The AAPS Journal, Vol. 11, No. 2, June 2009 ( # 2009)
`DOI: 10.1208/s12248-009-9106-3
`
`Regulatory Note
`Theme: Towards Integrated ADME Prediction: Past, Present, and Future Directions
`Guest Editors: Lawrence X. Yu, Steven C. Sutton, and Michael B. Bolger
`
`Predicting Drug–Drug Interactions: An FDA Perspective
`
`Lei Zhang,1 Yuanchao (Derek) Zhang,1 Ping Zhao,1 and Shiew-Mei Huang1,2
`
`Received 15 January 2009; accepted 12 April 2009; published online 6 May 2009
`Abstract. Pharmacokinetic drug interactions can lead to serious adverse events, and the evaluation of a
`new molecular entity’s drug–drug interaction potential is an integral part of drug development and
`regulatory review prior to its market approval. Alteration of enzyme and/or transporter activities
`involved in the absorption, distribution, metabolism, or excretion of a new molecular entity by other
`concomitant drugs may lead to a change in exposure leading to altered response (safety or efficacy). Over
`the years, various in vitro methodologies have been developed to predict drug interaction potential in
`vivo. In vitro study has become a critical first step in the assessment of drug interactions. Well-executed in
`vitro studies can be used as a screening tool for the need for further in vivo assessment and can provide
`the basis for the design of subsequent in vivo drug interaction studies. Besides in vitro experiments, in
`silico modeling and simulation may also assist in the prediction of drug interactions. The recent FDA
`draft drug interaction guidance highlighted the in vitro models and criteria that may be used to guide
`further in vivo drug interaction studies and to construct informative labeling. This report summarizes
`critical elements in the in vitro evaluation of drug interaction potential during drug development and uses
`a case study to highlight the impact of in vitro information on drug labeling.
`KEY WORDS: drug development; drug–drug interaction; new drug application; prediction; regulatory
`and guidance.
`
`INTRODUCTION
`
`The desirable and undesirable effects of a drug are
`generally related to its concentration at the sites of action,
`which in turn is related to the amount administered (dose)
`and to the drug’s absorption, distribution, metabolism, and/or
`excretion (ADME). All these processes can be influenced by
`both intrinsic and extrinsic factors such as age, race, gender,
`disease states, concomitantly administered drugs, food, and
`juices (1). Observed changes arising from pharmacokinetic
`drug–drug interactions can be substantial such as an order of
`magnitude or more increase or decrease in the blood and
`tissue concentrations of a drug or its metabolites. Many of
`
`The opinions contained in this paper do not necessarily reflect the
`official views of the FDA.
`1 Office of Clinical Pharmacology, Office of Translational Sciences,
`Center for Drug Evaluation and Research, Food and Drug
`Administration, Rm 3188, Bldg 51, 10903 New Hampshire Avenue,
`Silver Spring, Maryland 20993, USA.
`2 To whom correspondence should be addressed. (e-mail: shiewmei.
`huang@fda.hhs.gov)
`ABBREVIATIONS: ADME, Absorption, distribution, metabolism
`or excretion; AhR, Aryl hydrocarbon receptor; BCRP, Breast cancer
`resistance protein; CAR, Constitutive androstane receptor; IND,
`Investigational new drug; NDA, New drug application; NME, New
`molecular entity; OAT, Organic anion transporter; OATP, Organic
`anion transporting polypeptide; OCT, Organic cation transporter; P-gp,
`P-glycoprotein; UGT, UDP-glucuronosyltransferase.
`
`these interactions involved inhibition of metabolizing
`enzymes and transporters, resulting in increased systemic
`exposure and subsequent adverse drug reactions. In other
`cases, induction of metabolizing enzymes and transporters
`resulted in reduced systemic exposure leading to a risk of loss
`of efficacy of co-administered drugs. Therefore, drug interac-
`tion potential is recognized as an important consideration in
`the evaluation of a new molecular entity (NME) (2,3) and is
`an integral part of drug development and regulatory review
`prior to NME’s market approval.
