Pharmacokinetic Drug-drug Interactions Research Articles

Risk of Enzyme- and Transporter-Mediated Drug Interactions With Drugs Approved by the US Food and Drug Administration in 2022: A Detailed Analysis of In Vitro and Clinical Data Available in New Drug Application Reviews

PurposeThis analysis aimed to provide mechanistic understanding and clinical relevance of pharmacokinetic drug-drug interactions (DDIs) associated with drugs approved by the Food and Drug Administration in 2022. MethodsDrug metabolism, transport, and DDI data available in New Drug Applications (NDAs) of small molecular drugs approved (n = 22) was analyzed. The mechanism and clinical magnitude of these interactions were characterized based on in vitro, in silico, and clinical data. FindingsAs victims, 10 drugs were identified as clinical substrates. Of these, 7 drugs were substrates of CYP3A, including the sensitive substrates daridorexant and mitapivat. As perpetrators, 3 drugs (adagrasib, lenacapavir, and vonoprazan) were clinical inhibitors of CYP enzymes, and 2 drugs (mavacamten and mitapivat) showed induction. Regarding transporter data, abrocitinib and deucravacitinib were found to be substrates of OAT3 and P-gp/BCRP, respectively, and 4 drugs (abrocitinib, adagrasib, lenacapavir, and oteseconazole) were found to inhibit P-gp and/or BCRP. As expected, all clinical DDIs with AUC changes ≥ 2-fold triggered label recommendations. Over half of DDIs with an AUC change < 2 also had label recommendations, pertaining most often to the concomitant use of drugs with a narrow therapeutic index. Overall, CYP3A played a major role in the drug disposition of the drugs approved in 2022, mediating all strong drug interactions. ImplicationsThe mechanistic information obtained from studying these new therapeutics with marker compounds can be extrapolated to common concomitant medications sharing the same pharmacokinetic properties, enhancing the safe and effective administration of these products in situations of polytherapy.

Zibotentan Can Be Co-administered with Contraceptives Containing Ethinyl Estradiol and Levonorgestrel: A Pharmacokinetic Drug-Drug Interaction Study.

The endothelin A receptor antagonist zibotentan, combined with the sodium-glucose co-transporter-2 inhibitor dapagliflozin, is being investigated for the treatment of chronic kidney disease with high proteinuria. To allow women of childbearing potential access to this treatment, highly effective contraception is required and drug interactions compromising contraception reliability must be avoided. This study investigated the risk of pharmacokinetic (PK) interaction between zibotentan and the contraceptives ethinyl estradiol and levonorgestrel. A single-sequence, within-participant comparison study was conducted in 24 healthy women of non-childbearing potential, comparing the PK of ethinyl estradiol/levonorgestrel alone and with zibotentan. Single oral doses of 0.06 mg ethinyl estradiol/0.3 mg levonorgestrel were administered on Days 1 and 15; zibotentan 10 mg was dosed orally, once-daily through Days 6-19. PK profiles were determined and ethinyl estradiol/levonorgestrel PK was compared between Day 1 and 15 based on geometric least-squares mean ratios of PK parameters, including maximum observed concentration (Cmax) and area under the plasma concentration-time curve from zero to infinity (AUCinf). Co-administration with zibotentan did not affect ethinyl estradiol PK (geometric mean ratio [90% confidence interval] Cmax 1.05 [0.99-1.11], AUCinf 1.00 [0.96-1.05]), while a weak interaction (increased exposure) was observed for levonorgestrel (Cmax 1.12 [1.02-1.23], AUCinf 1.30 [1.21-1.39]), which was regarded as without clinical relevance. Plasma exposure of ethinyl estradiol/levonorgestrel was not reduced by multiple-dose zibotentan. In conclusion, contraception containing ethinyl estradiol/levonorgestrel is regarded possible under zibotentan-containing treatments. This expands choices for women of childbearing potential, supporting diversity in the ZENITH High Proteinuria trial.

Enhancing the Efficacy and Safety of Methotrexate Treatment: A Focus on Drug Interactions (Review)

