This article is available online at http://dmd.aspetjournals.org ABSTRACT:Current regulatory guidances do not address specific study designs for in vitro and in vivo drug-drug interaction studies. There is a common desire by regulatory authorities and by industry sponsors to harmonize approaches, to allow for a better assessment of the significance of findings across different studies and drugs. There is also a growing consensus for the standardization of cytochrome P450 (P450) probe substrates, inhibitors and inducers and for the development of classification systems to improve the communication of risk to health care providers and to patients. While existing guidances cover mainly P450-mediated drug interactions, the importance of other mechanisms, such as transporters, has been recognized more recently, and should also be addressed. This article was prepared by the Pharmaceutical Research and Manufacturers of America (PhRMA) Drug Metabolism and Clinical Pharmacology Technical Working Groups and represents the current industry position. The intent is to define a minimal best practice for in vitro and in vivo pharmacokinetic drug-drug interaction studies targeted to development (not discovery support) and to define a data package that can be expected by regulatory agencies in compound registration dossiers.Drug-drug interactions can lead to severe side effects and have resulted in early termination of development, refusal of approval, severe prescribing restrictions, and withdrawal of drugs from the market. Regulators, including the U.S. Food and Drug Administration (FDA 1 ) have therefore issued guidances for in vitro and in vivo drug interaction studies to be conducted during development. These guidances, however, do not address the specific designs of the studies, and there is a desire by regulatory authorities to harmonize approaches and study designs to allow for a better assessment and comparison of different drugs. In addition, the existing guidances cover mainly cytochrome P450 (P450)-mediated drug interactions and the importance of other mechanisms, such as transporters, has been recognized only recently. To address these issues, workshops have been held in

Current regulatory guidances do not address specific study designs for in vitro and in vivo drug-drug interaction studies. There is a common desire by regulatory authorities and by industry sponsors to harmonize approaches to allow for a better assessment of the significance of findings across different studies and drugs. There is also a growing consensus for the standardization of cytochrome P450 (CYP) probe substrates, inhibitors, and inducers and for the development of classification systems to improve the communication of risk to health care providers and patients. While existing guidances cover mainly CYP-mediated drug interactions, the importance of other mechanisms, such as transporters, has been recognized more recently and should also be addressed. This paper was prepared by the Pharmaceutical Research and Manufacturers of America (PhRMA) Drug Metabolism and Clinical Pharmacology Technical Working Groups and represents the current industry position. The intent is to define a minimal best practice for in vitro and in vivo pharmacokinetic drug-drug interaction studies targeted to development (not discovery support) and to define a data package that can be expected by regulatory agencies in compound registration dossiers.

Current regulatory guidances do not address specific study designs for in vitro and in vivo drug-drug interaction studies. There is a common desire by regulatory authorities and by industry sponsors to harmonize approaches to allow for a better assessment of the significance of findings across different studies and drugs. There is also a growing consensus for the standardization of cytochrome P450 (CYP) probe substrates, inhibitors, and inducers and for the development of classification systems to improve the communication of risk to health care providers and patients. While existing guidances cover mainly CYP-mediated drug interactions, the importance of other mechanisms, such as transporters, has been recognized more recently and should also be addressed. This paper was prepared by the Pharmaceutical Research and Manufacturers of America (PhRMA) Drug Metabolism and Clinical Pharmacology Technical Working Groups and represents the current industry position. The intent is to define a minimal best practice for in vitro and in vivo pharmacokinetic drug-drug interaction studies targeted to development (not discovery support) and to define a data package that can be expected by regulatory agencies in compound registration dossiers.

Various approaches are compared for the design and analysis of studies to assess the transfer of an analytical method from a research and development site to one or more other sites: comparison of observed bias and precision to acceptance limits, statistical quality control-type analysis, statistical difference tests, and statistical equivalence tests. These approaches are evaluated in terms of the extent to which the risks of incorrect decisions (consumer risk of failing to detect that a site is unacceptable, and producer risk of rejecting an acceptable site) are known and/or controlled. Comparison of observed accuracy and precision to acceptance limits is a flawed approach because both the consumer and producer risks are unknown and uncontrolled. For technology transfec where the objective is to demonstrate sufSicient acceptability or similarity, the statistical quality control and difference tests are well known to suffer from illogical characteristics (decreasing true acceptance probabilities as the sample size increases). The equivalence test is the preferred approach because it alone controls the more important consumer risk and performs in a scientifically logical manne,: Acceptance limits for accuracy and precision in the equivalence test should be based on need for intended use (ie, ensuring thar good batches will pass, and bad batches will fail, during future release testing and stability testing), and a rigorous method for selection of well-conceived limits is presented. Methods for sample size determination are also included. The proposed approach is illustrated with two examples.

We challenge the "one size fits all" current definition of bioequivalence acceptance limits for highly variable drugs, proposing alternative limits or "goal posts" which vary in accordance with the intrasubject variability of the reference product.