In vivo assessment of potential for UGT-inhibition-based drug-drug interaction between sorafenib and tapentadol

Phar-LSTM: a pharmacological representation-based LSTM network for drug-drug interaction extraction

Pharmacological drug interactions are among the most common causes of medication errors. Many different methods have been proposed to extract drug-drug interactions from the literature to reduce medication errors over the last few years. However, the performance of these methods can be further improved. In this paper, we present a Pharmacological representation-based Long Short-Term Memory (LSTM) network named Phar-LSTM. In this method, a novel embedding strategy is proposed to extract pharmacological representations from the biomedical literature, and the information related to the target drug is considered. Then, an LSTM-based multi-task learning scheme is introduced to extract features from the different but related tasks according to their corresponding pharmacological representations. Finally, the extracted features are fed to the SoftMax classifier of the corresponding task. Experimental results on the DDIExtraction 2011 and DDIExtraction 2013 corpuses show that the performance of Phar-LSTM is competitive compared with other state-of-the-art methods. Our Python implementation and the corresponding data of Phar-LSTM are available by using the DOI 10.5281/zenodo.8249384.

In vivo assessment of the pharmacokinetic interactions between donafenib and dapagliflozin, donafenib and canagliflozin in rats

Donafenib (DONA), a deuterium derivative of sorafenib, is used for advanced hepatocellular carcinoma (HCC). Dapagliflozin (DAPA) and canagliflozin (CANA) are sodium-glucose co-transporter 2 (SGLT2) inhibitors used for T2DM, which is frequently comorbid with HCC. Three drugs are substrates of UGT1A9 isoenzyme. This study aimed to evaluate donafenib-dapagliflozin and donafenib-canagliflozin pharmacokinetic interactions and explore the potential mechanisms. Rats were divided into seven groups (n = 6) that received donafenib (1), dapagliflozin (2), canagliflozin (3), dapagliflozin and donafenib (4), canagliflozin and donafenib (5), donafenib and dapagliflozin (6), donafenib and canagliflozin (7). The concentrations of drugs were determined by an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method. The messenger RNA (mRNA) expressions were measured by quantitative RT-PCR. Multiple doses of dapagliflozin caused donafenib maximum plasma concentration (C_max) to increase 37.01%. Canagliflozin increased donafenib C_max 1.77-fold and the area under the plasma concentration-time curves (AUC_0-t and AUC_inf) 1.39- and 1.41-fold, respectively, while reducing the apparent clearance (CL_z) 28.38%. Multiple doses of donafenib increased dapagliflozin AUC_0-t 1.61-fold, AUC_inf 1.77-fold, whereas its CL_z reduced 40.50%. Furthermore, donafenib caused similar changes in canagliflozin pharmacokinetics. The PCR results demonstrated that dapagliflozin inhibited the mRNA expression of Ugt1a7 in liver and donafenib decreased the expression of Ugt1a7 mRNA in liver and intestine. Increased exposure to these drugs may be due to their metabolism inhibition mediated by Ugt1a7. These pharmacokinetic interactions observed in this study may be of clinical significance, which may help adjust dose properly and avoid toxicity effects in patients with HCC and T2DM.

Development of UPLC-MS/MS Method to Study the Pharmacokinetic Interaction between Sorafenib and Dapagliflozin in Rats

