The drug–drug interaction of sorafenib mediated by P-glycoprotein and CYP3A4

1.?The aim of this study was to investigate the potential drug–drug interaction of sorafenib mediated by P-glycoprotein (P-gp) and cytochrome P450 3A4 (CYP3A4).

2.?In this research, a sensitive and reliable LC-MS/MS method was developed and applied for the determination of sorafenib in rat plasma. The pharmacokinetic profiles of orally administered sorafenib from rats with and without verapamil pretreatment were investigated.

3.?The results indicated that when the rats were pretreated with verapamil, the C_max of sorafenib increased from 55.73?ng/ml to 87.72?ng/ml (57.40%), and the AUC_(0?t) increased by approximately 58.2% when sorafenib was co-administered with verapamil. Additionally, the effects of verapamil on the absorption of sorafenib were investigated using the Caco-2 cell transwell model, and the effects of verapamil on the metabolic stability of sorafenib were also studied using rat liver microsomes incubation systems. A markedly higher transport of sorafenib across the Caco-2 cells was observed in the basolateral-to-apical direction and was abrogated in the presence of the P-gp inhibitor, verapamil. The results indicated that P-gp was involved in the transport of sorafenib, and verapamil could increase its absorption in the Caco-2 cell model, and the metabolic stability of sorafenib was prolonged by the pretreatment with verapamil.

4.?In conclusion, the drug–drug interaction of sorafenib might happen when sorafenib was co-administered with P-gp or CYP3A4 inhibitors.     

Comparison of two endogenous biomarkers of CYP3A4 activity in a drug–drug interaction study between midostaurin and rifampicin

Purpose

Midostaurin, a multitargeted tyrosine kinase inhibitor, is primarily metabolized by CYP3A4. This midostaurin drug–drug interaction study assessed the dynamic response and clinical usefulness of urinary 6β-hydroxycortisol to cortisol ratio (6βCR) and plasma 4β-hydroxycholesterol (4βHC) for monitoring CYP3A4 activity in the presence or absence of rifampicin, a strong CYP3A4 inducer.

Methods

Forty healthy adults were randomized into groups for either placebo or treatment with rifampicin 600 mg QD for 14 days. All participants received midostaurin 50 mg on day 9. Midostaurin plasma pharmacokinetic parameters were assessed. Urinary 6βCR and plasma 4βHC levels were measured on days 1, 9, 11, and 15.

Results

Both markers remained stable over time in the control group and increased significantly in the rifampicin group. In the rifampicin group, the median increases (vs day 1) on days 9, 11, and 15 were 4.1-, 5.2-, and 4.7-fold, respectively, for 6βCR and 3.4-, 4.1-, and 4.7-fold, respectively, for 4βHC. Inter- and intrasubject variabilities in the control group were 45.6 % and 30.5 %, respectively, for 6βCR, and 33.8 % and 7.5 %, respectively, for 4βHC. Baseline midostaurin area under the concentration–time curve (AUC) correlated with 4βHC levels (ρ?=??0.72; P?=?.003), but not with 6βCR (ρ?=?0.0925; P?=?.6981).

Conclusions

Both 6βCR and 4βHC levels showed a good dynamic response range upon strong CYP3A4 induction with rifampicin. Because of lower inter- and intrasubject variability, 4βHC appeared more reliable and better predictive of CYP3A4 activity compared with 6βCR. The data from our study further support the clinical utility of these biomarkers.     

