Efficacy and safety of nebivolol and valsartan as fixed-dose combination in hypertension: a randomised, multicentre study

AttenSyn: An Attention-Based Deep Graph Neural Network for Anticancer Synergistic Drug Combination Prediction

Identifying synergistic drug combinations is fundamentally important to treat a variety of complex diseases while avoiding severe adverse drug-drug interactions. Although several computational methods have been proposed, they highly rely on handcrafted feature engineering and cannot learn better interactive information between drug pairs, easily resulting in relatively low performance. Recently, deep-learning methods, especially graph neural networks, have been widely developed in this area and demonstrated their ability to address complex biological problems. In this study, we proposed AttenSyn, an attention-based deep graph neural network for accurately predicting synergistic drug combinations. In particular, we adopted a graph neural network module to extract high-latent features based on the molecular graphs only and exploited the attention-based pooling module to learn interactive information between drug pairs to strengthen the representations of drug pairs. Comparative results on the benchmark datasets demonstrated that our AttenSyn performs better than the state-of-the-art methods in the prediction of anticancer synergistic drug combinations. Additionally, to provide good interpretability of our model, we explored and visualized some crucial substructures in drugs through attention mechanisms. Furthermore, we also verified the effectiveness of our proposed AttenSyn on two cell lines by visualizing the features of drug combinations learnt from our model, exhibiting satisfactory generalization ability.

A model-agnostic framework to enhance knowledge graph-based drug combination prediction with drug-drug interaction data and supervised contrastive learning

Combination therapies have brought significant advancements to the treatment of various diseases in the medical field. However, searching for effective drug combinations remains a major challenge due to the vast number of possible combinations. Biomedical knowledge graph (KG)-based methods have shown potential in predicting effective combinations for wide spectrum of diseases, but the lack of credible negative samples has limited the prediction performance of machine learning models. To address this issue, we propose a novel model-agnostic framework that leverages existing drug-drug interaction (DDI) data as a reliable negative dataset and employs supervised contrastive learning (SCL) to transform drug embedding vectors to be more suitable for drug combination prediction. We conducted extensive experiments using various network embedding algorithms, including random walk and graph neural networks, on a biomedical KG. Our framework significantly improved performance metrics compared to the baseline framework. We also provide embedding space visualizations and case studies that demonstrate the effectiveness of our approach. This work highlights the potential of using DDI data and SCL in finding tighter decision boundaries for predicting effective drug combinations.

KGANSynergy: knowledge graph attention network for drug synergy prediction

Combination therapy is widely used to treat complex diseases, particularly in patients who respond poorly to monotherapy. For example, compared with the use of a single drug, drug combinations can reduce drug resistance and improve the efficacy of cancer treatment. Thus, it is vital for researchers and society to help develop effective combination therapies through clinical trials. However, high-throughput synergistic drug combination screening remains challenging and expensive in the large combinational space, where an array of compounds are used. To solve this problem, various computational approaches have been proposed to effectively identify drug combinations by utilizing drug-related biomedical information. In this study, considering the implications of various types of neighbor information of drug entities, we propose a novel end-to-end Knowledge Graph Attention Network to predict drug synergy (KGANSynergy), which utilizes neighbor information of known drugs/cell lines effectively. KGANSynergy uses knowledge graph (KG) hierarchical propagation to find multi-source neighbor nodes for drugs and cell lines. The knowledge graph attention network is designed to distinguish the importance of neighbors in a KG through a multi-attention mechanism and then aggregate the entity's neighbor node information to enrich the entity. Finally, the learned drug and cell line embeddings can be utilized to predict the synergy of drug combinations. Experiments demonstrated that our method outperformed several other competing methods, indicating that our method is effective in identifying drug combinations.

MGAE-DC: Predicting the synergistic effects of drug combinations through multi-channel graph autoencoders