Sorafenib (SOR), an inhibitor of multiple kinases, is a classic targeted drug for advanced hepatocellular carcinoma (HCC) which often coexists with type 2 diabetes mellitus (T2DM). Dapagliflozin (DAPA), a sodium–glucose cotransporter-2 inhibitor (SGLT2i), is widely used in patients with T2DM. Notably, co-administration of SOR with DAPA is common in clinical settings. Uridine diphosphate-glucuronosyltransferase family 1 member A9 (UGT1A9) is involved in the metabolism of SOR and dapagliflozin (DAPA), and SOR is the inhibitor of UGT1A1 and UGT1A9 (in vitro). Therefore, changes in UGT1A9 activity caused by SOR may lead to pharmacokinetic interactions between the two drugs. The objective of the current study was to develop an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for the simultaneous determination of SOR and DAPA in plasma and to evaluate the effect of the co-administration of SOR and DAPA on their individual pharmacokinetic properties and the mechanism involved. The rats were divided into four groups: SOR (100 mg/kg) alone and co-administered with DAPA (1 mg/kg) for seven days, and DAPA (1 mg/kg) alone and co-administered with SOR (100 mg/kg) for seven days. Liquid–liquid extraction (LLE) was performed for plasma sample preparation, and the chromatographic separation was conducted on Waters XSelect HSS T3 column with a gradient elution of 0.1% formic acid and 5 mM ammonium acetate (Phase A) and acetonitrile (Phase B). The levels of Ugt1a7 messenger RNA (mRNA) were determined in rat liver and intestine using quantitative real-time polymerase chain reaction (qRT-PCR). The method was successfully applied to the study of pharmacokinetic interactions. DAPA caused a significant decrease in the maximum plasma concentrations (Cmax) and the area under the plasma concentration–time curves (AUC0–t) of SOR by 41.6% and 50.5%, respectively, while the apparent volume of distribution (Vz/F) and apparent clearance (CLz/F) significantly increased 2.85- and 1.98-fold, respectively. When co-administering DAPA with SOR, the AUC0–t and the elimination half-life (t1/2Z) of DAPA significantly increased 1.66- and 1.80-fold, respectively, whereas the CLz/F significantly decreased by 40%. Results from qRT-PCR showed that, compared with control, seven days of SOR pretreatment decreased Ugt1a7 expression in both liver and intestine tissue. In contrast, seven days of DAPA pretreatment decreased Ugt1a7 expression only in liver tissue. Therefore, pharmacokinetic interactions exist between long-term use of SOR with DAPA, and UGT1A9 may be the targets mediating the interaction. Active surveillance for the treatment outcomes and adverse reactions are required.

Pharmacokinetic Interactions between Canagliflozin and Sorafenib or Lenvatinib in Rats

Hepatocellular carcinoma (HCC) and type 2 diabetes mellitus (T2DM) are common clinical conditions, and T2DM is an independent risk factor for HCC. Sorafenib and lenvatinib, two multi-targeted tyrosine kinase inhibitors, are first-line therapies for advanced HCC, while canagliflozin, a sodium-glucose co-transporter 2 inhibitor, is widely used in the treatment of T2DM. Here, we developed an ultra-performance liquid chromatography-tandem mass spectrometry method for the simultaneous determination of canagliflozin, sorafenib, and lenvatinib, and investigated the pharmacokinetic drug interactions between canagliflozin and sorafenib or lenvatinib in rats. The animals were randomly divided into five groups. Groups I–III were gavage administrated with sorafenib, lenvatinib, and canagliflozin, respectively. Group IV received sorafenib and canagliflozin; while Group V received lenvatinib and canagliflozin. The area under the plasma concentration-time curves (AUC) and maximum plasma concentrations (C_max) of canagliflozin increased by 37.6% and 32.8%, respectively, while the apparent volume of distribution (V_z/F) and apparent clearance (CL_z/F) of canagliflozin significantly decreased (30.6% and 28.6%, respectively) in the presence of sorafenib. Canagliflozin caused a significant increase in AUC and C_max of lenvatinib by 28.9% and 36.2%, respectively, and a significant decrease in V_z/F and CL_z/F of lenvatinib by 52.9% and 22.7%, respectively. In conclusion, drug interactions exist between canagliflozin and sorafenib or lenvatinib, and these findings provide a reference for the use of these drugs in patients with HCC and T2DM.