INTRODUCTION. Methotrexate (MTX) is the main disease-modifying antirheumatic drug (DMARD) and the gold standard for the safety and efficacy evaluation of biologicals and targeted small molecules. However, its narrow therapeutic range, interpatient variability in pharmacokinetics and pharmacodynamics, and potential clinically relevant drug–drug interactions (DDIs) may lead to treatment failure and increase the risk of adverse drug reactions (ADRs).AIM. The study aimed to describe the main clinically significant DDIs associated with MTX used in rheumatic disease therapy and determine possible approaches to addressing this issue based on a literature review.DISCUSSION. MTX is characterised by pharmacokinetic DDIs during absorption, cell penetration, and elimination. Some non-steroidal anti-inflammatory drugs (NSAIDs), theophylline, sulfasalazine, antibacterial agents, and proton pump inhibitors (PPIs) affect MTX elimination and therapeutic effects. The main ADRs associated with MTX include haematotoxicity, hepatotoxicity, lung tissue damage (interstitial pneumonitis and pulmonary fibrosis), and renal dysfunction. The severity of these ADRs depends on the dose, comorbidities, and concomitant therapy. The toxicity of MTX may be increased by the concomitant administration of medicinal products that exhibit haematotoxicity and affect renal function (impair the elimination of medicines). When co-administering MTX and medicines having clinically significant DDIs described in the literature, healthcare providers should consider the risk factors for each individual patient. The most significant risk factors include moderate to severe renal and hepatic impairment, older age, polypharmacy, and hypoalbuminemia.CONCLUSIONS. This article describes potential clinically significant interactions between MTX and certain NSAIDs, antibacterial agents, and PPIs that depend on individual patient characteristics and may increase the toxicity or decrease the effectiveness of MTX. MTX deprescribing, short-term withdrawal, and dosing optimisation may be considered as approaches to DDI risk mitigation.

Discovering clinical drug-drug interactions with known pharmacokinetics mechanisms using spontaneous reporting systems and electronic health records

ObjectiveAlthough the mechanisms behind pharmacokinetic (PK) drug-drug interactions (DDIs) are well-documented, bridging the gap between this knowledge and clinical evidence of DDIs, especially for serious adverse drug reactions (SADRs), remains challenging. While leveraging the FDA Adverse Event Reporting System (FAERS) database along with disproportionality analysis tends to detect a vast number of DDI signals, this abundance complicates further investigation, such as validation through clinical trials. Our study proposed a framework to efficiently prioritize these signals and assessed their reliability using multi-source Electronic Health Records (EHR) to identify top candidates for further investigation. MethodsWe analyzed FAERS data spanning from January 2004 to March 2023, employing four established disproportionality methods: Proportional Reporting Ratio (PRR), Reporting Odds Ratio (ROR), Multi-item Gamma Poisson Shrinker (MGPS), and Bayesian Confidence Propagating Neural Network (BCPNN). Building upon these models, we developed four ranking models to prioritize DDI-SADR signals and cross-referenced signals with DrugBank. To validate the top-ranked signals, we employed longitudinal EHRs from Vanderbilt University Medical Center and the All of Us research program. The performance of each model was assessed by counting how many of the top-ranked signals were confirmed by EHRs and calculating the average ranking of these confirmed signals. ResultsOut of 189 DDI-SADR signals identified by all four disproportionality methods, only two were documented in the DrugBank database. By prioritizing the top 20 signals as determined by each of the four disproportionality methods and our four ranking models, 58 unique DDI-SADR signals were selected for EHR validations. Of these, five signals were confirmed. The ranking model, which integrated the MGPS and BCPNN, demonstrated superior performance by assigning the highest priority to those five EHR-confirmed signals. ConclusionThe fusion of disproportionality analysis with ranking models, validated through multi-source EHRs, presents a groundbreaking approach to pharmacovigilance. Our study's confirmation of five significant DDI-SADRs, previously unrecorded in the DrugBank database, highlights the essential role of advanced data analysis techniques in identifying ADRs.

Risk of pharmacokinetic drug-drug interactions with novel drugs approved by the US FDA in 2022: a detailed review of DDI data from NDA documentation

Risk of pharmacokinetic drug-drug interactions with novel drugs approved by the US FDA in 2022: a detailed review of DDI data from NDA documentation

Oral Pharmacokinetic Drug-drug Interactions between Amifampridine and Acetaminophen in Rats

Amifampridine, the first-line medication for Lambert-Eaton myasthenic syndrome (LEMS), is extensively metabolized by N-acetyltransferase 2 (NAT2). Drug-drug interactions (DDIs) can occur when co-administered with a NAT2 inhibitor and amifampridine. Acetaminophen is a widely used analgesic for mild to moderate pain, which is also known as a NAT2 inhibitor. In this work, we studied the effects of acetaminophen on the amifampridine pharmacokinetics in rats. Both acetaminophen (300 mg/kg) and amifampridine (2 mg/kg) were administered orally. In acetaminophen-treated rats, the systemic exposure to amifampridine significantly increased, and the ratio of the area under the plasma concentration-time curve for 3-N-acetylamifampridine to amifampridine (AUCm/AUCp) decreased markedly, which is likely due to the inhibition of NAT2 by acetaminophen. Also, the urinary amount excreted was increased in the acetaminophen-treated group, but the renal clearance remained unchanged. This oral pharmacokinetic drug-drug interaction study showed that orally administered acetaminophen significantly inhibits the NAT2-based metabolism of amifampridine and may cause meaningful DDIs.

