In Your Order
Pharmacogene Polymorphism Report*


Placing an order constitutes your agreement to our privacy policy & terms of service linked below.

Our system accepts raw DNA data files from 23andme & ancestry DNA.

Download your raw DNA data to your computer. File format is usually  (file.txt) . Click File in Notepad or any other text editor and click Save As. In the File name box, type the name of your file followed
by . CSV For example, if you wanted to save a Raw as a CSV, you may type Raw.csv

Order Details

- Analysis of genetic variations in genes encoding proteins involved in drug metabolism

- CYP2C19 gene

- CYP2D6  gene

- CYP2C9  gene

- CYP3A5  gene

- IFNL3  gene**     

- Your report includes Allelic genes, metabolic activity, cytogenic location & core alleles frequencies in   various population groups.

- You'll be able to view your report within 72 hours, most reports are ready under 24 hours.

** Core alleles frequencies in various population groups. is not available for the IFNL3 gene report

The information in this Report is for informational and educational purposes only. It is not intended for direct diagnostic use or medical decision-making. Individuals should not change their health behavior solely on the basis of information contained on this website. If you have questions about the information contained on this website, please see a health care professional.

*This product provides only a preliminary analytical result. An independent, clinically validated test must be used in connection with the medical trait in question.Limitations: This product analyzes certain genetic variants associated with  how quickly a medication is metabolized in the body. This product does not query all possible alleles associated with drug metabolism. Results may change as research advances and permit us to better understand what these genetic variations mean for health. Numerous factors can affect response to a medicine, including gender, age, and diet. Not a diagnostic product. Contains data from dbSNP, ClinVar, 1000 genomes project, COSMIC, dbGaP, dbVAR, EGA and many other sources.

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