Drug Development Support

Utilizing cutting-edge omics data analysis, find drug targets, mechanisms, and biomarkers.

Throughout the drug development process, molecular measurements based next-generation sequencing, single cells profiling and spatial transcriptomics and proteomics are used to help in target discovery and validation, preclinical development and biomarker search.

We have collaborated with clients on the development of biologics, gene, cell, and immunologic therapies as well as small molecules. Learn more about the phases of drug development that benefit from high-throughput molecular measurements combined with cutting-edge bioinformatics!

NGS assays and analysis supports drug development at all stages

Starting phase and basic research

Rational drug discovery requires fundamental studies of the molecular and cellular biology of a disease. This category includes a sizable portion of the work that our clients contract out to us. See more information about our background in basic science by research areas and data modalities.

Target discovery

Finding a protein or other biomolecule to use as a treatment target is the first step in the development of a target-based drug. The abundance of public, semi-public, and private data makes data-driven target discovery possible.

  • locating genetic variations that cause a hereditary disease in families or in genome-wide association studies.
  • finding genes linked to disease progression events using information from, for instance, tumor RNA-sequencing or proteomic data.
  • using patient samples or disease-related animal models to find genes that are up- or down-regulated specifically in certain diseases
  • determining which signaling pathways are active or inactive during a disease.

Target validation

Gene knockout models can be used in vitro or in vivo to examine and validate a candidate target in more detail. Such models' gene expression analysis may reveal both desired and undesirable downstream effects of a gene knock-out.

Preclinical development

The mechanism-of-action and off-target analyses can be carried out after a candidate drug has been identified against the target, once more using in vitro or in vivo models. The high-throughput measurements for proteomics, epigenomics, and transcriptomics (RNA-seq, ChIP-seq, ATAC-seq, etc.) are particularly applicable.

Biomarker discovery

Biomarkers, such as proteins, metabolites, or genetic variants, can help stratify patients according to how likely it is that they will respond favorably to a given treatment.

Prior to a clinical trial, potential biomarkers could be found (from, say, biobank data) to help identify high-risk patients.

On the other hand, molecular measurements during and following a clinical trial can be used to find biomarkers for treatment response or side effects (including pharmacogenetic markers).