`Several FDA guidance documents developed since the
`mid-1990s and the most recent draft drug interaction guid-
`ance released in September 2006 reflect the Agency’s view
`that the metabolism of an NME and its potential on inhibition
`and induction of key metabolizing enzymes and transporters
`should be defined (4–6). Potential drug–drug interactions
`resulting from the effects of other drugs on NME and the
`effects of NME on other drugs should be explored during
`drug development to ensure an adequate assessment of an
`NME’s safety and effectiveness (6,7). An integrated approach
`(in vitro and in vivo) to the evaluation of an NME’s drug
`interaction potential may reduce the number of unnecessary
`studies and optimize knowledge. The recent FDA draft drug
`interaction guidance highlighted the in vitro models and
`criteria that may be used to guide further in vivo drug
`interaction studies (6). Besides in vitro experiments, in silico
`modeling and simulation may also assist in the prediction for
`drug interactions.
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`CURRENT STATUS AND RECOMMENDATION
`IN PREDICTING IN VIVO DRUG INTERACTIONS
`BASED ON IN VITRO EVALUATION
`
`Pharmacokinetic drug interactions can occur via inhibi-
`tion or induction of metabolic enzymes or transporters.
`Evaluation of an NME’s drug–drug interaction potential is
`an integrated part of drug development and regulatory review
`prior to its market approval. In general, three basic questions
`need to be addressed in the new drug application: (1) Will
`other drugs alter the exposure to an NME? (2) Will an NME
`alter the exposure to other drugs? (3) Are these alterations in
`exposure clinically relevant to warrant dose adjustment?
`While drug interactions can be evaluated via specific clinical
`studies in healthy subjects or patients, in vitro approaches are
`now becoming common as a critical first step in the
`assessment of drug interaction potential via specific pathways,
`and knowledge obtained from these studies may help reduce
`the number of unnecessary studies. The experiments are
`generally conducted during early phase of drug development
`process. Results from the in vitro studies can be used to
`predict in vivo interaction and guide the need for further in
`vivo study evaluation. The 2006 FDA draft drug interaction
`guidance has specific recommendation as to how to use in
`vitro models to address drug interaction potential and, for the
`first time, includes criteria for evaluating transporter-based
`drug interactions (6).
`
`Prediction of Metabolism-Mediated Drug Interaction
`
`The following cytochrome P450 (CYP) enzymes are
`recommended for routine assessment to identify potential
`P450-mediated drug interactions: CYP1A2, CYP2B6, CYP2C8,
`CYP2C9, CYP2C19, CYP2D6, and CYP3A. Evaluation of
`phase II enzymes is highly encouraged if applicable (6).
`
`Understanding Whether an NME is a Substrate
`for a Particular P450 Enzyme
`
`Understanding which P450 enzyme is responsible for the
`metabolism of an NME is important in the evaluation of drug
`interaction potential. Drug interaction is likely to occur
`between such a drug and known inhibitors or inducers of
`that specific pathway if it contributes >25% to the total
`clearance of the NME. It is also important for selecting the
`interacting drugs to evaluate drug interaction in vivo,
`determining the impact of polymorphic enzyme activity on
`drug disposition, and deciding whether a multiple inhibitor
`study may be warranted. In general, the likelihood of drug
`interactions increases when a compound has a high affinity
`for a single metabolizing enzyme compared with a compound
`with affinity for a number of different enzymes.