Accurate prediction of synergistic effects of drug combinations can reduce the experimental costs for drug development and facilitate the discovery of novel efficacious combination therapies for clinical studies. The drug combinations with high synergy scores are regarded as synergistic ones, while those with moderate or low synergy scores are additive or antagonistic ones. The existing methods usually exploit the synergy data from the aspect of synergistic drug combinations, paying little attention to the additive or antagonistic ones. Also, they usually do not leverage the common patterns of drug combinations across different cell lines. In this paper, we propose a multi-channel graph autoencoder (MGAE)-based method for predicting the synergistic effects of drug combinations (DC), and shortly denote it as MGAE-DC. A MGAE model is built to learn the drug embeddings by considering not only synergistic combinations but also additive and antagonistic ones as three input channels. The later two channels guide the model to explicitly characterize the features of non-synergistic combinations through an encoder-decoder learning process, and thus the drug embeddings become more discriminative between synergistic and non-synergistic combinations. In addition, an attention mechanism is incorporated to fuse each cell-line's drug embeddings across various cell lines, and a common drug embedding is extracted to capture the invariant patterns by developing a set of cell-line shared decoders. The generalization performance of our model is further improved with the invariant patterns. With the cell-line specific and common drug embeddings, our method is extended to predict the synergy scores of drug combinations by a neural network module. Experiments on four benchmark datasets demonstrate that MGAE-DC consistently outperforms the state-of-the-art methods. In-depth literature survey is conducted to find that many drug combinations predicted by MGAE-DC are supported by previous experimental studies. The source code and data are available at https://github.com/yushenshashen/MGAE-DC.

Blood pressure lowering effects of β-blockers as add-on or combination therapy: A meta-analysis of randomized controlled trials

The authors performed a meta-analysis to assess the efficacy of non-atenolol β-blockers as add-on to monotherapy or as a component of combination antihypertensive therapy in patients with hypertension. The authors searched and identified relevant randomized controlled trials from PubMed until November 2021. Studies comparing blood pressure lowering effects of β-blockers with diuretics, calcium channel blockers (CCBs), angiotensin-converting enzyme inhibitors (ACEIs), or angiotensin receptor blockers (ARBs) were included. The analysis included 20 studies with 5544 participants. β-blockers add-on to monotherapy significantly reduced systolic and diastolic blood pressure as compared with non-β-blocker monotherapy (weighted mean difference in mm Hg [95% confidence interval]: -4.1 [-6.0, -2.2] and -3.7 [-4.6, -2.8], respectively). These results were consistent across the comparisons with diuretics (systolic pressure, -10.2 [-14.2, -6.2]; diastolic pressure, -5.4 [-8.2, -2.6]), CCBs (systolic pressure, -4.1 [-7.1, -1.0]; diastolic pressure, -2.8 [-4.1, -1.5]), and ACEIs/ARBs (systolic pressure, -2.9 [-4.3, -1.5]; diastolic pressure, -4.2 [-5.0, -3.4]). There was no significant difference in blood pressure lowering effects between combinations with and without a β-blocker (systolic pressure, -1.3 mm Hg [-5.8, 3.2]; diastolic pressure, -.3 mm Hg [-2.7, 2.1]). Metoprolol add-on or combination therapy had a significantly greater blood pressure reduction than non-β-blocker therapy (systolic pressure, -3.6 mm Hg [-5.9, -1.3]; diastolic pressure, -2.1 mm Hg [-3.5, -.7]). In conclusion, non-atenolol β-blockers are effective in lowering blood pressure as add-on to monotherapy or as a component of combination antihypertensive therapy. In line with the current hypertension guideline recommendations, β-blockers can and should be used in combination with other antihypertensive drugs.

DSN-DDI: an accurate and generalized framework for drug-drug interaction prediction by dual-view representation learning

Drug-drug interaction (DDI) prediction identifies interactions of drug combinations in which the adverse side effects caused by the physicochemical incompatibility have attracted much attention. Previous studies usually model drug information from single or dual views of the whole drug molecules but ignore the detailed interactions among atoms, which leads to incomplete and noisy information and limits the accuracy of DDI prediction. In this work, we propose a novel dual-view drug representation learning network for DDI prediction ('DSN-DDI'), which employs local and global representation learning modules iteratively and learns drug substructures from the single drug ('intra-view') and the drug pair ('inter-view') simultaneously. Comprehensive evaluations demonstrate that DSN-DDI significantly improved performance on DDI prediction for the existing drugs by achieving a relatively improved accuracy of 13.01% and an over 99% accuracy under the transductive setting. More importantly, DSN-DDI achieves a relatively improved accuracy of 7.07% to unseen drugs and shows the usefulness for real-world DDI applications. Finally, DSN-DDI exhibits good transferability on synergistic drug combination prediction and thus can serve as a generalized framework in the drug discovery field.