The Role of CYPs and Transporters in the Biotransformation and Transport of the Anti-hepatitis C Antiviral Agents Asunaprevir, Daclatasvir, and Beclabuvir: Impact of Liver Disease, Race and Drug-drug Interactions on Safety and Efficacy.

Asunaprevir, daclatasvir, and beclabuvir are direct-acting antiviral agents used in the treatment of patients infected with hepatitis C genotype 1b. This article reviews the biotransformation and disposition of these drugs in relation to the safety and efficacy of therapy. CYP3A4 and 3A5 catalyze the oxidative biotransformation of the drugs, while P-glycoprotein mediates their efflux from tissues. Asunaprevir is also a substrate for the influx transporters OATP1B1 and OATP2B1 and the efflux transporter MRP2, while beclabuvir is also a substrate for the efflux transporter BCRP. Liver disease decreases the expression of CYPs and transporters that mediate drug metabolism and disposition. Serum asunaprevir concentrations, but not those of daclatasvir or beclabuvir, are increased in patients with severe liver disease, which may produce toxicity. Pharmacogenomic variation in CYPs and transporters also has the potential to disrupt therapy with asunaprevir, daclatasvir and beclabuvir; some variants are more prevalent in certain racial groups. Pharmacokinetic drug-drug interactions, especially where asunaprevir, daclatasvir, and beclabuvir are victim drugs, are mediated by coadministered rifampicin, ketoconazole and ritonavir, and are attributable to inhibition and/or induction of CYPs and transporters. Conversely, there is also evidence that asunaprevir, daclatasvir and beclabuvir are perpetrators of drug interactions with coadministered rosuvastatin and dextromethorphan. Together, liver disease, pharmacogenomic variation and drug-drug interactions may disrupt.

A comprehensive review on potential drug-drug interactions of proton pump inhibitors with antidiabetic drugs metformin and DPP-4 inhibitors.

A drug interaction is a condition in which two or more drugs are taken at the same time. Type 2 diabetes mellitusis a significant contributor to polypharmacy. Proton pump inhibitors (PPIs) are often prescribed in combination with metformin or DPP-4 inhibitors (sitagliptin, saxagliptin, linagliptin, and alogliptin) or a combined dose of metformin and DPP-4 inhibitor to treat gastritis in diabetic patients. This review article mainly focused on evaluating the potential drug-drug interactions (DDIs) between PPIs (i.e. esomeprazole, lansoprazole, omeprazole, pantoprazole, and rabeprazole) with metformin and PPIs with DPP-4 inhibitors. The findings demonstrated the existence of pharmacokinetic and pharmacodynamic DDIs between the aforementioned PPIs with metformin and DPP-4 inhibitors, which could impact the biological activities (i.e., hypoglycemia) of these drugs. Moreover, this review suggested that esomeprazole could be the best drug in the PPI group to be prescribed simultaneously with metformin and DPP-4 inhibitors, as most of the antidiabetic drugs of this study did not show any interaction with esomeprazole. The findings of this study also revealed that both antidiabetic drugs and PPIs could have positive interactions as PPIs have the potential to lessen the gastrointestinal side effects of metformin and DPP-4 inhibitors. To achieve the greatest therapeutic impact with the fewest side effects, careful dose control of these drugs is required. So, more extensive research on both human and animal subjects are needed to ascertain the veracity of this hypothesis.

Proposing a framework to quantify the potential impact of pharmacokinetic drug-drug interactions caused by a new drug candidate by using real world data about the target patient population.

Drug development teams must evaluate the risk/benefit profile of new drug candidates that perpetrate drug-drug interactions (DDIs). Real-world data (RWD) can inform this decision. The purpose of this study was to develop a predicted impact score for DDIs perpetrated by three hypothetical drug candidates via CYP3A, CYP2D6, or CYP2C9 in type 2 diabetes mellitus (T2DM), obesity, or migraine. Optum Market Clarity was analyzed to estimate use of CYP3A, CYP2D6, or CYP2C9 substrates classified in the University of Washington Drug Interaction Database as moderate sensitive, sensitive, narrow therapeutic index, or QT prolongation. Scoring was based on prevalence of exposure to victim substrates and characteristics (age, polypharmacy, duration of exposure, and number of prescribers) of those exposed. The study population of 14,163,271 adults included 1,579,054 with T2DM, 3,117,753 with obesity, and 410,436 with migraine. For T2DM, 71.3% used CYP3A substrates, 44.3% used CYP2D6 substrates, and 44.3% used CYP2C9 substrates. For obesity, 57.1% used CYP3A substrates, 34.6% used CYP2D6 substrates, and 31.0% used CYP2C9 substrates. For migraine, 64.1% used CYP3A substrates, 44.0% used CYP2D6 substrates, and 28.9% used CYP2C9 substrates. In our analyses, the predicted DDI impact scores were highest for DDIs involving CYP3A, followed by CYP2D6, and CYP2C9 substrates, and highest for T2DM, followed by migraine, and obesity. Insights from RWD can be used to estimate a predicted DDI impact score for pharmacokinetic DDIs perpetrated by new drug candidates currently in development. This score can inform the risk/benefit profile of new drug candidates in a target patient population.