`A set of experiments (also known as reaction phenotyp-
`ing) is conducted to identify the specific enzymes responsible
`for the metabolism of an NME. Oxidative and hydrolytic
`reactions involve cytochrome P450 (CYP) and non-CYP
`enzymes. For many drugs, transferase reactions (involving
`phase II enzymes) are preceded by oxidation or hydrolysis of
`the drug. However, direct transferase reactions may represent
`a major metabolic pathway for compounds containing the
`requisite functional groups. The guidance recommends that
`
`the metabolic profile of the NME be investigated using
`human liver tissues such as freshly isolated liver slices, freshly
`prepared or cryopreserved human hepatocytes, subcellular
`liver tissue fractions such as liver S9 fraction, liver micro-
`somes, or recombinant complementary DNA (cDNA)-
`expressed microsomes for a particular CYP enzyme. If
`human in vivo data indicate that CYP enzymes contribute
`>25% of the total clearance of the NME, studies should be
`conducted using human liver microsomes or recombinant
`enzymes to determine the individual CYP enzymes responsi-
`ble for the drug’s metabolism. If an NME is a substrate of a
`particular CYP, an in vivo interaction with a strong inhibitor
`or inducer for that CYP is needed to determine whether
`inhibition or induction of this particular pathway may lead to
`a change in the NME’s pharmacokinetics. Negative results
`would alleviate further in vivo studies with less strong
`inhibitors or inducers. If results are positive, further clinical
`studies with less potent inhibitors or inducers would generally
`be needed to provide guidance on dosage adjustment.
`If an NME is metabolized by a polymorphic enzyme
`(such as CYP2D6, CYP2C9, or CYP2C19), the extent of drug
`interactions (inhibition or induction) may be different
`depending on the subjects’ genotype for the specific enzyme
`being evaluated. For example, subjects lacking the major,
`polymorphic clearance pathway will show reduced total
`metabolism. But alternative pathways may become quantita-
`tively more important and need to be understood and studied
`appropriately. In general, the comparison of pharmacokinetic
`parameters of this NME in poor metabolizers versus extensive
`metabolizers may indicate the extent of interaction of this drug
`with strong inhibitors of these enzymes and make interaction
`studies with such inhibitors unnecessary. When the above study
`shows significant interaction, further evaluation with weaker
`inhibitors may be necessary.
`
`Understanding Whether an NME is an Inhibitor
`for a Particular P450 Enzyme
`
`If an NME is an inhibitor of a specific CYP enzyme, it
`may have the potential
`to inhibit
`the metabolism of a
`substrate drug of that CYP enzyme. The inhibition potential
`is usually evaluated using human liver microsomes or cDNA-
`expressed microsomes. An in vitro inhibition constant (Ki)
`that reflects the inhibitory effect of the NME is determined
`and its value is compared to clinically relevant concentrations.
`Because hepatocyte concentration is not easily measured,
`plasma concentrations are often used for this estimation. For
`an NME as a reversible inhibitor for a particular CYP
`enzyme, the guidance suggests that in vivo inhibition studies
`with representative substrates for that enzyme are needed if
`the calculated [I]/Ki is >0.1, where [I] is the estimated mean
`maximum total (bound and unbound) plasma concentration
`(Cmax) at steady state of the highest clinical dose and Ki is the
`inhibition constant for the NME measured in vitro. The total
`plasma concentration (instead of the free plasma concentra-
`tion) is used as a conservative estimate to predict
`the
`expected higher hepatic concentration and to avoid false
`negative results when free plasma concentration is used in the
`I/Ki calculation. When evaluating the potential of the NME to
`inhibit CYP3A, at least two structurally different CYP3A
`substrates such as midazolam and testosterone should be used
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`(8,9). If the [I]/Ki is >0.1 from either substrate, an in vivo
`interaction study is recommended.
`In addition, time-dependent inhibition (TDI) potential
`for an NME should be evaluated. TDI is a collective term for
`a change (often an increase) in potency of CYP inhibitors
`during in vitro incubation or dosing period in vivo. Potential
`mechanisms include the formation of a more inhibitory
`metabolite or mechanism-based inhibition: the inactivation
`of enzymes by metabolic products that form haem or protein
`adducts. Over the past decade, time-dependent CYP inhibi-
`tion has been recognized to be responsible for some
`important drug interactions in vivo (10). For example, the
`calcium channel blocker, mibefradil, is a potent mechanism-
`based CYP3A inhibitor and P-glycoprotein (P-gp) inhibitor
`(11). Mibefradil was withdrawn in 1998 shortly after its
`approval as a consequence of serious drug–drug interactions
`with substrates of CYP3A and/or P-gp (11,12). Therefore,
`TDI should be studied and its possible in vivo drug
`interaction potential needs to be projected.
