play diverse roles in drug development. The ICH E16 guidance on biomarkers describes several purposes:
- Selecting an eligible patient population for an indication or for participation in a clinical study. Such biomarkers can be used to identify individuals with a subtype of the disease of interest. HER2 is such a biomarker: therapies such as trastuzumab are indicated for individuals who have HER2-positive breast cancer. This type of biomarker is of particular interest for precision medicine because it can predict response to therapy.
- Assessing disease state or prognosis. The cardiac biomarkers troponin I and N-terminal prohormone brain natriuretic peptide (NT-proBNP), indicators of cardiac injury and cardiac dysfunction respectively, are in this category.
- Assessing the mechanism of action, including the mechanism of pharmacological mode of action, therapeutic effect or toxicity.
- Optimising the dose.
- Monitoring drug response, both drug safety and drug efficacy.
- Maximising efficacy.
- Minimising toxicity.
Biomarkers can therefore be used in a variety of contexts: predicting an individual's risk of developing a disease, diagnosing a disease state, identifying a disease subtype, predicting a response to a therapy, detecting the effect of a therapy on an individual, monitoring the status of the disease, and monitoring safety. Biomarkers can also be used to predict clinical outcomes and to accelerate drug development. Hopes for personalised medicine rely on biomarkers that are sensitive (correctly detecting true positives) and specific (correctly detecting true negatives), so that therapies can be tailored to individuals. As of 2021, the range of biomarkers was continuously evolving.
Qualifying a biomarker for regulatory approval
Clinical outcome assessments have traditionally supported the regulatory approval of therapies, but a validated biomarker can also be used for regulatory approval. ICH E16 lays out general principles for qualifying biomarkers for submissions, that is, for demonstrating that a biomarker reliably reflects a biological process, response or event. The submission for biomarker qualification is organised along the same lines as the Common Technical Document, with sections for regional administrative information, summaries, quality reports, nonclinical reports and clinical reports.
Clinical biomarkers from omics and clinical data
Patients' clinical data, from real-world data and clinical trials, can be combined with omics data from patients, such as genomic, transcriptomic, proteomic and metabolomic data, to identify clinical biomarker signatures. These signatures are analysed with systems biology, which uses a collection of quantitative experimental and computational methods to reveal the information flow between the genes, proteins and metabolites essential in the functional pathways that exist among cells, tissues, organs and organism-level phenotypes. The clinical biomarkers then inform the construction of predictive models of disease course and of patients' response to therapy, which helps to form and update the biological model.