Human Data on Pharmacokinetic Interactions of Cannabinoids: A Narrative Review.

Concomitant use of cannabinoids with other drugs may result in pharmacokinetic drug-drug interactions, mainly due to the mechanism involving Phase I and Phase II enzymes and/or efflux transporters. Cannabinoids are not only substrates but also inhibitors or inducers of some of these enzymes and/or transporters. This narrative review aims to provide the available information reported in the literature regarding human data on the pharmacokinetic interactions of cannabinoids with other medications. A search on Pubmed/Medline, Google Scholar, and Cochrane Library was performed. Some studies were identified with Google search. Additional articles of interest were obtained through cross-referencing of published literature. All original research papers discussing interactions between cannabinoids, used for medical or recreational/adult-use purposes, and other medications in humans were included. Thirty-two studies with medicinal or recreational/adult-use cannabis were identified (seventeen case reports/series, thirteen clinical trials, and two retrospective analyses). In three of these studies, a bidirectional pharmacokinetic drug-drug interaction was reported. In the rest of the studies, cannabinoids were the perpetrators, as in most of them, concentrations of cannabinoids were not measured. In light of the widespread use of prescribed and non-prescribed cannabinoids with other medications, pharmacokinetic interactions are likely to occur. Physicians should be aware of these potential interactions and closely monitor drug levels and/or responses. The existing literature regarding pharmacokinetic interactions is limited, and for some drugs, studies have relatively small cohorts or are only case reports. Therefore, there is a need for high-quality pharmacological studies on cannabinoid-drug interactions.

Infrequent transition to direct oral anticoagulants in patients with cancer.

Pharmacokinetic drug-drug interactions (DDIs) are challenging aspects of direct oral anticoagulant (DOAC) therapy in patients with cancer. We evaluated the prevalence of potential DOAC/antineoplastic agent DDIs and the one-year cumulative incidence of switching from low-molecular-weight heparin (LMWH) to a DOAC in patients with cancer. Patients with cancer and an indication of LMWH were included from Herlev and Gentofte Hospital, Denmark, in the 2014-2019 period. Follow-up was initiated when the first dose of LMWH was dispensed. Data were obtained from electronic medical records. One-year cumulative incidence of switching from LMWH to DOAC was estimated using the Aalen-Johansen estimator. Potential DDIs were evaluated using a report from the European Heart Rhythm Association (EHRA) and a review by Hellfritzsch et al. RESULTS. A total of 161 patients were included with a median age of 70.8 (interquartile range: 64.2-76.1) years. The one-year cumulative incidence of switching from LMWH to DOAC was 32% (95% confidence intervals: 21-43%) in patients eligible for DOACs. Using the EHRA report, a total of 24% of antineoplastic agents were not identified. This percentage decreased to 8% using data from Hellfritzsch et al. CONCLUSIONS. In patients with cancer, the one-year cumulative incidence of switching from LMWH to DOAC was less-t 35% in patients eligible for DOAC, revealing a potential for improved anticoagulant treatment. Furthermore, contemporary data elaborated on potential DDIs between DOACs/antineoplastic agents. "Helsefonden" (21-B-0350) and the "Karen Elise Jensens Fonden" (29-4-2021) funded the study. Not relevant.

Virtual twins for model-informed precision dosing of clozapine in patients with treatment-resistant schizophrenia.

Model-informed precision dosing using virtual twins (MIPD-VTs) is an emerging strategy to predict target drug concentrations in clinical practice. Using a high virtualization MIPD-VT approach (Simcyp version 21), we predicted the steady-state clozapine concentration and clozapine dosage range to achieve a target concentration of 350 to 600 ng/mL in hospitalized patients with treatment-resistant schizophrenia (N = 11). We confirmed that high virtualization MIPD-VT can reasonably predict clozapine concentrations in individual patients with a coefficient of determination (R2 ) ranging between 0.29 and 0.60. Importantly, our approach predicted the final dosage range to achieve the desired target clozapine concentrations in 73% of patients. In two thirds of patients treated with fluvoxamine augmentation, steady-state clozapine concentrations were overpredicted two to four-fold. This work supports the application of a high virtualization MIPD-VT approach to inform the titration of clozapine doses in clinical practice. However, refinement is required to improve the prediction of pharmacokinetic drug-drug interactions, particularly with fluvoxamine augmentation.