`Time-dependent inhibition is mainly assessed in vitro
`using microsomes or hepatocytes and has been incorporated
`increasingly in drug discovery process (13,14). Although
`inhibition parameters (i.e., kinact and KI) can be readily
`obtained in vitro, prediction of time-dependent inhibition in
`vivo remains challenging because of the complexity of the
`mechanism as compared to reversible inhibition. Thus, a
`decision tree with regard to the evaluation of mechanism-
`based inhibition in vivo based on in vitro parameters similar
`to the evaluation of reversible inhibition outlined in the FDA
`draft guidance needs to be developed.
`
`Understanding Whether an NME is an Inducer for a Particular
`P450 Enzyme
`
`An NME that induces a CYP enzyme can cause drug
`interactions with substrate drugs for that particular pathway
`leading to enhanced clearance. Human primary hepatocytes
`are the preferred experimental system for the evaluation of
`P450 induction. The results of a recent survey of the practice
`in pharmaceutical industries indicated general consensus that
`human hepatocyte culture induction studies are the best
`predictor of in vivo induction (15). However, there appeared
`to be no standard methods for conducting these studies and
`no consistent criteria for determining whether a clinical drug–
`drug interaction study should be carried out (15). The FDA
`guidance suggests that induction studies be carried out using
`freshly isolated or cryopreserved human hepatocytes or
`immortalized cell lines including a positive control. Hepato-
`cytes need to be prepared from at least three individual donor
`livers because of the known inter-individual differences in
`induction potential. When using immortalized cell lines, the
`experiment needs to be conducted in triplicate. If the increase
`in enzyme activity for NME-treated cells is >40% of a
`positive control in any one batch of hepatocytes or immor-
`talized cell lines, the NME is considered to be an enzyme
`inducer and in vivo induction studies are recommended. An
`alternative endpoint
`is the use of an EC50 (effective
`concentration at which 50% maximal induction occurs) value,
`an index that can be used to compare the potency of different
`compounds. Relative induction score approach has also been
`reported for prediction of induction potential (16).
`
`Studies have indicated that activation of the nuclear
`receptor, pregnane X receptor, results in the co-induction of
`CYP3A and CYP2C. Thus, a negative in vitro result for
`CYP3A induction may eliminate the need for additional
`induction studies for both CYP3A and CYP2C enzymes.
`However, whether CYP2C and CYP3A are always co-
`induced may need further validation. Because CYP1A2
`induction is mainly via aryl hydrocarbon receptor (AhR),
`CYP1A2 is not likely to be co-induced with CYP3A. For
`CYP2B6, although overlap exists between CYP2B6 and
`CYP3A inducers, there are data suggesting that certain
`CYP2B6 inducers selectively bind to the constitutive andros-
`tane receptor (CAR), and these inducers do not show
`significant induction for CYP3A (17). Therefore, the poten-
`tial
`for induction of CYP1A2 and CYP2B6 should be
`evaluated separately regardless of the CYP3A induction
`result.
`
`Phase II Enzymes
`
`Phase II enzymes have been recognized to play impor-
`tant roles in the pharmacokinetics of drugs. Historically, these
`enzymes have attracted less attention than CYP enzymes in
`drug interaction potential evaluation, most likely due to the
`lack of tools to study them and/or a lower incidence of
`observed adverse drug–drug interactions. Exceptions include
`the polymorphisms of N-acetyltransferases (18) resulting in
`fast and slow acetylators and acyl glucuronidation by UDP
`glucuronosyl transferases (UGTs) (19); both can lead to the
`formation of toxic metabolites. Recently, there has been an
`increased interest in drug–drug interactions involving UGTs.
