Azithromycin (AZ) is a broad-spectrum macrolide antibiotic with a long half-life and a large volume of distribution. It is primarily used for the treatment of respiratory, enteric, and genitourinary bacterial infections. AZ is not approved for the treatment of viral infections, and there is no well-controlled, prospective, randomized clinical evidence to support AZ therapy in coronavirus disease 2019 . Nevertheless, there are anecdotal reports that some hospitals have begun to include AZ in combination with hydroxychloroquine or chloroquine (CQ) for treatment of COVID-19. It is essential that the clinical pharmacology (CP) characteristics of AZ be considered in planning and conducting clinical trials of AZ alone or in combination with other agents, to ensure safe study conduct and to increase the probability of achieving definitive answers regarding efficacy of AZ in the treatment of COVID-19. The safety profile of AZ used as an antibacterial agent is well established. 1 This work assesses published in vitro and clinical evidence for AZ as an agent with antiviral properties. It also provides basic CP information relevant for planning and initiating COVID-19 clinical studies with AZ, summarizes safety data from healthy volunteer studies, and safety and efficacy data from phase II and phase II/III studies in patients with uncomplicated malaria, including a phase II/III study in pediatric patients following administration of AZ and CQ in combination. This paper may also serve to facilitate the consideration and use of a priori-defined control groups for future research.

To address the most appropriate endogenous biomarker for drug–drug interaction risk assessment, eight healthy subjects received an organic anion transporting polypeptide 1B (OATP1B) inhibitor (rifampicin, 150, 300, and 600 mg), and a probe drug cocktail (atorvastatin, pitavastatin, rosuvastatin, and valsartan). In addition to coproporphyrin I, a widely studied OATP1B biomarker, we identified at least 4 out of 28 compounds (direct bilirubin, glycochenodeoxycholate‐3‐glucuronide, glycochenodeoxycholate‐3‐sulfate, and hexadecanedioate) that presented good sensitivity and dynamic range in terms of the rifampicin dose‐dependent change in area under the plasma concentration‐time curve ratio (AUCR). Their suitability as OATP1B biomarkers was also supported by the good correlation of AUC0‐24h between the endogenous compounds and the probe drugs, and by nonlinear regression analysis (AUCR−1 vs. rifampicin plasma Cmax (maximum total concentration in plasma)) to yield an estimate of the inhibition constant of rifampicin. These endogenous substrates can complement existing OATP1B‐mediated drug–drug interaction risk assessment approaches based on agency guidelines in early clinical trials.

Understanding transporter-mediated drug-drug interactions (DDIs) for investigational agents is important during drug development to assess DDI liability, its clinical relevance, and to determine appropriate DDI management strategies. P-glycoprotein (P-gp) is an efflux transporter that influences the pharmacokinetics (PK) of various compounds. Assessing transporter induction in vitro is challenging and is not always predictive of in vivo effects, and hence there is a need to consider clinical DDI studies; however, there is no clear guidance on when clinical evaluation of transporter induction is required. Furthermore, there is no proposed list of index transporter inducers to be used in clinical studies. This review evaluated DDI studies with known P-gp inducers to better understand the mechanism and site of P-gp induction, as well as the magnitude of induction effect on the exposure of P-gp substrates. Our review indicates that P-gp and cytochrome P450 (CYP450) enzymes are coregulated via the pregnane xenobiotic receptor (PXR) and the constitutive androstane receptor (CAR). The magnitude of the decrease in substrate drug exposure by P-gp induction is generally less than that of CYP3A. Most P-gp inducers reduced total bioavailability with a minor impact on renal clearance, despite known expression of P-gp at the apical membrane of the kidney proximal tubules. Rifampin is the most potent P-gp inducer, resulting in an average reduction in substrate exposure ranging between 20 and 67%. For other inducers, the reduction in P-gp substrate exposure ranged from 12 to 42%. A lower reduction in exposure of the P-gp substrate was observed with a lower dose of the inducer and/or if the administration of the inducer and substrate was simultaneous, i.e. not staggered. These findings suggest that clinical evaluation of the impact of P-gp inducers on the PK of investigational agents that are substrates for P-gp might be warranted only for compounds with a relatively steep exposure-efficacy relationship.

ABSTRACT:Silymarin, used by 30 to 40% of liver disease patients, is composed of six major flavonolignans, each of which may contribute to silymarin's hepatoprotective properties. Previous studies have only described the pharmacokinetics for two flavonolignans, silybin A and silybin B, in healthy volunteers. The aim of this study was to determine the pharmacokinetics of the major silymarin flavonolignans in liver disease patients. Healthy volunteers and three patient cohorts were administered a single, 600-mg p.o. dose of milk thistle extract, and 14 blood samples were obtained over 24 h.

Quantitative prediction of drug‐drug interactions (DDIs) involving organic anion transporting polypeptide (OATP)1B1/1B3 inhibition is limited by uncertainty in the translatability of experimentally determined in vitro inhibition potency (half‐maximal inhibitory concentration (IC50)). This study used an OATP1B endogenous biomarker‐informed physiologically‐based pharmacokinetic (PBPK) modeling approach to predict the effect of inhibitor drugs on the pharmacokinetics (PKs) of OATP1B substrates. Initial static analysis with about 42 inhibitor drugs, using in vitro IC50 values and unbound liver inlet concentrations (Iin,max,u), suggested in vivo OATP1B inhibition risk for drugs with R‐value (1+ Iin,max,u/IC50) above 1.5. A full‐PBPK model accounting for transporter‐mediated hepatic disposition was developed for coproporphyrin I (CP‐I), an endogenous OATP1B biomarker. For several inhibitors (cyclosporine, diltiazem, fenebrutinib, GDC‐0810, itraconazole, probenecid, and rifampicin at 3 different doses), PBPK models were developed and verified against available CP‐I plasma exposure data to obtain in vivo OATP1B inhibition potency—which tend to be lower than the experimentally measured in vitro IC50 by about 2‐fold (probenecid and rifampicin) to 37‐fold (GDC‐0810). Models verified with CP‐I data are subsequently used to predict DDIs with OATP1B probe drugs, rosuvastatin and pitavastatin. The predicted and observed area under the plasma concentration‐time curve ratios are within 20% error in 55% cases, and within 30% error in 89% cases. Collectively, this comprehensive study illustrates the adequacy and utility of endogenous biomarker‐informed PBPK modeling in mechanistic understanding and quantitative predictions of OATP1B‐mediated DDIs in drug development.