No drug-drug interactions between selective prolyl-tRNA synthetase inhibitor, bersiporocin, and pirfenidone or nintedanib in healthy participants.

Bersiporocin, a potent and selective prolyl-tRNA synthetase inhibitor, is expected to show a synergistic effect with pirfenidone or nintedanib in patients with idiopathic pulmonary fibrosis. To validate the combination therapy of bersiporocin with pirfenidone or nintedanib, a randomized, open-label, two-part, one-sequence, three-period, three-treatment study was designed to evaluate the effect of drug-drug interactions (DDI) regarding their pharmacokinetics, safety, and tolerability in healthy participants. In addition, the pharmacokinetic profiles of the newly formulated, enteric-coated bersiporocin tablet were evaluated after single and multiple administrations. The potential effects of cytochrome P450 2D6 (CYP2D6) genotyping on bersiporocin pharmacokinetics and DDI were also explored. In Part 1, participants were sequentially administered a single dose of pirfenidone 600 mg, a single dose of bersiporocin 150 mg followed by multiple doses, and bersiporocin in combination with pirfenidone. In Part 2, participants were sequentially administered a single dose of nintedanib 150 mg, multiple doses of bersiporocin 150 mg, and bersiporocin in combination with nintedanib. Forty-six participants completed the study. There was no significant pharmacokinetic DDI between bersiporocin, and pirfenidone or nintedanib. All adverse events (AEs) were mild to moderate and did not include serious AEs, suggesting bersiporocin alone or in combination therapy were well-tolerated. The newly formulated bersiporocin 150 mg tablet showed a moderate accumulation index. There was no significant difference in the pharmacokinetic profiles after administration of bersiporocin alone or in combination therapy between CYP2D6 phenotypes. In conclusion, there are no significant DDI regarding the pharmacokinetics, safety, and tolerability of bersiporocin administration with pirfenidone or nintedanib.

Natural Products Inhibition of Cytochrome P450 2B6 Activity and Methadone Metabolism.

Methadone is cleared predominately by hepatic cytochrome P450 (CYP) 2B6-catalyzed metabolism to inactive metabolites. CYP2B6 also catalyzes the metabolism of several other drugs. Methadone and CYP2B6 are susceptible to pharmacokinetic drug-drug interactions. Use of natural products such as herbals and other botanicals is substantial and growing, and concomitant use of prescription medicines and non-prescription herbals is common and may result in interactions, often precipitated by CYP inhibition. Little is known about herbal product effects on CYP2B6 activity, and CYP2B6-catalyzed methadone metabolism. We screened a family of natural product compounds used in traditional medicines, herbal teas, and synthetic analogs of compounds found in plants, including kavalactones, flavokavains, chalcones and gambogic acid, for inhibition of expressed CYP2B6 activity and specifically inhibition of CYP2B6-mediated methadone metabolism. An initial screen evaluated inhibition of CYP2B6-catalyzed 7-ethoxy-4-(trifluoromethyl) coumarin O-deethylation. Hits were further evaluated for inhibition of racemic methadone metabolism, including mechanism of inhibition and kinetic constants. In order of decreasing potency, the most effective inhibitors of methadone metabolism were dihydromethysticin (competitive, K i 0.074 µM), gambogic acid (noncompetitive, K i 6 µM), and 2,2'-dihydroxychalcone (noncompetitive, K i 16 µM). Molecular modeling of CYP2B6-methadone and inhibitor binding showed substrate and inhibitor binding position and orientation and their interactions with CYP2B6 residues. These results show that CYP2B6 and CYP2B6-catalyzed methadone metabolism are inhibited by certain natural products, at concentrations which may be clinically relevant. SIGNIFICANCE STATEMENT: This investigation identified several natural product constituents which inhibit in vitro human recombinant CYP2B6 and CYP2B6-catalyzed N-demethylation of the opioid methadone. The most potent inhibitors (K i) were dihydromethysticin (0.074 µM), gambogic acid (6 µM) and 2,2'-dihydroxychalcone (16 µM). Molecular modeling of ligand interactions with CYP2B6 found that dihydromethysticin and 2,2'-dihydroxychalcone bound at the active site, while gambogic acid interacted with an allosteric site on the CYP2B6 surface. Natural product constituents may inhibit CYP2B6 and methadone metabolism at clinically relevant concentrations.

An Uncertainty-Guided Deep Learning Method Facilitates Rapid Screening of CYP3A4 Inhibitors.