`For example, polymorphism of UGT1A1 was shown to affect
`exposure of SN-38, an active metabolite of irinotecan, which
`has efficacy and safety implications (20,21).
`Similar to the CYP enzymes, UGTs are encoded by a
`UGT gene “superfamily” with 17 human UGT proteins
`identified to date (22). Unlike CYP enzymes, there is no
`consensus with respect to the tools,
`i.e., enzyme sources,
`selective substrates, inhibitors, and inducers for studying the
`UGT enzymes. Recombinant human UGTs, many are avail-
`able from commercial sources, have been used to investigate
`the individual UGT enzymes responsible for the formation of
`a drug glucuronide metabolite. UGT1A1, 1A3, 1A4, 1A6,
`1A9, 2B7, and 2B15 are considered to be the enzymes of the
`greatest importance in hepatic drug elimination (Zhang Y., et.
`al., book chapter submitted).
`Establishing in vitro–in vivo correlation for drugs that are
`eliminated by glucuronidation has been challenging as
`compared to CYP enzymes. For example, the use of micro-
`somes to determine the intrinsic clearance of drugs that are
`eliminated by glucuronidation is problematic because UGTs
`are integral proteins of the endoplasmic reticulum and are
`dependent on lipid for catalytic activity; both are variable
`parameters not controlled well in in vitro system.
`
`Prediction of Transporter-Mediated Drug Interaction
`
`In addition to the effects of drug metabolizing enzymes
`on the pharmacokinetics of drugs,
`increasing attention is
`being given to transporters where emerging evidence indi-
`cates their important role in modulating drug absorption,
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`distribution, metabolism, and elimination as well as the
`historical importance of transporters in the development of
`drug resistant tumors. Transporters, acting alone or in concert
`with drug metabolizing enzymes, can affect the pharmacoki-
`netics and/or pharmacodynamics of a drug. Of the various
`transporters, P-gp is the most well and extensively studied
`transporter.
`
`Understanding Whether an NME is a Substrate for P-gp
`
`To test whether the NME is a P-gp substrate, bidirec-
`tional experiments of cell transport are carried out with the
`NME to determine the net flux ratio for the basolateral to
`apical (B→ A) and apical to basolateral transport (A→B). If
`the efflux ratio, (B→A) to (A→B), is ≥2 and addition of P-gp
`inhibitors to the experiment decreases the net flux ratio by
`more than 50% or decreases the ratio to close to 1, then the
`NME is a potential P-gp substrate. A net flux ratio “cutoff”
`higher than 2 or a relative ratio to positive controls may be
`used to avoid false positives if a ratio of 2 is deemed non-
`discriminative as supported by prior experience with the cell
`system used. If in vitro experiments demonstrate that an
`NME is a P-gp substrate, additional drug-specific factors may
`be considered before determining whether an in vivo drug
`interaction study is warranted. For example, the bioavailabil-
`ity of the Biopharmaceutics Classification System Class 1 (23)
`or the Biopharmaceutics Drug Disposition Classification
`System Class 1 (24) NMEs that are highly soluble, highly
`permeable, and highly metabolized may not be significantly
`affected by a co-administered drug that is a P-gp inhibitor,
`and thus, an in vivo interaction study may not be needed.
`Nonetheless, it is recognized that the effects of P-gp inhibitors
`at the tissue levels (e.g., tumor or brain) cannot be easily
`assessed. If an NME is a substrate for both CYP enzyme and
`transporter, selection of inhibitors for studying inhibition
`needs to consider the significant overlap between enzymes
`and transporters (e.g., CYP3A and P-gp). A “dual” inhibitor
`for enzyme and transporter may be selected to study the
`maximal inhibition effect, although specific attribution of an
`AUC change to transporter or CYP enzyme may not be
`possible.