Enzymatic characteristics of CYP3A5 and CYP3A4: A comparison of in vitro kinetic and drug–drug interaction patterns

CYP3A4 and CYP3A5 exhibit significant overlap in substrate specificity, but can differ in catalytic activity and regioselectivity. To investigate their characteristics further, the enzymatic reactions of the two CYP3A enzymes were compared using midazolam, nifedipine, testosterone and terfenadine as substrates. Both CYP3A5 and CYP3A4 showed sigmoid and substrate inhibition patterns for testosterone 6β-hydroxylation and terfenadine t-butylhydroxylation (TFDOH), respectively. In the other reactions, the kinetic model for CYP3A5 was not similar to that for CYP3A4. An inhibition study demonstrated that the interactions between α-naphthoflavone (αNF) and CYP3A substrates were different for the two CYP3A enzymes. αNF stimulated nifedipine oxidation catalysed by CYP3A5, but did not stimulate that catalysed by CYP3A4. αNF at less than 32?µM inhibited TFDOH catalysed by CYP3A5, but did not inhibit that catalysed by CYP3A4. These results indicate that CYP3A5 has different enzymatic characteristics from CYP3A4 in some CYP3A catalysed reactions.     

Oral administration of a low dose of midazolam (75 μg) as an in vivo probe for CYP3A activity

Objective We investigated whether the oral administration of a low dose (75 µg) of midazolam, a CYP3A probe, can be used to measure the in vivo CYP3A activity.Methods Plasma concentrations of midazolam, 1OH-midazolam and 4OH-midazolam were measured after the oral administration of 7.5 mg and 75 µg midazolam in 13 healthy subjects without medication, in four subjects pretreated for 2 days with ketoconazole (200 mg b.i.d.), a CYP3A inhibitor, and in four subjects pretreated for 4 days with rifampicin (450 mg q.d.), a CYP3A inducer.Results After oral administration of 75 µg midazolam, the 30-min total (unconjugated + conjugated) 1OH-midazolam/midazolam ratios measured in the groups without co-medication, with ketoconazole and with rifampicin were (mean±SD): 6.23±2.61, 0.79±0.39 and 56.1±12.4, respectively. No side effects were reported by the subjects taking this low dose of midazolam. Good correlations were observed between the 30-min total 1OH-midazolam/midazolam ratio and midazolam clearance in the group without co-medication (r²=0.64, P<0.001) and in the three groups taken together (r²=0.91, P<0.0001). Good correlations were also observed between midazolam plasma levels and midazolam clearance, measured between 1.5 h and 4 h.Conclusion A low oral dose of midazolam can be used to phenotype CYP3A, either by the determination of total 1OH-midazolam/midazolam ratios at 30 min or by the determination of midazolam plasma levels between 1.5 h and 4 h after its administration.     

Development of a simultaneous LC–MS/MS method to predict in vivo drug–drug interaction in mice

Cocktail substrates are useful in investigating drug–drug interactions (DDI) that can rapidly identify the cytochrome P450 (CYP) isoforms that interact with test drugs. In this study, we developed and validated five probe drugs for CYP1A, CYP2B, CYP2C, CYP2D, and CYP3A using LC–MS/MS to determine CYP activities in mice. The five probe substrates were caffeine (2 mg/kg), bupropion (30 mg/kg), omeprazole (4 mg/kg), dextromethorphan (40 mg/kg), and midazolam (2 mg/kg) for CYP1A, CYP2B, CYP2C, CYP2D, and CYP3A, respectively. The cocktail substrates were orally administered to male 5-week-old ICR mice over 0–240 min. The analytical method was validated; it showed high selectivity, linearity, and acceptable accuracy. We confirmed the lack of interaction of this cocktail in the control state (no effect of CYP inducer or inhibitor) and suggested AUC_ratio (metabolite/substrate) as a unit to evaluate DDI in vivo. In addition, the cocktail assay was applied for the determination of pharmacokinetic parameters against phenobarbital as a selective CYP2B inducer and ketoconazole as a strong CYP3A inhibitor. The concentration of cocktail substrates and the LC–MS/MS method were optimized. In conclusion, we developed a simultaneous and comprehensive analysis system for predicting potential DDI in mice.     

