BIOMARKER ANALYSIS

Biomarkers play a crucial role in the era of precision medicine.  Applications of biomarkers are being increasingly utilized in basic biomedical research and medical product development. Measurement of physiologic processes from biochemical, cellular, or molecular alterations are utilized to better understand disease etiology, prodrome, or drug response.

BSSI has been offering biomarker consulting and analytical services to the pharmaceutical and biotechnology industry for more than fifteen years. From the beginning, BSSI has been a pioneer in the field of translational sciences, specializing in biomarker analytics. BSSI serves clients from industry, academic and research institutions, and government agencies, and has become a preferred service provider of biomarker statistics for several major pharmaceutical companies.

Experienced translational team:

  • Biostatisticians
  • Bioinformaticists
  • Epidemiologists
  • Geneticists

Support from discovery through clinical development and application:

  • Identification and validation of disease state biomarkers
  • Measurement of pharmacokinetic (PK) markers to determine dosing
  • Linking pharmacodynamic (PD) biomarkers to the mechanism of action (MOA) of a therapeutic intervention
  • Analysis of relationship between predictive or prognostic biomarkers and drug effectiveness and safety
  • Utilization of biomarkers to identify and stratify patients with improved efficacy and safety profiles
  • Assist the development and validation of diagnostic tools (e.g. companion diagnostics)

Experienced in analyzing different types of biomarker data:

  • Next generation sequencing (NGS) for DNA and RNA: whole genome or exome sequencing, RNA sequencing
  • Microarrays for DNA and RNA: whole genome genotyping, candidate genes, methylation arrays, and gene expression arrays
  • Immunoassays: enzyme-linked immunosorbent assay (ELISA) for proteins, and microsphere-based immuno-multiplexing for cytokines and chemokines, and others
  • Imaging data
  • Data from other techniques such as immunohistochemistry (IHC), mass spectrometry, and flow cytometry

Complex data structure requires specialized approaches:

  • Analytical expertise for genetic and expression studies including variant, gene protein, and pathway level analyses
  • Computing capabilities to handle large amounts of data (such as proteomic and image data)
  • Predictive modeling
  • Resampling and machine learning approaches
  • Identification and stratification of patient subgroups
  • Systems biology approaches for pathway and network analyses
  • Effective illustration and exploration of biomarker data through static and interactive visualization