`For NME that has low cell permeability due to lack of
`basolateral transporters in the cell lines for P-gp evaluation,
`the use of membrane vesicles may be an alternative method
`to understand the “intrinsic” affinity of NME to P-gp.
`
`Understanding Whether an NME is an Inhibitor for P-gp
`
`To test whether the NME is a P-gp inhibitor, bidirec-
`tional experiments of cell transport are carried out after
`adding varying concentrations of the NME to both sides of
`the monolayer followed by adding known P-gp substrates to
`the apical or basal side of the monolayer. The NME is a
`potential P-gp inhibitor if the net flux ratio of a P-gp probe
`substrate is decreased in the presence of the NME. To
`determine the potency of inhibition, an IC50 (concentration
`that inhibits 50%) or Ki value is determined.
`The criteria for determining whether an in vivo drug
`interaction study is needed are evolving. The draft guidance
`published in Sept 2006 recommends [I]/IC50 of 0.1 as the
`“cutoff” for further in vivo evaluation, where [I] represents
`
`the total Cmax (bound plus unbound) at steady state at the
`highest clinical dose for NME (6). This ratio was adopted
`from criteria used to determine whether an NME is an
`inhibitor of P450 metabolizing enzymes. In contrast to P450
`enzymes in the liver or transporters in the kidney where [I]
`reflects the systemic Cmax, [I] concentrations at the luminal
`side of GI may be more relevant when evaluating P-gp
`inhibition by the NME following oral administration.
`To provide better criteria for recommending in vivo
`inhibition studies, in vitro IC50 (or Ki) values and in vivo
`inhibition data for marketed drugs and drugs under develop-
`ment, using the prototypic P-gp substrate digoxin, were
`collected and evaluated (25). Based on the evaluation results,
`the following alternative criteria are proposed: drugs that
`exhibit an [I]1/IC50>0.1 or [I]2/IC50>10 should be evaluated
`in vivo to determine whether there is clinically relevant P-gp
`inhibition with digoxin, a P-gp substrate with a narrow
`therapeutic index, where [I]1 is the mean NME steady-state
`total Cmax at
`the highest clinical dose and [I]2 is the
`theoretical maximal gastrointestinal NME concentration after
`oral administration estimated by the ratio of the highest
`clinical dose (mg) to a volume of 250 mL. If an NME meets
`either criterion, an in vivo drug interaction study with digoxin
`is recommended. Results from a recent publication from
`Fenner et al. (26) indicate that the proposed criteria for in
`vivo P-gp inhibition evaluation are reasonable.
`Studying P-gp inhibition with digoxin is clinically rele-
`vant and useful because digoxin has a narrow therapeutic
`index and is one of the few known P-gp substrates that is not
`a CYP3A substrate. As more information about the interplay
`of P-gp and CYP3A emerges, the clinical relevance of P-gp
`may be better understood. Inhibition data obtained with
`digoxin may be applied to other “pure” P-gp substrates that
`have a narrow therapeutic index.
`It is important to recognize the limitations of only using
`in vitro IC50 to predict in vivo interactions mediated by P-gp
`inhibition. The in vitro IC50 determination may be different
`across different laboratories. Appropriate controls are need-
`ed to compare results from different laboratories. Continued
`data collection is needed to further evaluate the adequacy of
`these criteria to predict possible in vivo interactions mediated
`by P-gp. A working group was formed following the October
`2008 Transporter Workshop to continue further research in
`the area towards better predicting in vivo P-gp-mediated
`interaction based on in vitro data (Dr. Caroline Lee, personal
`communication).
`
`Understanding Whether an NME is an Inducer for P-gp
`
`Methods for in vitro evaluation for P-gp induction are
`not well understood. Thus, the P-gp induction potential of an
`investigational drug can only be evaluated in vivo. Because of
`similarities in the mechanism of CYP3A and P-gp induction,
`information from tests of CYP3A inducibility can inform
`decisions about the induction P-gp. If an NME is found not to
`induce CYP3A in vitro, no further tests of CYP3A and P-gp
`induction in vivo are necessary. If a study of the NME’s effect
`on CYP3A activity in vivo is indicated from a positive in vitro
`screen but the drug is shown not to induce CYP3A in vivo,
`then no further test of P-gp induction in vivo is necessary.
