Biomarker

Biomarker - Axcellant

Biomarker

  1. Feb 28, 2025

What Does ‘Biomarker’ Mean?

A biomarker is a measurable indicator of a biological state or condition. It can be a molecule, gene, characteristic, or substance that can be objectively measured and evaluated as a sign of normal biological processes, pathogenic processes, or pharmacological responses to a therapeutic intervention.

Biomarkers are widely used in clinical research and medical practice to assess health states, disease risk, or treatment effectiveness. They can be found in various biological samples such as blood, urine, or tissue, and may include genetic markers, proteins, hormones, or specific cellular changes.

Why Is the ‘Biomarker’ Important in Clinical Research?

Biomarkers play a crucial role in clinical research by providing objective, quantifiable data about biological processes and drug responses. They enable researchers to assess the safety and efficacy of new treatments more accurately and efficiently, potentially reducing the time and cost of drug development.

Furthermore, biomarkers can help identify suitable patients for clinical trials, improving study design and increasing the likelihood of successful outcomes. They also contribute to the development of personalized medicine by allowing healthcare providers to tailor treatments based on individual patient characteristics and responses.

Good Practices and Procedures

  1. Validate biomarker assays for reproducibility and accuracy across different laboratories before implementation in clinical trials
  2. Establish clear criteria for biomarker positivity or threshold values, accounting for biological variability and analytical precision
  3. Incorporate biomarker collection and analysis plans into clinical trial protocols, specifying timing, sample handling, and storage procedures
  4. Conduct regular quality control checks on biomarker data to identify potential outliers or systematic errors
  5. Develop standardized reporting formats for biomarker results to facilitate data interpretation and cross-study comparisons

Related Terms

Resources

Large Language Models in Nuclear Cardiology: From Experimental Tools to Clinical Infrastructure

3 Questions with: Prof. Piotr Słomka Large language models are entering nuclear cardiology at a pace that makes the usual…

From Half-Life to Clinical Impact: Mastering Time-Critical Supply Chains

How Axcellant helped a diagnostic study overcome isotope supply, manufacturing, and logistics constraints In radiopharmaceutical development, we often say that…

How ACT EU Is Forcing a Global Approach to Trial Timelines

Europe’s clinical trials market is entering a more practical phase in its approach to competitiveness. With the Clinical Trials Regulation…