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i am doing a project on determination of Ki (inhibition constant) on CYP2C9 isozyme of Cytochrome P450 in vivo (using mice and rat) using Diclofenac as probe substrate. In literature i found that CYP2C9 is not present in rat and mice.
can i do this CYP2C9 inhibition in vivo study in rat and mice.
please help me in this regard.
with regards,
ramana
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Dear All:
I am doing project on CYP2C9 drug interaction. I have determined Ki vaules of some inhouse compounds by in vitro methods . From ki values it is clear that these compounds are inhibitors of CYP2C9. Now I want to do a in vivo CYP2C9 drug interaction study in rat or mouse. But in literature I" found that CYP2C9 is absent in rat and mouse.
My question to group is "Can I do a CYP2C9 drug interaction study in rat or mouse?" If yes which substrate I should use for in vivo study?
Can you give some references?
Thank you in advance...
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The following message was posted to: PharmPK
Dear Ramana,
What you found is consistent with my own small knowledge: CYP2C9 is a human enzyme and the CYP2C counterparts in rodents are very different in terms of functionality (substrate spectrum).
If you have been able to measure Ki in-vitro in human liver microsomes, then I believe the next step to assess the extent of DDI in humans is to run an in-vivo experiment ...in humans (i.e., a clinical study). You might not have to run any additional animal experiment at this point.
You could check the FDA guidance on DDI, or Bjornsson et al, Drug Metab Dispos 2003, 815.
Best regards
Frederic Massiere
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Hi Ramana
I wonder what would be the use of a drug-drug interaction study in rat or mouse which won't give you any indication of the possible outcome of such study in human? If in addition to the Ki value you have the metabolism data for your compound then using a mechanistic approach you can do some simulations to predict the level of interaction and optimally design your in vivo study, please see the following paper.
Zhang L, Reynolds KS, Zhao P and Huang S-M (2010) Drug interactions evaluation: An integrated part of risk assessment of therapeutics. Toxicology and Applied Pharmacology 243:134-145.
Regards
Masoud
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The following message was posted to: PharmPK
Dear Ramana
Quoting Frederic Massiere:
> If you have been able to measure Ki in-vitro in human liver
microsomes,
> then I believe the next step to assess the extent of DDI in humans is
> to run an in-vivo experiment ...in humans (i.e., a clinical study).
We (Simcyp and others) would say the next step is to run a simulation
using your in vitro data prior to a clinical study - population-based
IVIVE.
This may help you understand the behaviour of your drug, help with your
study design and indeed aid interpretation of a clinical study once it
is done.
There is a growing literature, including from certain regulatory
agencies,
supporting this approach; e.g.,
Zhang et al (2010) Drug interactions evaluation: an integrated part of
risk assessment of therapeutics. Toxicology and Applied Pharmacology
243(2):134-145.
Zhao P, Zhang L, Lesko L, Huang S-M (2009) Evaluating complex DDI using
modelling and simulations: application and challenge in regulatory
review. Sep 17th, Land O'Lakes Conference on Drug Metabolism/Applied
Pharmacokinetics. Merrimac, WI, USA.
Other references mainly from industry:
Allan et al (2008) Pre-clinical pharmacokinetics of UK-453,061, a novel
non-nucleoside reverse transcriptase inhibitor (NNRTI), and use of in
silico physiologically-based prediction tools to predict the oral
pharmacokinetics of UK-453,061 in man. Xenobiotica 38(6):620 - 640.
Dong et al (2008) Applications of Computer-Aided Pharmacokinetic and
Pharmacodynamic Methods from Drug Discovery through Registration.
Current Computer-Aided Drug Design 4(1):54-66.
Hyland et al (2008) Maraviroc: In vitro assessment of Drug-Drug
Interaction Potential. British Journal of Clinical Pharmacology
66(4):498-507.
Johnson et al (2009) Assessing the efficiency of mixed effects modelling
in quantifying metabolism based drug-drug interactions: using in vitro
data as an aid to assess study power. Pharmaceutical Statistics
8(3):186-202.
Rakhit et al (2008) The effects of CYP3A4 inhibition on erlotinib
pharmacokinetics: computer-based simulation (SimCYP) predicts in vivo
metabolic inhibition. European Journal of Clinical Pharmacology
64(1):31-41.
Youdim et al (2008) Application of CYP3A4 in vitro data to predict
clinical drug-drug interactions; predictions of compounds as objects of
interaction. British Journal of Clinical Pharmacology 65(5):680-92.
Expression levels (mainly liver and gut abundance) of enzymes such as
CYP2C9 are incorporated into databases linked to population-based IVIVE
software including the proportions of healthy humans known to be CYP2C9
poor metabolisers (there is also
for 2C9 a range of alleles). Information such as this can be used to
inform study design, dosing etc. Again for CYP2C9 (and of course other
enzymes) there are known changes in expression linked to disease status.
See also:
Jamei et al (2009) A framework for assessing inter-individual
variability in pharmacokinetics using virtual human populations and
integrating general knowledge of physical chemistry, biology, anatomy,
physiology and genetics: A tale of 'bottom-up' vs 'top-down' recognition
of covariates. Drug Metabolism and Pharmacokinetics 24(1):53-75.
Jamei et al (2009) The Simcyp((R)) Population-based ADME Simulator.
Expert Opinion in Drug Metabolism and Toxicology 5(2):211-223.
Jamei et al (2009) Population-Based Mechanistic Prediction of Oral Drug
Absorption. AAPS Journal 11(2):225-237.
Regards
David
David Turner, PhD
Principal Scientist
Simcyp Limited
Blades Enterprise Centre, John Street, Sheffield, S2 4SU, UK
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