`However, if the in vivo CYP3A induction test is positive, then
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`an additional study of the NME’s effect on a P-gp probe
`substrate is recommended (6).
`
`Evaluation of Transporters Other Than P-gp
`
`Reports of drug disposition mediated by membrane
`transporters other than P-gp continue to appear in the
`literature. For example, OATP1B1 and NTCP may play a
`major role in the disposition of the HMG-CoA reductase
`inhibitor rosuvastatin (27,28). A recent clinical study dem-
`onstrated that a genetic variation in the hepatic uptake
`transporter OCT1 is a determinant of metformin pharmaco-
`kinetics and may be associated with variation in response to
`this drug (29,30). Drug interaction potential exists if an
`NME is a substrate or inhibitor/inducer of transporters.
`However, routine in vitro studies cannot be recommended
`for transporters other than P-gp at this time because no
`consensus has been reached with regard to in vitro methods
`or probe substrates and inhibitors. Until additional knowl-
`edge and technologies are available, recommendations for
`evaluation of transporter-based drug interactions other than
`P-gp (e.g., OATP, BCRP, OATs, and OCTs) are on a case by
`case basis.
`A recent DIA/FDA Critical Path Transporter Workshop
`has discussed the emerging science in transporters (7). An
`international working group, including members from acade-
`mia, industry, and the FDA, are working on a whitepaper to
`highlight the recent progress in this field including in vitro
`tools and criteria for in vivo drug interaction evaluation for
`main transporters including P-gp, BCRP, OATP, OCT, and
`OAT.
`
`In Silico Models
`
`The current FDA guidance uses criteria that are based
`on in vitro Ki values in combination with in vivo total plasma/
`blood concentrations to predict
`the likelihood of drug
`interactions for NMEs as CYP inhibitors. The limitations of
`the I/Ki approach have been discussed elsewhere (31–36). For
`example, using total [I] may over-predict for drugs that are
`highly protein-bound in plasma. Conversely, using unbound
`plasma [I] may under-predict
`for drugs that are highly
`concentrated in the liver by uptake transporters (37). The
`use of single inhibitor concentration also poses a potential
`limitation because the in vivo drug interactions are expected
`to be dependent on the pharmacokinetic characteristics of
`both inhibitor and substrate.
`Over the years, in vitro to in vivo prediction models
`have been developed to predict/simulate the magnitude of
`the interaction based on in vitro results (16,38–41). Com-
`mercial software products have been developed as well.
`Time–concentration profile and/or inter-individual variabil-
`ity of intrinsic factors influencing ADME processes of both
`substrate and inhibitor drugs based on physiological-based
`pharmacokinetic prediction approach have been integrated
`into the modeling algorithm (38,39,42–45). Modeling and
`simulation of drug interactions in vivo using the physiolog-
`ical-based pharmacokinetic approach appear to be valuable
`in evaluating the magnitude of drug interaction potential
`under different clinical scenarios, e.g., different dosing
`regimen (44,46,47). The tools are helpful not only in
`
`interaction prediction but also in clinical study design.
`Although progresses have been made in the in silico models
`to predict drug interactions, challenges remain because the
`lack of the true physiological representation in the models
`limits the ability to predict in vivo situations such as enzyme
`and transporter interplay at various tissues, e.g., different
`interplay of CYP3A4 and P-gp in the intestine vs. in the
`liver.
