Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulations. Sheila Annie Peters

and time‐dependent inhibition of enzymes ¹CYPs UGT1A1 UGT2B7 CYP3A4, CYP2C9 CYP2C19 UGT2B7 — — Induction of enzymes CYP1A2 CYP2B6 CYP3A4 ²CYP2C CYP3A4 — — Transporters Inhibition of uptake transporters OATP1B1 OATP1B3 OCT1 OCT1 OAT1 OAT3 OCT2 — Inhibition of efflux transporters P‐gp BCRP ³MRP2 P‐gp BCRP ³MRP2 P‐gp BCRP MATE1 MATE2/K ³MRP2 ³MRP4 P‐gp BCRP

¹ Cytochrome P450 isoforms (CYPs) 1A2, 2B6, 2C8, 2C9, 2C19, 2D6, 3A4, 3A5. If these do not play a role, other CYPs (2A6, 2J2, 4F2, and 2E1), other Phase I enzymes (aldehyde oxidase, carboxylesterase, monoamine oxidase, flavin monooxygenase, xanthine oxidase, and alcohol/aldehyde dehydrogenase), or Phase II enzymes (UDP glucuronosyl transferases or UGTs and sulfotransferases or SULTs) may be important.

² CYP2C enzymes are induced via activation of pregnane X receptor (PXR) just as CYP3A. Since CYP3A is more sensitive to inducer effect, CYP2C induction may be evaluated, if the drug induces CYP3A. UGTs may be coinduced with CYP3A.

³ Not in current regulatory guidelines.

2.2 DRUG INTERACTIONS MEDIATED BY ENZYMES AND TRANSPORTERS AT VARIOUS SITES

The DDI mechanisms and the enzymes and transporters at various sites recommended for DDI risk assessment by FDA and EMA are summarized in Table 2.1.

      The rationale for the significance of enzymes and transporters presented in Table 2.1 are as follows:

       High affinity, low‐capacity enzymes like CYPs 2C9, 2C19, and 2D6 are more susceptible for inhibition.

       Polymorphic enzymes (CYPs 3A5, 2B6, 2C8, 2C19, 2D6; UGTs 1A1, and 2B7) when involved in DDI could contribute to exaggerated exposure variability in some patients.

       Enzymes that are expressed in gut (CYP3A4, UGT2B7, etc.) are exposed to higher perpetrator concentrations during absorption phase and therefore contribution of the gut to the overall DDI risk is considerably high.

       Clinically relevant DDIs are rare for UGTs, as many of them are low‐affinity, high‐capacity enzymes with broad substrate specificity. Most interactions involving UGTs are associated with low AUC ratios and mostly confined to UGT2B7, a polymorphic enzyme that is involved in the metabolism of many marketed drugs.

       Among transporters, organic anion transporting protein (OATP1B1 and OATP1B3), organic cation transporters (OCT1, OCT2), P‐glycoprotein (P‐gp), and breast cancer resistance protein (BCRP) are polymorphic.

       Many statins rely on OATP1B1 for their uptake into liver. They are likely to be victims of DDI, when coadministered with OATP1B1 inhibitors. Due to their widespread use, high probability of comedication, and the risk of myalgia and rhabdomyolysis with increased exposure, statins attract considerable interest with respect to DDI.

       Among the efflux transporters, interactions with P‐gp are the most studied. Inhibition of P‐gp may not result in clinically significant differences in the exposure of the victim drug, but it can attenuate the efficacy of drugs targeting barrier tissues such as brain, lymphocytes, and tumor.

2.3 FACTORS AFFECTING DDI

The extent of DDI will depend on the characteristics of the perpetrator and victim drugs involved in the interaction. Perpetrator and victim properties impacting drug interaction risk are summarized in Figure 2.2. For an inhibitor, the greater the unbound inhibitor concentration relative to its potency, the greater is the extent of inhibition. Inhibitor concentrations at any point of time will depend on the dose administered and the organ where the affected enzyme or transporter is located. For a victim of inhibition, the greater its dependence on the inhibited route for its elimination, the greater is the potential for an altered pharmacokinetics of the drug. If more than 70% of a drug is eliminated using the inhibited pathway, the risk for interaction is high (Dunne et al., 2011). Thus, it is important to balance the clearance of a victim drug between hepatic, renal, and biliary routes during the design stage, in order to minimize risk from drug–drug interactions. For a high clearance victim drug that is orally administered, the magnitude of interaction is likely to be high due to first‐pass, making it more sensitive to DDI compared with a low clearance drug. Victim drugs associated with a narrow therapeutic window and high variability are more sensitive to DDI.

Figure 2.2. Perpetrator and victim properties impacting drug interaction risk.

      Induction and/or inhibition of drug transporters of the small intestine, liver, and kidney are major determinants of drug–drug interactions. Transporter‐mediated drug–drug interactions in these three organs can considerably influence the pharmacokinetics and clinical effects of drugs. Transporters of interest are those controlling intestinal efflux, hepatic efflux, blood–brain barrier (P‐gp and BCRP), hepatic uptake (OATP1B1 and OATP1B3) and renal tubular uptake/bidirectional transport (OAT1, OAT3, OCT2), and efflux (MATE1 and MATE2/K). Renal DDIs are rare and associated with significantly lower AUC ratios compared with hepatic DDIs. Victims of renal DDIs are generally compounds whose eliminations are largely dependent on the renal route. Examples include metformin, a substrate of OCT2 and MATEs, and the endogenous compound creatinine, a substrate of OAT2, OCT2, and MATEs, the secretion of both of which are reduced by cimetidine, known to inhibit OCT2 and MATEs. Cimetidine also reduces the renal clearance of bisoprolol, nicotine, and procainamide (Ayrton and Morgan, 2001; Shitara et al., 2009; Shitara et al., 2009; Kirch et al., 1987; Somogyi et al., 1987; Bendayan et al., 1990; Ayrton and Morgan, 2001; Shitara et al., 2009; Ivanyuk et al., 2017). Uptake transporters act in concert with efflux transporters to eliminate toxins (e.g., OCT2 and MATE1, MATE2‐K). Therefore, for secreted drugs that are reliant on transporters for overcoming the membrane barrier, the inhibition of efflux transporters could result in an accumulation of drugs in the cytoplasm of proximal