In vitro effects of opicapone on activity of human UDP-glucuronosyltransferases isoforms

Catechol-O-methyltransferase (COMT) inhibitors are widely used as an add-on treatment to levodopa in adults with Parkinson's disease. It has been evidenced that the second-generation COMT inhibitors entacapone and tolcapone are potent inhibitors on human UDP-glucosyltransferases (UGTs), while the effect of the third-generation COMT inhibitor opicapone on human UGTs activities is unclear. The purpose of this study is to systemically investigate the effects of opicapone on human UGTs activities, and also to assess the potential risk of drug-drug interactions (DDIs) associated with opicapone. Our results indicated that opicapone is a broad-spectrum inhibitor of UGTs. Particularly, opicapone exhibited potent inhibition against UGT1A1, 1A7, 1A8, 1A9, and 1A10, with a range of inhibition constant K_i values of 1.31-10.58 µM. Furthermore, the DDI risk was quantitatively predicted by using the in vitro-in vivo extrapolation (IVIVE). The prediction suggested that co-administration of opicapone at 25 mg/day or 50 mg/day with drugs primarily cleared by hepatic UGT1A9 or intestinal UGT1A1, 1A7, 1A8, 1A9, or 1A10 might result in potential DDI via inhibition of intestinal or hepatic UGTs.

Pharmacokinetic Drug Interaction Study of Sorafenib and Morphine in Rats

A combination of the tyrosine kinase inhibitor—sorafenib—and the opioid analgesic—morphine—can be found in the treatment of cancer patients. Since both are substrates of P-glycoprotein (P-gp), and sorafenib is also an inhibitor of P-gp, their co-administration may affect their pharmacokinetics, and thus the safety and efficacy of cancer therapy. Therefore, the aim of this study was to evaluate the potential pharmacokinetic drug–drug interactions between sorafenib and morphine using an animal model. The rats were divided into three groups that Received: sorafenib and morphine (I_SOR+MF), sorafenib (II_SOR), and morphine (III_MF). Morphine caused a significant increase in maximum plasma concentrations (C_max) and the area under the plasma concentration–time curves (AUC_0–t, and AUC_0–∞) of sorafenib by 108.3 (p = 0.003), 55.9 (p = 0.0115), and 62.7% (p = 0.0115), respectively. Also, the C_max and AUC_0–t of its active metabolite—sorafenib N-oxide—was significantly increased in the presence of morphine (p = 0.0022 and p = 0.0268, respectively). Sorafenib, in turn, caused a significant increase in the C_max of morphine (by 0.5-fold, p = 0.0018). Moreover, in the presence of sorafenib the C_max, AUC_0–t, and AUC_0–∞ of the morphine metabolite M3G increased by 112.62 (p < 0.0001), 46.82 (p = 0.0124), and 46.78% (p = 0.0121), respectively. Observed changes in sorafenib and morphine may be of clinical significance. The increased exposure to both drugs may improve the response to therapy in cancer patients, but on the other hand, increase the risk of adverse effects.

Interaction Between Florfenicol and Doxycycline Involving Cytochrome P450 3A in Goats (Capra hricus)

When two drugs are combined, drug-drug interactions (DDI) often occur. Metabolic DDI usually occur due to inhibition of the metabolism of one drug by the other. This leads to an increase in the plasma concentration of the drug whose metabolism is inhibited. The objective of this research study was to verify the DDI risk of two antibacterial, florfenicol (FF) and doxycycline (DOX) due to metabolism. Because food containing residues of any pharmacologically active substance could potentially constitute a public health hazard, we selected a food producing animal, goat, goat liver microsomes and recombinant metabolic enzymes, for in vivo and in vitro metabolism studies. In vitro experiments showed that CYP3A was the key enzyme subfamily in FF metabolism, DOX slowed down FF metabolism and R440 was possibly the key amino acid in the metabolic interaction between FF and DOX. In vivo studies in the goats showed that DOX inhibited up-regulation of CYP3A24 gene expression produced by FF; in liver and kidney, DOX slightly slowed down FF metabolism. Quantitative prediction of DDI risk suggest that when DOX is used in combination with FF in veterinary medicine, may result in a clinical significant increase of FF plasma and tissue concentrations, resulting a prevalence of harmful tissue residues of medicinal products in the food chain. Through our experimentation, when DOX is used in combination with FF, the withdrawal period of FF in the kidney was extended by 1 day. Otherwise, an appropriate withdrawal period (20 days) of FF was established for FF and DOX combined use to ensure that the animal can be safely slaughtered for food.