Cytochrome P450 3A4 (CYP3A4), a prominent member of the P450 enzyme superfamily, plays a crucial role in metabolizing various xenobiotics, including over 50% of clinically significant drugs. Evaluating CYP3A4 inhibition before drug approval is essential to avoiding potentially harmful pharmacokinetic drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Despite the development of several CYP inhibitor prediction models, the primary approach for screening CYP inhibitors still relies on experimental methods. This might stem from the limitations of existing models, which only provide deterministic classification outcomes instead of precise inhibition intensity (e.g., IC50) and often suffer from inadequate prediction reliability. To address this challenge, we propose an uncertainty-guided regression model to accurately predict the IC50 values of anti-CYP3A4 activities. First, a comprehensive data set of CYP3A4 inhibitors was compiled, consisting of 27,045 compounds with classification labels, including 4395 compounds with explicit IC50 values. Second, by integrating the predictions of the classification model trained on a larger data set and introducing an evidential uncertainty method to rank prediction confidence, we obtained a high-precision and reliable regression model. Finally, we use the evidential uncertainty values as a trustworthy indicator to perform a virtual screening of an in-house compound set. The in vitro experiment results revealed that this new indicator significantly improved the hit ratio and reduced false positives among the top-ranked compounds. Specifically, among the top 20 compounds ranked with uncertainty, 15 compounds were identified as novel CYP3A4 inhibitors, and three of them exhibited activities less than 1 μM. In summary, our findings highlight the effectiveness of incorporating uncertainty in compound screening, providing a promising strategy for drug discovery and development.

Alrizomadlin (APG-115) Alone or Combined with Azacitidine (AZA) in Patients (pts) with Relapsed or Refractory (R/R) Acute Myeloid Leukemia (AML) or Relapsed or Progressive Higher-Risk Myelodysplastic Syndrome (HR-MDS): Phase 1b Trial Results

*Drs. Yifan Zhai and Jianxiang Wang are co-corresponding authors. Background Pts with R/R AML and HR-MDS failing hypomethylating agents have limited therapeutic options and relatively dismal outcomes with available therapies. Investigational alrizomadlin is a novel, orally active, potent, small-molecule selective inhibitor that destabilizes the p53-MDM2 complex and activates p53-mediated apoptosis in tumor cells and has shown apoptotic activity in AML and MDS xenograft models, alone and combined with AZA. Here, we present safety and efficacy results of this therapy in these pts. Methods This open-label dose escalation and expansion trial included adults with R/R AML or relapsed/progressed HR-MDS (IPSS-R ≥ 4.5). MTD and RP2D of alrizomadlin ± AZA were determined by dose escalation. Alrizomadlin (100/150/200/250 mg) was administered orally on Days (D) 1-7 in 28-day cycles. In the combination dose escalation group, alrizomadlin (100/150/200 mg) + AZA (75 mg/m 2) was administered orally once daily on D 1-7 in 28-day cycles and at the combination RP2D during dose expansion. Responses were assessed per revised International Working Group (IWG) Response Criteria 2003, ELN 2017 classifications for AML, and IWG 2006 for MDS. Extensive pharmacokinetic (PK) analyses were performed. Results As of June 1, 2023, 29 pts were enrolled in China. In the monotherapy group, 21 pts (median [range] age, 65 [32-76] years; 76.2%, R/R AML) had a median (range) of 2 (1-10) prior lines of therapy. In the combination group, 8 pts (median [range] age of 69.5 [20-76] years; 50%, R/R AML) had a median (range) of 2 (1-4) prior lines of therapy. In both groups, common any-grade treatment-related adverse events (TRAEs; ≥ 20%) were hematologic- and gastrointestinal-related toxicities, hypokalemia, and dizziness, and most grade ≥ 3 TRAEs were hematologic toxicities. No grade ≥ 3 gastrointestinal toxicities were reported (Figure 1). One DLT, a pulmonary embolism (PE), was reported among 6 evaluable patients at the alrizomadlin 100 mg + AZA dose level: a 59-year-old pt with MDS had a prior COVID-19 infection and abnormal coagulation function before (and during) study treatment. The study investigator attributed the PE to the pt's COVID-19 infection, age, primary disease, and long-term bed rest. One pt in each arm discontinued treatment because of AEs. In pts with AML, the overall response rate (ORR) was defined as complete remission (CR) + CR with incomplete hematologic recovery (CRi) + partial response (PR) + morphologic leukemia-free state (MLFS). In pts with MDS, ORR was defined as CR + PR + marrow CR (mCR). In the monotherapy group, the ORR and CR/CRi rates among pts with R/R AML were 25% (4/16) and 18.75% (3/16), respectively. Three of 6 pts with MDS that progressed to R/R AML experienced responses, including 2 CRis and 1 MLFS. One of 10 pts with R/R AML treated with venetoclax + HMA experienced a CRi. In the monotherapy cohort, 4 pts with MDS refractory to HMAs were evaluated, of whom 2 experienced an mCR. The monotherapy RP2D was determined as 200 mg. In the combination group, 6 pts had an efficacy evaluation at least once. Among these pts, 3 of 3 with MDS experienced an mCR and 1 of 3 with R/R AML, MLFS. Among 4 pts with prior venetoclax + HMA treatment, 2 with MDS experienced an mCR and 2 with R/R AML showed a half marrow blast reduction at the end of C1 (Table 1). No PK drug-drug interaction between alrizomadlin and AZA was observed. Conclusions Alrizomadlin alone or combined with AZA demonstrated a manageable safety profile and preliminary efficacy in pts with R/R AML and HMA-refractory MDS. An antileukemic effect was observed in both monotherapy and combination settings, including a few pts whose disease failed on prior venetoclax treatment. Evaluation of the alrizomadlin + AZA cohort is ongoing. Internal study (CT.gov) identifiers: APG-115-AC101 (NCT04275518).