Investigation of drug–polymer interaction in solid dispersions by vapour sorption methods

The objective of this study was to investigate the effect of different polymeric carriers in solid dispersions with an active pharmaceutical ingredient (API) on their water vapour sorption equilibria and the influence of the API–polymer interactions on the dissolution rate of the API. X-ray diffraction, scanning electron microscopy (SEM), moisture sorption analysis, infrared (IR) spectroscopy and dissolution tests were performed on various API–polymer systems (Valsartan as API with Soluplus, PVP and Eudragit polymers) after production of amorphous solid dispersions by spray drying. The interactions between the API and polymer molecules caused the water sorption isotherms of solid dispersions to deviate from those of ideal mixtures. The moisture sorption isotherms were lower in comparison with the isotherms of physical mixtures in all combinations with Soluplus and PVP. In contrast, the moisture sorption isotherms of solid dispersions containing Eudragit were significantly higher than the corresponding physical mixtures. The nature of the API–polymer interaction was explained by shifts in the characteristic bands of the IR spectra of the solid dispersions compared to the pure components. A correlation between the dissolution rate and the water sorption properties of the API–polymer systems has been established.     

Effects of isolation housing and timing of drug administration on amikacin kinetics in mice

目的：研究社会环境及给药时刻对小鼠阿米卡星代谢的影响．方法：小鼠按饲养环境：隔离饲养（Ｉ）或集体饲养（Ａ）及给药时间：日中（Ｄ）及午夜（Ｎ）随机分为：Ｉ－Ｄ，Ｉ－Ｎ，Ａ－Ｄ，Ａ－Ｎ４组．饲养４周后于Ｄ（１３∶００）或Ｎ（０１∶００）ｓｃ阿米卡星１５ｍｇ·ｋｇ－１，测定给药后其血浆浓度，以开放一室模型拟合并计算有关药代动力学参数．结果：Ａ－Ｎ组阿米卡星清除率较Ａ－Ｄ及Ｉ－Ｎ组增大，血浆半衰期变短，０－１小时血浆浓度时间曲线下面积（ＡＵＣ（０－１））较Ｉ－Ｎ组减少．隔离饲养两组（Ｉ－Ｄ，Ｉ－Ｎ）间药代动力学参数无显著差异．结论：社会环境及给药时刻均显著影响小鼠阿米卡星代谢动力学．     

Potential protective effect of sunitinib after administration of diclofenac: biochemical and histopathological drug–drug interaction assessment in a mouse model

Sunitinib is a tyrosine kinase inhibitor for GIST and advanced renal cell carcinoma. Diclofenac is used in cancer pain management. Coadministration may mediate P450 toxicity. We evaluate their interaction, assessing biomarkers ALT, AST, BUN, creatinine, and histopathological changes in the liver, kidney, heart, brain, and spleen. ICR mice (male, n?=?6 per group/dose) were administered saline (group A) or 30 mg/kg diclofenac ip (group B), or sunitinib po at 25, 50, 80, 100, 140 mg/kg (group C) or combination of diclofenac (30 mg/kg, ip) and sunitinib (25, 50, 80, 100, 140 mg/kg po). Diclofenac was administered 15 min before sunitinib, mice were euthanized 4 h post-sunitinib dose, and biomarkers and tissue histopathology were assessed. AST was 92.2?±?8.0 U/L in group A and 159.7?±?14.6 U/L in group B (p?<?0.05); in group C, it the range was 105.1–152.6 U/L, and in group D, it was 156.0–209.5 U/L (p?<?0.05). ALT was 48.9?±?1.6 U/L (group A), 95.1?±?4.5 U/L (p?<?0.05) in group B, and 50.5–77.5 U/L in group C and 82.3–115.6 U/L after coadministration (p?<?0.05). Renal function biomarker BUN was 16.3?±?0.6 mg/dl (group A) and increased to 29.9?±?2.6 mg/dl in group B (p?<?0.05) and it the range was 19.1–33.3 mg/dl (p?<?0.05) and 26.9–40.8 mg/dl in groups C and D, respectively. Creatinine was 5.9 pmol/ml in group A; 6.2 pmol/ml in group B (p?<?0.01), and the range was 6.0–6.2 and 6.2–6.4 pmol/ml in groups C and D, respectively (p?<?0.05 for D). Histopathological assessment (vascular and inflammation damages) showed toxicity in group B (p?<?0.05) and mild toxicity in group C. Damage was significantly lesser in group D than group B (p?<?0.05). Spleen only showed toxicity after coadministration. These results suggest vascular and inflammation protective effects of sunitinib, not shown after biomarker analysis.     