`
`Recent NDA Examples
`
`Recent IND and NDA reviews indicate that most
`pharmaceutical companies conduct recommended in vitro
`evaluation studies according to the guidance prior to drug
`approval. For example, a recent review of 121 new molecular
`entity drugs approved during 2003 and 2008 (up to Dec. 21,
`2008) indicated that 88% (57 out of 65) of those intended for
`oral administration included in vitro study information with
`regard to which metabolic and/or transport pathways are
`involved in the ADME process of the drug (Fig. 1) (48). P450
`3A is the main P450 enzyme involved in the metabolism of
`NMEs. In addition, most NMEs were studied for their
`inhibition or induction potential for major P450 enzymes.
`The information has greatly enhanced our ability to predict in
`vivo interaction potential to construct an informative labeling.
`Besides major CYPs and P-gp, in vitro evaluation studies are
`increasingly conducted with regard to whether an NME is a
`substrate or inhibitor for phase II enzymes (mostly UGTs)
`and transporters other than P-gp (e.g., BCRP, OATP1B1,
`OAT, and OCT). Although in vitro studies are being
`conducted, we found that positive in vitro findings are not
`necessarily always followed by in vivo drug interaction
`evaluation. In these situations, appropriate language is
`usually constructed in the labeling based on in vitro results.
`In some cases, post-marketing drug interaction studies are
`requested according to clinical need.
`For example, ambrisentan, an endothelin receptor an-
`tagonist, was approved in 2007 for the treatment of pulmo-
`nary arterial hypertension (48). It was found to be a substrate
`of CYP3A, CYP2C19, UGT1A9, UGT2B7, UGT1A3, OATP,
`and P-gp. Because the relative contribution of each pathway
`
`Fig. 1. Distribution of metabolism and transport pathways for NMEs
`approved between 2003 and 2008 intended for oral administration
`
`5
`
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`Predicting Drug–Drug Interactions: An FDA Perspective
`
`305
`
`for ambrisentan is not clear, specific interaction studies with
`inhibitors for these pathways were not conducted. The
`“HIGHLIGHT” section of the labeling states that “…based
`on in vitro data, interactions with P-glycoprotein (P-gp), the
`organic anion transport protein (OATP), CYP3A4,and
`CYP2C19 inhibitors, and uridine 5′-diphosphate glucurono-
`syltransferases (UGTs) would be expected.” The “WARN-
`INGS AND PRECAUTIONS” section of the labeling states
`that caution should be exercised with ambrisentan when co-
`administered with cyclosporine A (a CYP3A, OATP, and
`P-gp inhibitor), strong CYP3A or CYP2C19 inhibitors. Post-
`marketing studies have been committed to explore the
`interactions between ambrisentan and a strong inhibitor of
`CYP2C19 (e.g., omeprazole), cyclosporine A (a strong
`inhibitor of OATP and P-gp), and rifampin (an inhibitor of
`OATP and inducer of P-gp, CYP3A, and CYP2C19).
`
`Challenges in Predicting In Vivo Drug Interactions
`
`Our understanding of the relationship between in vitro
`and in vivo drug–drug interactions and our ability to predict
`these interactions has improved over the years. The FDA
`drug interaction guidance (6) has included various decision
`trees for determining when clinical drug interaction studies
`are indicated. Depending on the study results, recommen-
`dations can then be made whether dosage adjustment is
`required including suitable language in the labeling. Even
`without in vivo evaluation, in vitro results are included in
`the labeling as the basis for cautionary language when
`appropriate.
`these advances, unexpected drug–drug
`In spite of
`interactions do occur which could be due to several variables
`that we do not yet understand or cannot accurately measure.
`First,
`the interaction may be due to pharmacodynamic
`interactions or pharmacokinetic interaction involved with
`unknown mechanism (e.g., transporter or uncommon meta-
`bolic pathways). Second, prediction could be confounded
`when multiple enzymes or both metabolizing enzymes and
`transporters are involved in a drug’s disposition. The lack of
`in vitro models that represent the true physiological environ-
`ment also limits our ability to predict in vivo situations where
`multiple drugs are co-administered and concomitant inhibi-
`tion and induction of metabolic enzymes and