Interaction between warfarin and short-term intravenous amiodarone in intensive care unit patients after cardiac surgery

An exploration into CTEPH medications: Combining natural language processing, embedding learning, in vitro models, and real-world evidence for drug repurposing

BACKGROUND

In the modern era, the growth of scientific literature presents a daunting challenge for researchers to keep informed of advancements across multiple disciplines.

OBJECTIVE

We apply natural language processing (NLP) and embedding learning concepts to design PubDigest, a tool that combs PubMed literature, aiming to pinpoint potential drugs that could be repurposed.

METHODS

Using NLP, especially term associations through word embeddings, we explored unrecognized relationships between drugs and diseases. To illustrate the utility of PubDigest, we focused on chronic thromboembolic pulmonary hypertension (CTEPH), a rare disease with an overall limited number of scientific publications.

RESULTS

Our literature analysis identified key clinical features linked to CTEPH by applying term frequency-inverse document frequency (TF-IDF) scoring, a technique measuring a term's significance in a text corpus. This allowed us to map related diseases. One standout was venous thrombosis (VT), which showed strong semantic links with CTEPH. Looking deeper, we discovered potential repurposing candidates for CTEPH through large-scale neural network-based contextualization of literature and predictive modeling on both the CTEPH and the VT literature corpora to find novel, yet unrecognized associations between the two diseases. Alongside the anti-thrombotic agent caplacizumab, benzofuran derivatives were an intriguing find. In particular, the benzofuran derivative amiodarone displayed potential anti-thrombotic properties in the literature. Our in vitro tests confirmed amiodarone's ability to reduce platelet aggregation significantly by 68% (p = 0.02). However, real-world clinical data indicated that CTEPH patients receiving amiodarone treatment faced a significant 15.9% higher mortality risk (p<0.001).

CONCLUSIONS

While NLP offers an innovative approach to interpreting scientific literature, especially for drug repurposing, it is crucial to combine it with complementary methods like in vitro testing and real-world evidence. Our exploration with benzofuran derivatives and CTEPH underscores this point. Thus, blending NLP with hands-on experiments and real-world clinical data can pave the way for faster and safer drug repurposing approaches, especially for rare diseases like CTEPH.

Mechanism-based inactivation of cytochromes P450: implications in drug interactions and pharmacotherapy

Cytochrome P40 (CYP) enzymes dominate the metabolism of numerous endogenous and xenobiotic substances. While it is commonly believed that CYP-catalysed reactions result in the detoxication of foreign substances, these reactions can also yield reactive intermediates that can bind to cellular macromolecules to cause cytotoxicity or irreversibly inactivate CYPs that create them.Mechanism-based inactivation (MBI) produces either irreversible or quasi-irreversible inactivation and is commonly caused by CYP metabolic bioactivation to an electrophilic reactive intermediate. Many drugs that have been known to cause MBI in CYPs have been discovered as perpetrators in drug-drug interactions throughout the last 20-30 years.This review will highlight the key findings from the recent literature about the mechanisms of CYP enzyme inhibition, with a focus on the broad mechanistic elements of MBI for widely used drugs linked to the phenomenon. There will also be a brief discussion of the clinical or pharmacokinetic consequences of CYP inactivation with regard to drug interaction and toxicity risk.Gaining knowledge about the selective inactivation of CYPs by common therapeutic drugs helps with the assessment of factors that affect the systemic clearance of co-administered drugs and improves comprehension of anticipated interactions with other drugs or xenobiotics.

Construction of warfarin population pharmacokinetics and pharmacodynamics model in Han population based on Bayesian method

The purpose of this paper is to study the genetic polymorphisms of related gene loci (CYP2C9*3, VKORC1-1639G > A) based on demographic and clinical factors, and use the maximum a posterior Bayesian method to construct a warfarin individualized dose prediction model in line with the Chinese Han population. Finally, the built model is compared and analyzed with the widely used models at home and abroad. In this study, a total of 5467 INR measurements are collected from 646 eligible subjects in our hospital, and the maximum a posterior Bayesian method is used to construct a warfarin dose prediction that conforms to the Chinese Han population on the basis of the Hamberg model. The model is verified and compared with foreign models. This study finds that body weight and concomitant use of amiodarone have a significant effect on the anticoagulant effect of warfarin. The model can provide an effective basis for individualized and rational dosing of warfarin in Han population more accurately. In the performance of comparison with different warfarin dose prediction models, the new model has the highest prediction accuracy, and the prediction percentage is as high as 72.56%. The dose predicted by the Huang model is the closest to the actual dose of warfarin. The population pharmacokinetics and pharmacodynamics model established in this study can better reflect the distribution characteristics of INR values after warfarin administration in the Han population, and performs better than the models reported in the literature.

Warfarin-Rifampin-Gene (WARIF-G) Interaction: A Retrospective, Genetic, Case-Control Study

Warfarin is extensively metabolized by cytochrome P450 2C9 (CYP2C9). Concomitant use with the potent CYP2C9 inducer, rifampin, requires close monitoring and dosage adjustments. Although, in theory, warfarin dose increase should overcome this interaction, most reported cases over the last 50 years have not responded even to high warfarin doses, but some have responded to modest doses. To investigate the genetic polymorphisms' impact on this unexplained interpatient variability, we performed genotyping of CYP2C9, VKORC1, and CYP4F2 for warfarin and rifampin concomitant receivers from 2016 to 2022 at Hamad Medical Corporation, Doha, Qatar. We identified and included 36 patients: 22 responders and 14 nonresponders. Warfarin-responders were significantly more likely to have one or more warfarin-sensitizing CYP2C9/VKORC1 alleles than nonresponders (odds ratio = 23.2, 95% confidence interval = 3.2-195.6; P = 0.0001). The mean genetic-based pre-interaction calculated dose was significantly lower for responders than for nonresponders (P < 0.001); and was negatively correlated with warfarin sensitivity index (WSI) (r = -0.58; P = 0.0002). The median percentage time in therapeutic range and mean WSI were significantly higher in the warfarin-sensitizing CYP2C9/VKORC1 alleles carriers than noncarriers (P = 0.017 and 0.0004, respectively). Whereas the warfarin-sensitizing CYP2C9/VKORC1 genotypes were associated with modest on-rifampin warfarin dose requirements, the noncarriers would have required more than double these doses to respond. Warfarin-sensitizing CYP2C9/VKORC1 genotypes and low genetic-based warfarin calculated doses were associated with higher warfarin sensitivity and better anticoagulation quality in patients receiving rifampin concomitantly.