Model for the drug–drug interaction responsible for CYP3A enzyme inhibition. II: establishment and evaluation of dexamethasone-pretreated female rats

1.?Cytochrome P450 (CYP) 3A catalysis of testosterone 6β-hydroxylation in female rat liver microsomes was significantly induced, then reached a plateau level after pretreatment with 80?mg?kg^?1?day^?1 dexamethasone (DEX) for 3 days.

2.?Midazolam was mainly metabolized by CYP3A in DEX-treated female rat liver microsomes from an immuno-inhibition study, and the apparent K_m was 1.8?μM, similar to that in human microsomes.

3.?Ketoconazole and erythromycin, typical CYP3A inhibitors, demonstrated extensive inhibition of midazolam metabolism in DEX-treated female rat liver microsomes, and the apparent K_i values were 0.088 and 91.2?μM, respectively. The values were similar to those in humans, suggesting that DEX-treated female rat liver microsomes have properties similar to those of humans.

4.?After oral administration of midazolam, the plasma midazolam concentration in DEX-treated female rats significantly decreased compared with control female rats. The area under the plasma concentration curve (AUC) and elimination half-life were one-11th and one-20th of those of control female rats, respectively.

5.?Using DEX-treated female rats, the effect of CYP3A inhibitors on midazolam pharmacokinetics was evaluated. The AUC and maximum concentration in plasma (C_max) increased when ketoconazole was co-administered with midazolam.

6.?It was shown that the drug–drug interaction that occurs in vitro is also observed in vivo after oral administration of midazolam. In conclusion, the DEX-treated female rat could be a useful model for evaluating drug–drug interactions based on CYP3A enzyme inhibition.     

Model for the drug–drug interaction responsible for CYP3A enzyme inhibition. I: evaluation of cynomolgus monkeys as surrogates for humans

1.?Anti-human cytochrome P450 (CYP) 3A4 antiserum completely inhibited midazolam metabolism in monkey liver microsomes, suggesting that midazolam was mainly metabolized by CYP3A enzyme(s) in monkey liver microsomes.

2.?Midazolam metabolism was also inhibited in vitro by typical chemical inhibitors of CYP3A, such as ketoconazole, erythromycin and diltiazem, and the apparent K_i values for ketoconazole, erythromycin and diltiazem were 0.127, 94.2 and 29.6?μM, respectively.

3.?CYP3A inhibitors increased plasma midazolam concentrations when midazolam and CYP3A inhibitors were co-administered orally. However, the pharmacokinetic parameters of midazolam were not changed by treatment with CYP3A inhibitors when midazolam was given intravenously. This suggests that CYP3A inhibitors modified the first-pass metabolism in the liver and/or intestine, but not systemic metabolism.

4.?The drug–drug interaction responsible for CYP3A enzyme(s) inhibition was observed when midazolam and inhibitors were co-administrated orally. Therefore, it was concluded that monkeys given midazolam orally could be useful models for predicting drug–drug interactions in man based on CYP3A enzyme inhibition.     

Method for predicting the risk of drug–drug interactions involving inhibition of intestinal CYP3A4 and P-glycoprotein

1. To develop a method to predict the risk of drug–drug interactions involving the inhibition of intestinal CYP3A4 or P-glycoprotein, data from clinical drug–drug interaction studies of CYP3A4 and/or P-glycoprotein substrates were analysed. The ratio of inhibitor dose (Dose_i) to inhibition constant (K_i), termed the drug-interaction number, was used to index intestinal drug–drug interaction.

