Translational Medicine

Pharmacogenomics is Improving Drug Development Outcome - May, 2013

Pharmacogenomics (PGx) is becoming a fundamental part of drug development programs as organizations continue to benefit from improved prediction of efficacy and safety. The ultimate goal of pharmacogenomics is the delivery of “personalized medicine.” The promise of personalized medicine is to understand the patient’s unique genetic traits so that the right dose of the right medication is delivered at the right time.

Pharmacogenetics examines the inherited variations in genes (known as genetic polymorphisms) that dictate pharmacological and toxicological reactions in individuals upon exposure to drugs. Identified genetic variations can be used to predict how a patient will respond to a specific therapeutic. Pharmacogenetic data can help treatment decision making, improve clinical trial outcomes, and produce significant time and resource savings.

Improved study outcome through targeted responders

The cost, risk and duration of clinical trials can be significantly reduced by identifying non-responder patient groups or patient populations at risk for adverse events.  Pharmacogenomics aids clinical studies by targeting only those persons capable of responding to a drug, with a desirable therapeutic profile.

Polymorphisms in genes coding for drug metabolizing enzymes have major effects on drug activity and thus the efficacy of the therapeutic. The cytochrome P450 enzymes such as CYP2D6, CYP2C9, CYP2C19 and CYP3A4 are the best studied polymorphic enzymes associated with alterations in the action of a significant proportion of currently administered drugs. Patient CYP450 enzyme variability may result in potentially unfavorable phenotypes such as poor metabolizer or ultra-rapid metabolizer.  Poor metabolizers may suffer adverse events due to reduced metabolism at usual doses while ultra-rapid metabolizers may not reach therapeutic concentrations at recommended doses. For administered pro-drugs, ultra-rapid metabolizers may suffer adverse effects while poor metabolizers may not respond. The identification of such patients earlier in clinical trials will increase the chances a drug will make it into the marketplace.

QPS has supported multiple phase I studies by identifying poor metabolizers and ultra-rapid metabolizers such that they may be excluded from clinical studies. In these types of programs, QPS and the sponsor identify a panel of polymorphisms that are believed to impact the metabolism of the therapeutic being tested. Patients are genotyped for these polymorphisms and then categorized as ultra-rapid metabolizers, extensive metabolizers (normal), intermediate metabolizers or poor metabolizers. Based on this categorization, subsets of patients are identified as being undesirable for enrollment and thus are excluded from the study.

Pharmacogenomics can also greatly reduce the frequency of adverse drug reactions in drug development programs. Adverse drug reactions are a significant cause of morbidity and mortality. Understanding an individual’s genetic profile can result in the decrease of adverse drug reactions during drug development. This improved safety can then be propagated into the clinic.

Recently, QPS has developed and validated genotyping assays to analyze two separate mutations in mitochondrial DNA that are associated with permanent hearing loss in patients treated with aminoglycoside antibiotics. In an upcoming program being supported by QPS, patients will be screened for these mutations prior to enrollment in the study. Patients determined to be positive for either mutation will be excluded from the study so as to not be put at risk for hearing loss.

Genotype-specific protocols

Lack of efficacy or adverse events are major contributors to the overall failure rate of drugs in development. By utilizing pharmacogenomics, subpopulations of patients with different drug responses and underlying genetic markers can be stratified in clinical trials, based on their genotypes.

From 2008 to 2012, QPS supported a Phase III Alzheimer’s drug clinical trial associated with approximately 4,500 patients at over 150 clinical sites world wide. The program achieved global 72-hour turnaround of results in order to support patient stratification for clinical enrollment. Genotyping analysis of Apolipoprotein E (ApoE) was performed on clinical samples. Specifically, genomic DNA isolated from EDTA-whole blood samples was screened for 2 single-base variations located in exon 4 at codon positions 112 and 158 (112T>C and 158C>T) in order to determine ApoE e4 carrier status. ApoE e4 carriers have a higher risk of vasogenic edema than non-carriers at dosages proposed for the trial. After genotyping, each patient was enrolled in a specific protocol with appropriate dosing.

QPS TLM Support for Pharmacogenomics

QPS provides a reliable, flexible and rapid genotyping service for research and regulatory-compliant DNA variation analysis. We utilize proven, reliable, high-throughput genotyping platforms from Applied Biosystems and Qiagen. QPS’ scientists can also design and develop custom assays for less common or unique pharmacogenetic analyses.

Below are the PGx services offered at the Translational Medicine (TLM) Department at QPS Delaware:

Nucleic acid isolation
  • Wide variety of matrices (blood, tissue, FFPE, etc.) accepted for DNA or RNA isolation
  • Automated Qiagen BioRobot MDx platform available (PAXgene with FDA 510(K) clearance)
Expression Analysis
  • TaqMan platform (ABI 7900HT) and Quantigene (Panomics and Luminex platform)
  • TaqMan low density arrays available
  • Pyrosequencing (Qiagen), TaqMan (Life Technologies) and xTAG (Luminex) platforms available
  • Large list of validated assays
    • CYP2B6 (*5A, *9 , *18)
    • CYP2C9 (*2, *3, *4, *5, *8, *11, *13)
    • CYP2C19 (*2, *3, *4, *5, *6, *8)
    • CYP2D6 (*3, *3b, *4, *5/*2xN, *6, *7, *8, *9, *10, *11, *14, *15, *17, *19, *20, *29, *35, *38, *40, *41, *44, 1846G>A, 1023C>T, 2850C>T, 4180G>C)
    • CYP3A4 (*1B, *2, *3)
    • CYP3A5 (*3C, *6)
    • UGT1A1 (*1, *6, *7, *27, *28, *36, *37, *60, *62)
    • NAT1 (*10, *14B)
    • NAT2 (*5A, *6A, *7A, *14A)
    • VKORC1 (-1639G>A)
    • Cytidine Deaminase (CDA) (79A>C, 208G>A, 435C>T)
    • Alzheimer’s Disease associated (ApoE: 112T>C, 158C>T)
    • Oncology associated (BRAF, KRAS, PIK3CA)
    • Clinically relevant transporters (SLCO1B1)
    • Mitochondrial DNA polymorphisms (MT-TS1, MT-RNR1)
    • Custom assay development available
For detailed discussion, please contact:

 Charles Saginario, Ph.D.
(302) 453-5949,

LingSing Chen, Ph.D.
(302) 453-5904,

20 years in pharma R&D navigation