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I am wondering how to investigate clinical relevance DDI for a lead
compound showing strong CYP inhibition in human liver microsomes.
Also, if the this compound did not show inhibition of the metabolism
of the relevant drug in vitro in human hepatocytes (due to
permeability or transporter) pave the way to exlude DDI in vivo?
Please provide you input and relevant references
Thank you
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The following message was posted to: PharmPK
Ksar:
I think the contradictory results may result in close scrutiny by
regulators (if there is any question regarding the methodology I
suggest you repeat these experiments). It is likely that the
regulators will require a clinical study with probe substrates of the
CYP or CYPs inhibited by your lead compound. Depending on the
therapeutic use of your product, they may also require clinical
studies with critical drugs that are likely to be co-prescribed (for
example: narrow therapeutic range drugs). This website may be of help:
http://www.fda.gov/cder/drug/drugInteractions/default.htm
Sincerely,
Carol Collins
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The following message was posted to: PharmPK
Dear Ksar
As Carol mentioned because of high level of interaction in microsomes
and
low level in hepatocytes you need to do more investigations to
identify the
reasons behind such differences and you should expect regulators
asking for
clinical studies. You mentioned permeability or transport as possible
causes
of such difference which means even more complexity as if, for whatever
reasons, the activity of involved transporters get inhibited then you
may
see the same level of interaction observed in microsomes.
In order to project the relevance of DDI in vivo there are many
methods from
very simplistic [I]/Ki, to considering fms or using fully
physiologically-based models, please see some of the references below,
in
particular Obach 2009 review and the references therein. In any such
attempts the PK characteristics of all moieties involved (substrate,
inhibitor(s) and perhaps their metabolites) should be considered and
recently some regulators encourage the use of modelling and simulation
for
determining the best dosing strategy of DDI studies (Huang and Lesko
2009).
Regards
Masoud
Brown HS, Ito K, Galetin A and Houston JB (2005) Prediction of in vivo
drug-drug interactions from in vitro data: impact of incorporating
parallel
pathways of drug elimination and inhibitor absorption rate constant.
Br J
Clin Pharmacol 60:508-518.
Huang S-M and Lesko LJ (2009) Authors' Response. J Clin Pharmacol
49:370.
Ito K, Iwatsubo T, Kanamitsu S, Nakajima Y and Sugiyama Y (1998)
Quantitative prediction of in vivo drug clearance and drug
interactions from
in vitro data on metabolism, together with binding and transport. Annu
Rev
Pharmacol Toxicol 38:461-499.
Obach RS (2009) Predicting drug-drug interactions from in vitro drug
metabolism data: challenges and recent advances. Curr Opin Drug Discov
Devel
12:81-89.
Rostami-Hodjegan A and Tucker GT (2004) 'In silico' simulations to
assess
the 'in vivo' consequences of 'in vitro' metabolic drug-drug
interactions.
Drug Discovery Today: Technologies 1:441-448.
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Thank you Carol,
So if I understand well, if a compound is a strong CYP2C9 inhibitor
and you show in intro that the compound did not significantly inhibit
warfarin metabolism in human hepatocytes, the FDA might still require
clinical CYP2C9 DDI study
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The following message was posted to: PharmPK
Yes. Please look at the studies carefully... If you are dealing with
the FDA, the approved in vitro substrates are tolbutamide methyl-
hydroxylation
S-warfarin 7-hydroxylation and diclofenac 4'-hydroxylation. They will
also accept (but may put less weight on flurbiprofen 4'-hydroxylation
or
phenytoin-4-hydroxylation. Make sure it was the (S) enantiomer of
warfarin not the racemic mixture that was used in hepatocytes.
The final issue is the expect clinical range of your substrate and the
concentration of the worst case scenario (for example in hepatic or
renal failure patients). According to the FDA's draft guidance:
http://www.fda.gov/cder/guidance/6695dft.pdf
Design Considerations for In Vitro CYP Inhibition Studies
(a) Typical experiments for determining IC50 values involve incubating
the substrate, if the metabolic rate is sufficient, at concentrations
below its Km to more closely relate the inhibitor IC50 to its Ki. For
Ki determinations, both the substrate and inhibitor concentrations
should be varied to cover ranges above and below the drug's Km and
inhibitor's Ki. (b) Microsomal protein concentrations used are usually
less than 1 mg/ml. (c) Because buffer strength, type, and pH can all
significantly affect Vmax and Km, standardized assay conditions are
recommended. (d) Preferably no more than 10-30% substrate or inhibitor
depletion should occur. However, with low Km substrates, it may be
difficult to avoid > 10% substrate depletion at low substrate
concentrations.(e) We suggest a linear relationship between time and
amount of product formed. (f) We recommend a linear relationship
between amount of enzyme and product formation. (g) Any solvents
should be used at low concentrations (< 1% (v/v) and preferably <
0.1%). Some of the solvents inhibit or induce enzymes. The experiment
can include a no solvent control and a solvent control. (h) Use of an
active control (known inhibitor) is optional.
Determining Whether an NME is a Reversible Inhibitor
Theoretically, significant enzyme inhibition occurs when the
concentration of the inhibitor present at the active site is
comparable to or in excess of the Ki. In theory, the degree of
interaction (R, expressed as fold-change in AUC) can be estimated by
the following equation: R = 1+ [I]/Ki, where [I] is the concentration
of inhibitor exposed to the active site of the enzyme and Ki is the
inhibition constant.
Although the [I]/Ki ratio is used to predict the likelihood of
inhibitory drug interactions, there are factors that affect selection
of the relevant [I] and Ki. Factors that affect [I] include
uncertainty regarding the concentration that best represents
concentration at the enzyme binding site (at the gastrointestinal
versus liver) and uncertainty regarding the impact of first pass
exposure. Factors that affect Ki include substrate specificity,
binding to components of incubation system, and substrate and
inhibitor depletion.
Current recommended approach
The likelihood of an in vivo interaction is projected based on the [I]/
Ki ratio where [I] represents the mean steady-state Cmax value for
total drug (bound plus unbound) following administration of the
highest proposed clinical dose. As the ratio increases, the likelihood
of an interaction increases. The following table suggests the
likelihood of in vivo interaction based on estimated [I]/Ki ratios. An
estimated [I]/Ki ratio of greater than 0.1 is considered positive and
a follow-up in vivo evaluation is recommended.
Table 4. Prediction of clinical relevance of competitive CYP inhibition
[I]/Ki Prediction
[I]/Ki > 1 Likely
1 > [I]/Ki > 0.1 Possible
0.1 > [I]/Ki Remote
Although quantitative predictions of in vivo drug-drug interactions
from in vitro studies are not possible, rank order across the
different CYP enzymes for the same drug may help prioritize in vivo
drug-drug interaction evaluations. When various [I]/Ki ratios are
obtained with the major CYP enzymes (CYP1A2, CYP2C8, CYP2C9, CYP2C19,
CYP2D6, and CYP3A), an in vivo study starting with the CYP with the
largest [I]/Ki (or smallest Ki) may be appropriate.
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