2. From the analysis, it was found that (1) CYP3A4 inhibitors with a drug-interaction number below 2.8?L have a low risk of interacting with substrates which exhibit intestinal first-pass metabolism and those with a drug-interaction number above 9.4?L have a high risk; (2) P-glycoprotein inhibitors with a drug-interaction number below 10.8?L have a low risk of interacting with P-glycoprotein substrates and those with a drug-interaction number above 27.9?L have a high risk; and (3) the drug-interaction number indexes, 2.8?L and 9.4?L for CYP3A4 and 10.8?L and 27.9?L for P-glycoprotein were validated by data from dual CYP3A4/P-glycoprotein substrates.

3. In conclusion, the drug-interaction number is useful for classifying the risk of drug–drug interactions involving the inhibition of intestinal CYP3A4 and P-glycoprotein. This drug-interaction number-based approach is similar to the method that the US Food and Drug Administration (USFDA) recently proposed in the draft guidance for predicting P-glycoprotein-mediated drug–drug interaction.

     

Determination of cidofovir in human plasma after low dose drug administration using high-performance liquid chromatography–tandem mass spectrometry

A sensitive and specific method for the determination of cidofovir (CDV) in human plasma using high-performance liquid chromatography with tandem mass spectrometry (LC–MS/MS) was developed and validated. Plasma samples were processed by a solid phase extraction (SPE) procedure using Varian^® SAX extraction cartridges prior to chromatography. The internal standard was ¹³C5-Folic acid (¹³C5-FA). Chromatography was performed using a Luna C8(2) analytical column, 5 μm, 150 mm × 3.0 mm, using an isocratic elution with a mobile phase consisting of 43% methanol in water containing 12 mM ammonium acetate, at a flow rate of 0.3 mL/min. The retention times of CDV and ¹³C5-FA were 2.1 min and 1.9 min, respectively, with a total run time of 5 min. The analytes were detected by a Micromass Quattro Micro triple quadrupole mass spectrometer in positive electron spray ionization (ESI) mode using multiple reaction monitoring (MRM). The extracted ions monitored following MRM transitions were m/z 280.0 → 262.1 for CDV and m/z 447.0 → 294.8 for ¹³C5-FA (IS). The assay was linear over the range 20–1000 ng/mL. Accuracy (101.6–105.7%), intra-assay precision (4.1–5.4%), and inter-assay precision (5.6–6.8%) were within FDA limits. No significant variation in the concentration of CDV was observed with different sample storage conditions. This method is simple, adaptable to routine application, and allows easy and accurate measurement of CDV in human plasma.     

Clinical disposition,metabolism and in vitro drug–drug interaction properties of omadacycline

1.?Absorption, distribution, metabolism, transport and elimination properties of omadacycline, an aminomethylcycline antibiotic, were investigated in vitro and in a study in healthy male subjects.

2.?Omadacycline was metabolically stable in human liver microsomes and hepatocytes and did not inhibit or induce any of the nine cytochrome P450 or five transporters tested. Omadacycline was a substrate of P-glycoprotein, but not of the other transporters.

3.?Omadacycline metabolic stability was confirmed in six healthy male subjects who received a single 300?mg oral dose of [¹⁴C]-omadacycline (36.6 μCi). Absorption was rapid with peak radioactivity (～610 ngEq/mL) between 1–4?h in plasma or blood. The AUC_last of plasma radioactivity (only quantifiable to 8?h due to low radioactivity) was 3096 ngEq?h/mL and apparent terminal half-life was 11.1?h. Unchanged omadacycline reached peak plasma concentrations (～563?ng/mL) between 1–4?h. Apparent plasma half-life was 17.6?h with biphasic elimination. Plasma exposure (AUC_inf) averaged 9418?ng?h/mL, with high clearance (CL/F, 32.8?L/h) and volume of distribution (Vz/F 828?L). No plasma metabolites were observed.

4.?Radioactivity recovery of the administered dose in excreta was complete (>95%); renal and fecal elimination were 14.4% and 81.1%, respectively. No metabolites were observed in urine or feces, only the omadacycline C4-epimer.     

