Collecting sparse sampling during the larger phase III clinical trials can help identify both the intrinsic and extrinsic factors that might affect exposure to a drug. Thus using such a screening approach might be valuable in detecting unsuspected drug-drug interactions especially in patients exhibiting a higher incidence of side effects. Both the U.S. FDA guidance and the Canadian guidance state that a well-executed population analysis can provide further evidence of the absence of a drug interaction when in vitro data suggest the lack of one. However, on the other hand both guidances agree that the sparse sampling approach to detect a drug interaction is not yet well established and that it is unlikely that one will be able to rule out an interaction that is strongly suggested by information that is obtained from in vitro or in vivo studies specifically designed to detect an interaction. This is due to the presence of confounding variables that are not controlled in the study that reduce the power to detect an interaction. The major advantage of such an approach is that the study is conducted in the target patient population and thus clinical inferences on the magnitude of the interaction as well as dosing recommendations are easier made from the results obtained. Another advantage of such an approach is that it does not expose healthy volunteers to unnecessary side effects of the drug. However, these studies are considered to be much more difficult to perform and believed by some to be more costly [100, 101].
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