A Phase 1, Open-Label, Multicenter, Dose-Escalation Study of Sgr-1505 As Monotherapy in Subjects with Mature B-Cell Malignancies

Background and Significance: MALT1 (Mucosa-associated lymphoid tissue lymphoma translocation protein 1) is a component of the MALT1-BCL10-CARD11 complex downstream from the Bruton Tyrosine Kinase (BTK) on the B-cell receptor signaling pathway. MALT1 is a key mediator of nuclear factor kappa B (NF-κB) signaling, which is the main driver of a subset of B-cell lymphomas. MALT1 is considered a potential therapeutic target for several subtypes of non-Hodgkin B-cell lymphomas and chronic lymphocytic leukemia (CLL), including tumors with acquired BTK inhibitor (BTKi) resistance. Constitutive activation of NF-κB is a molecular hallmark of activated B cell-like diffuse large B cell lymphoma (ABC-DLBCL), and MALT1 may have utility as a treatment option for ABC-DLBCL. Furthermore, a MALT1 inhibitor (JNJ-67856633) showed efficacy in mature B cell malignancies from phase 1 studies (ref 1, 2). SGR-1505 is an oral potent small molecule allosteric inhibitor of MALT1 that inhibits MALT1 enzymatic activity and demonstrates anti-proliferative activity in BTKi-sensitive (OCI-LY10) and BTKi-resistant (OCI-LY3) ABC-DLBCL cell lines. SGR-1505 administered as a single agent and in combination with the approved Bruton's tyrosine kinase (BTK) inhibitor, ibrutinib, demonstrates tumorostatic and regressive antitumor activity in ABC-DLBCL cell line-derived and patient-derived xenograft models. These data suggest that SGR-1505-mediated MALT1 inhibition may expand therapeutic options for patients with selected B-cell lymphomas, supporting further evaluation of SGR-1505 in clinical trials. Study Design and Methods: SGR-1505-101 (NCT05544019) is a phase 1, multicenter trial of SGR-1505 as monotherapy in subjects with mature B-cell malignancies (figure 1). At present, the study is open to accrual at multiple investigative sites in the US with plans to expand to Europe. The primary objective is to evaluate safety and tolerability of SGR-1505 as monotherapy and to identify the maximum tolerated dose (MTD) and/or recommended dose (RD). Secondary objectives are to evaluate the pharmacokinetic (PK) profile, food effect, drug-drug interaction, and preliminary anti-tumor activity of SGR-1505. Key inclusion criteria are: history of mature B-cell malignancy (including aggressive and indolent B-cell lymphomas, Waldenström macroglobulinemia, and CLL); measurable or detectable disease according to the applicable disease-specific classification system (Lugano, iwCLL, WWM6); Eastern Cooperative Oncology Group (ECOG) performance status of ≤ 2. Patients with indolent B-cell lymphomas or CLL must have an indication for treatment and not require immediate cytoreductive therapy. Subjects with symptomatic or active CNS involvement, and other conditions or laboratory findings placing them at increased risk to the use of an investigational drug are excluded. SGR-1505 is initially dose-escalated using an accelerated titration design in cohorts of 1-6 subjects, and at higher dose levels using a conventional 3+3 design.

Deep learning-enabled natural language processing to identify directional pharmacokinetic drug-drug interactions.