In vitro inhibition of UGT1A3, UGT1A4 by ursolic acid and oleanolic acid and drug–drug interaction risk prediction

1.?Ursolic acid (UA) and oleanolic acid (OA) may have important activity relevant to health and disease prevention. Thus, we studied the activity of UA and OA on UDP-glucuronosyltransferases (UGTs) and used trifluoperazine as a probe substrate to test UGT1A4 activity. Recombinant UGT-catalyzed 4-methylumbelliferone (4-MU) glucuronidation was used as a probe reaction for other UGT isoforms.

2.?UA and OA inhibited UGT1A3 and UGT1A4 activity but did not inhibit other tested UGT isoforms.

3.?UA-mediated inhibition of UGT1A3 catalyzed 4-MU-β-d-glucuronidation was via competitive inhibition (IC₅₀ 0.391?±?0.013?μM; K_i 0.185?±?0.015?μM). UA also competitively inhibited UGT1A4-mediated trifluoperazine-N-glucuronidation (IC₅₀ 2.651?±?0.201?μM; K_i 1.334?±?0.146?μM).

4.?OA offered mixed inhibition of UGT1A3-mediated 4-MU-β-d-glucuronidation (IC₅₀ 0.336?±?0.013?μM; K_i 0.176?±?0.007?μM) and competitively inhibited UGT1A4-mediated trifluoperazine-N-glucuronidation (IC₅₀ 5.468?±?0.697?μM; K_i 6.298?±?0.891?μM).

5.?Co-administering OA or UA with drugs or products that are substrates of UGT1A3 or UGT1A4 may produce drug-mediated side effects.     

Population pharmacokinetic modelling of S-warfarin to evaluate the design of drug–drug interaction studies for CYP2C9

This study is to assess pharmacokinetic (PK) sampling time schedules and trial size requirements of drug–drug interaction (DDI) studies for CYP2C9, based on S-warfarin population PK models. S-warfarin plasma concentrations from eight DDI studies were utilized to develop S-warfarin population PK models. Optimal PK sampling times were obtained that minimized mean squared error of geometric mean of the area under the concentration–time curve (AUC_0−∞). The powers and type I error rates of testing the equivalences of the geometric means of AUC_0−∞ only and AUC_0−∞ and maximum concentration (C _max), jointly, were assessed via simulation for two-by-two cross-over designs. The results were compared to those from three bioequivalence sample size calculation methods. Two-compartment population PK models with first order absorption were established for non-Asian and Asian subjects. The optimal PK sampling times of size 17 per individual per period were found to be 0.0, 0.5, 1.0, 2.0, 4.0, 6.0, 10.0, 12.0, 16.0, 24.0, 36.0, 48.0, 60.0, 72.0, 96.0, 120.0, 144.0 h post a single oral dose of 25 mg warfarin. For non-Asian subjects, the minimum numbers of subjects required per trial with the optimal PK sampling schedule to achieve 80% power and 5% type I error rate, ranged from 6 to 19 for the equivalence of AUC_0−∞ and C _max jointly. It has been demonstrated that appropriately selected PK sampling time points can greatly increase the corresponding power of the study without increasing the number of subjects, especially when the true ratio is near the default bioequivalence boundary (0.8–1.25).     

In vitro assessment of the roles of drug transporters in the disposition and drug–drug interaction potential of olaparib

1.?In vitro assessments were conducted to examine interactions between olaparib (a potent oral inhibitor of poly[ADP-ribose] polymerase) and drug transporters.

2.?Olaparib showed inhibition of the hepatic drug uptake transporters OATP1B1 (IC₅₀ values of 20.3?μM and 27.1?μM) and OCT1 (IC₅₀ 37.9?μM), but limited inhibition of OATP1B3 (25% at 100?μM); inhibition of the renal uptake transporters OCT2 (IC₅₀ 19.9?μM) and OAT3 (IC₅₀ 18.4?μM), but limited inhibition of OAT1 (13.5% at 100?μM); inhibition of the renal efflux transporters MATE1 and MATE2K (IC₅₀s 5.50?μM and 47.1?μM, respectively); inhibition of the efflux transporter MDR1 (IC₅₀ 76.0?μM), but limited inhibition of BCRP (47% at 100?μM) and no inhibition of MRP2. At clinically relevant exposures, olaparib has the potential to cause pharmacokinetic interactions via inhibition of OCT1, OCT2, OATP1B1, OAT3, MATE1 and MATE2K in the liver and kidney, as well as MDR1 in the liver and GI tract. Olaparib was found to be a substrate of MDR1 but not of several other transporters.

