What we do
We are a contract research organization using alternative model systems for highly efficient generation of preclinical data. We specialize in using transcriptomic analysis and omics technologies to understand the molecular mechanisms behind the action of driving the health benefits of compounds. This creates science-based evidence to bring high confidence for obtaining efficacy finding in a product.
One of our core capacities is the use of transcriptomics for gene expression analysis, which we map to cellular signaling pathways to uncover the various way a compound or formulation works. At the core of the technology is RNA-seq analysis that can detect which genes are being activated by treatment with a compound. To understand how RNA analysis is a way to detect gene activation, we take advantage of a basic biology principle - the Central Dogma of how DNA information gets turned into protein.
In the Central Dogma, The DNA is first transcribed into a messenger RNA (mRNA). Next, the mRNA is translated into protein which then participates in the cellular signaling pathways of the cell. Activation of various signaling pathways by test-sample treatment yields a molecular mechanism of action (mMoA) understanding of types of applications for which the nutraceutical will be efficacious. As a result, measuring the levels of mRNA with transcriptomics can provide insight into which genes are turned on or off by a exposure to a nutraceutical treatment.
Transcriptiomics using RNA-seq measures the response of each gene when exposed to a nutraceutical compound. A series of genes are tested for mRNA expression changes with (-) and without (+) compound. When 100 genes are examined only a small percentage will be affected. Yet, with the 20,000 genes of human genome, very large datasets (~20 Gb) of gene expression effects are recorded. This mountain of data can be challenging to interpret but by doing a rank order to see which clusters of genes are turned up and which genes are turned down. This results in a Differential Gene Expression (DGE) dataset that can then be mapped to cellular signaling pathways and identify the molecular mechanism of action for a treatment or compound.
Accurate structure function claims are important for nutraceutical credibility. We use identification of molecular Mechanism of Action (mMoA) via gene expression analysis and, in a proprietary process, we quantifiably aggregate the data into identify various health concerns impacted with nutraceutical treatment.
First, the molecular mechanism from gene expression is identified as groups of genes for core cellular processes that are activated with test sample treatment. In the example above, a nutraceutical is showing activity in cellular processes involved in mitochondrial health.
Second, with the identification of activity in sets of gene involved in core cellular processes, we have been developing various algorithms to extrapolate the effects into various health categories. In the example above, the test samples activity in mitochondrial health correlated to a higher activity in the healthy aging pathway. Also observed is a suppression of inflammation pathway which can be used to file novel structure function claims for healthy tissue support.
When cellular process is activated with nutraceutical treatment, the genetic analysis can be extended with a phenotypic validation experiment. Observing an effect with a phenotypic assay would bring even greater support of a novel structure function claim.
In an example of nutraceutical showing gene expression activity in mitochondrial health, a phenotypic experiment can be done to look at a the ability of a compound or formulation to prevent sarcopenia - a muscle wasting condition that affects all of us as we age. A major driver of sarcopenia is the health of our mitochondria in the muscle tissue. shown in the picture above is the mitochondria (stained green) in young vs old muscle tissue. Quantified, a treatment leading to retention of healthy muscle will avoid the fragmentation and aggregation of mitochondria that is seen in old muscle tissue.