During drug development, it is essential to gather information about the change of clinical exposure of a drug (object) due to the pharmacokinetic (PK) drug-drug interactions (DDIs) with another drug (precipitant). While many natural language processing (NLP) methods for DDI have been published, most were designed to evaluate if (and what kind of) DDI relationships exist in the text, without identifying the direction of DDI (object vs. precipitant drug). Here we present a method for the automatic identification of the directionality of a PK DDI from literature or drug labels. We reannotated the Text Analysis Conference (TAC) DDI track 2019 corpus for identifying the direction of a PK DDI and evaluated the performance of a fine-tuned BioBERT model on this task by following the training and validation steps prespecified by TAC. This initial attempt showed the model achieved an F-score of 0.82 in identifying sentences as containing PK DDI and an F-score of 0.97 in identifying object versus precipitant drugs in those sentences. Despite a growing list of NLP methods for DDI extraction, most of them use a common set of corpora to perform general purpose tasks (e.g., classifying a sentence into one of several fixed DDI categories). There is a lack of coordination between the drug development and biomedical informatics method development community to develop corpora and methods to perform specific tasks (e.g., extract clinical exposure changes due to PK DDI). We hope that our effort can encourage such a coordination so that more "fit for purpose" NLP methods could be developed and used to facilitate the drug development process.

Pharmacokinetic and pharmacodynamic drug-drug interaction of Nomilin with atorvastatin in hyperlipidemic mice

Atorvastatin (Atv) is widely used to lower cholesterol levels and treat hyperlipidemia in clinical application. Nomilin (Nom) is a kind of limonoids, which is found and isolated from the citrus herbs of Rutaceae family, which are widely used as patent medicines, functional foods, and nutritional supplements in many countries. In previous studies, Nom has the effect of anti-obesity and curing other metabolic diseases. Nevertheless, in recent years, the drug-drug interaction (DDI) caused by the administration of drugs with synergistic effects have raised worldwide concerns. To investigate the DDI of Nom and Atv in vivo, the pharmacokinetic studies were performed with using C57BL/6 mice. The plasma concentrations of Nom and Atv were measured after oral administration of different drug combinations by a simple and sensitive UHPLC-MS/MS method. The experimental mice were randomly divided into five groups, including control group, model group, administered Nom individually group, administered Atv individually group and co-administered of Nom and Atv group. The lipid levels including total cholesterol (TC), triglycerides (TG), high density lipoproteins-cholesterol (HDL-C), low density lipoproteins-cholesterol (LDL-C) were measured for pharmacodynamic study. The hepatic microsomal Cytochrome P450 (CYP1A2, CYP2E1 and CYP3A11) activities were probed using cocktail assay. The gene and protein expressions of CYP3A11 were detected via qPCR and Western blot method. The results shown that the area under the plasma concentration-time curve (AUC) of Atv in administered Atv individually group was 69.30 ± 15.45 ng/mL × h, while that of combined Nom with Atv group was 42.37 ± 10.15 ng/mL × h (p＜0.05). The degree of reduction in lipid levels of mice treated with co-administration of Atv and Nom was less than that of mice treated with Atv alone. In addition, Nom could cause an increased hepatic microsomal CYP3A11 activity significantly, and induce the gene levels and protein expressions of CYP3A11 elevated in mice livers. In conclusion, Nom could up-regulate CYP3A11 activity, thereby impacting on the pharmacokinetic profile and pharmacodynamic effect of Atv. The findings provide more insight for the use risk of these two drugs to treat hyperlipidemia diseases.

Effect of probenecid on blood levels and renal elimination of furosemide and endogenous compounds in rats: Discovery of putative organic anion transporter biomarkers

Transporter-mediated drug-drug interactions (DDIs) are assessed using probe drugs and in vitro and in vivo models during drug development. The utility of endogenous metabolites as transporter biomarkers is emerging for prediction of DDIs during early phases of clinical trials. Endogenous metabolites such as pyridoxic acid and kynurenic acid have shown potential to predict DDIs mediated by organic anion transporters (OAT1 and OAT3). However, these metabolites have not been assessed in rats as potential transporter biomarkers. We carried out a rat pharmacokinetic DDI study using probenecid and furosemide as OAT inhibitor and substrate, respectively. Probenecid administration led to a 3.8-fold increase in the blood concentrations and a 3-fold decrease in renal clearance of furosemide. High inter-individual and intra-day variability in pyridoxic acid and kynurenic acid, and no or moderate effect of probenecid administration on these metabolites suggest their limited utility for prediction of Oat-mediated DDI in rats. Therefore, rat blood and urine samples were further analysed using untargeted metabolomics. Twenty-one m/z features (out of >8000 detected features) were identified as putative biomarkers of rat Oat1 and Oat3 using a robust biomarker qualification approach. These m/z features belong to metabolic pathways such as fatty acid analogues, peptides, prostaglandin analogues, bile acid derivatives, flavonoids, phytoconstituents, and steroids, and can be used as a panel to decrease variability caused by processes other than Oats. When validated, these putative biomarkers will be useful in predicting DDIs caused by Oats in rats.