3.?Our assessments indicate that olaparib is a substrate of MDR1 and may cause clinically meaningful inhibition of MDR1, OCT1, OCT2, OATP1B1, OAT3, MATE1 and MATE2K.     

Time-dependent inhibition (TDI) of CYP3A4 and CYP2C9 by noscapine potentially explains clinical noscapine–warfarin interaction

AIMS

To investigate the inhibition potential and kinetic information of noscapine to seven CYP isoforms and extrapolate in vivo noscapine-warfarin interaction magnitude from in vitro data.

METHODS

The activities of seven CYP isoforms (CYP3A4, CYP1A2, CYP2A6, CYP2E1, CYP2D6, CYP2C9, CYP2C8) in human liver microsomes were investigated following co- or preincubation with noscapine. A two-step incubation method was used to examine in vitro time-dependent inhibition (TDI) of noscapine. Reversible and TDI prediction equations were employed to extrapolate in vivo noscapine–warfarin interaction magnitude from in vitro data.

RESULTS

Among seven CYP isoforms tested, the activities of CYP3A4 and CYP2C9 were strongly inhibited with an IC₅₀ of 10.8 ± 2.5 µm and 13.3 ± 1.2 µm. Kinetic analysis showed that inhibition of CYP2C9 by noscapine was best fit to a noncompetitive type with K_i value of 8.8 µm, while inhibition of CYP3A4 by noscapine was best fit to a competitive manner with K_i value of 5.2 µm. Noscapine also exhibited TDI to CYP3A4 and CYP2C9. The inactivation parameters (K_I and k_inact) were calculated to be 9.3 µm and 0.06 min⁻¹ for CYP3A4 and 8.9 µm and 0.014 min⁻¹ for CYP2C9, respectively. The AUC of (S)-warfarin and (R)-warfarin was predicted to increase 1.5% and 1.1% using C_max or 0.5% and 0.4% using unbound C_max with reversible inhibition prediction equation, while the AUC of (S)-warfarin and (R)-warfarin was estimated to increase by 110.9% and 48.9% using C_max or 41.8% and 32.7% using unbound C_max with TDI prediction equation.

CONCLUSIONS

TDI of CYP3A4 and CYP2C9 by noscapine potentially explains clinical noscapine–warfarin interaction.     

Evaluation of community pharmacists’ knowledge about drug–drug interaction in Central Saudi Arabia

IntroductionAlthough all implemented and ongoing initiatives, drug-drug interactions (DDIs) are still a global problem. Most published studies about DDIs in Saudi Arabia are carried out in hospital settings. In addition, assessing the knowledge of drug interactions in Saudi Arabia is limited. The aim of our study is to evaluate the knowledge of potential common drug-drug interactions among community pharmacists particularly in Saudi Arabia.MethodologyA crosses-sectional study utilizing a self- administered questionnaire was conducted among community pharmacy in Riyadh city Saudi Arabia. DDIs' knowledge was assessed by 26 drug pairs. Community pharmacists were asked to select the DDIs as “contraindication”, “may be used together with monitoring”, “no interaction” and “not sure”.ResultsA total of 283 of community pharmacists completed the survey with response rate of 80.9%. Among the 26 drug pairs only 5 of them were identified correctly by most of the participants. To add more 3 out of the 5 pairs had a cutoff of less than 10% between the correct and wrong answer, meaning there still a majority that couldn't identify the correct answer. All the 26 pairs had a statistically significant difference between the correct and incorrect answer.ConclusionThe results of this study showed that knowledge of community pharmacists about DDIs was inadequate. Community pharmacist should have specific courses in drug interactions to cover the most possible interactions that can be seen in this setting.