Exploratory Biomarker data analysis


Biomarkers are the traceable biological characteristics of an individual. They range from genetic blueprints to immune cell populations and proteins in the blood. While biological processes cannot always be observed directly, biomarkers can be used to indirectly measure these processes.

Biomarkers can be divided into three main types:

  1. Prognostic, providing information on the likely course of a disease;
  2. Predictive, used to identify subgroups of patients most likely to respond to a given treatment;
  3. Pharmacodynamic, measuring the biological activity of the drug itself

At Quartz Bio, we have accumulated a significant expertise analyzing data from phase I to phase IV projects and using various biomarkers such as: genomic biomarkers, transcriptomic biomarkers, proteomic as well as metabolomics markers.

Patient Stratification Analyses

A stratification analysis aims at identifying sub-populations of patients where the likelihood of observing a given phenotype (e.g. disease evolution, response to treatment etc) is increased. The patients sub-populations are defined using on one or more biomarkers.

Both predictive and prognostic markers contribute to increase knowledge on the drug and the underlying disease mechanisms, bringing value to clinical development projects. Ultimately stratification analyses aim at identifying the most adapted drugs to a group of patients.

However, with the increasing biological complexity & number of biomarkers assessed, patient stratification could be very challenging and needs a very thorough study design and statistical analysis plan for an efficient outcome.

Ancestry-independent genetic information in the reclassification of Systemic Autoimmune Diseases

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