Combinatorial approaches for novel cardiovascular drug discovery: a review of the literature

INTRODUCTION

In this article, authors report an inclusive discussion about the combinatorial approach for the treatment of cardiovascular diseases (CVDs) and for counteracting the cardiovascular risk factors. The mentioned strategy was demonstrated to be useful for improving the efficacy of pharmacological treatments and in CVDs showed superior efficacy with respect to the classical monotherapeutic approach.

AREAS COVERED

According to this topic, authors analyzed the combinatorial treatments that are available on the market, highlighting clinical studies that demonstrated the efficacy of combinatorial drug strategies to cure CVDs and related risk factors. Furthermore, the review gives an outlook on the future perspective of this therapeutic option, highlighting novel drug targets and disease models that could help the future cardiovascular drug discovery.

EXPERT OPINION

The use of specifically designed and increasingly rational and effective drug combination therapies can therefore be considered the evolution of polypharmacy in cardiometabolic and CVDs. This approach can allow to intervene on multiple etiopathogenetic mechanisms of the disease or to act simultaneously on different pathologies/risk factors, using the combinations most suitable from a pharmacodynamic, pharmacokinetic, and toxicological perspective, thus finding the most appropriate therapeutic option.

Multidrug representation learning based on pretraining model and molecular graph for drug interaction and combination prediction

MOTIVATION

Approaches for the diagnosis and treatment of diseases often adopt the multidrug therapy method because it can increase the efficacy or reduce the toxic side effects of drugs. Using different drugs simultaneously may trigger unexpected pharmacological effects. Therefore, efficient identification of drug interactions is essential for the treatment of complex diseases. Currently proposed calculation methods are often limited by the collection of redundant drug features, a small amount of labeled data and low model generalization capabilities. Meanwhile, there is also a lack of unique methods for multidrug representation learning, which makes it more difficult to take full advantage of the originally scarce data.

RESULTS

Inspired by graph models and pretraining models, we integrated a large amount of unlabeled drug molecular graph information and target information, then designed a pretraining framework, MGP-DR (Molecular Graph Pretraining for Drug Representation), specifically for drug pair representation learning. The model uses self-supervised learning strategies to mine the contextual information within and between drug molecules to predict drug-drug interactions and drug combinations. The results achieved promising performance across multiple metrics compared with other state-of-the-art methods. Our MGP-DR model can be used to provide a reliable candidate set for the combined use of multiple drugs.

AVAILABILITY AND IMPLEMENTATION

Code of the model, datasets and results can be downloaded from GitHub (https://github.com/LiangYu-Xidian/MGP-DR).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A new approach used in docking study for predicting the combination drug efficacy in EML4-ALK target of NSCLC

Combination drug treatments are usually used in many diseases, including cancers and AIDS. This treatment strategy is known as one of the cornerstone in therapies, which potentially reduces drug toxicity and drug resistance and also enhances therapeutic efficacy. Before using a drug in treatment, several experimental studies are done in vivo and in vitro to ensure the drug's efficacy. In such experimental studies, the drug's efficacy is evaluated with the help of drug dose ratio. In the combination drug experimental studies, the efficacy of the drugs is quantified with the Combination Index (CI) value and then interpreted by various terminologies like synergy, additive, and antagonism. Several computational models have now been invented for the speedy identification of combination drug efficacy. Unfortunately, none of these models have predicted the atomic level interaction of the combination drug with the target protein. This type of intermolecular interaction can be identified with the help of docking software. In the proposed work, we try to identify the intermolecular interaction and efficacy of the combination drug Crzizotinib and Temozolomide in the target of EML4-ALK in NSCLC by in silico study. The result of the study was evaluated with drug properties and Complex Energy (CE) of the docked complex rather than using docking score and binding energy. From this study, we could understand that first, Crizotinib and then after the Temozolomide drug binded on the EML4-ALK protein complex, showed very least CE and also identified that the combination of Crizotinib and Temozolomide drug are more effective in NSCLC.Communicated by Ramaswamy H. Sarma.

Emerging targetome and signalome landscape of gut microbial metabolites

The gut microbiome produces chemically diverse small molecules to interact with the host, conveying signals from the gut to the whole system. The microbial metabolites feature several unique modes of interaction with host targets, which fits well into the balanced and networked fashion of biological regulation. Hence, fully unveiling the targetome of signaling microbial metabolites may offer new insights into host health and disease, expand the repertoire of druggable targets, and enlighten a bioinspired path to drug design and discovery. In this review, we present an updated understanding of how microbial metabolite interaction with host targets finely orchestrates and integrates multiple signals to pathophysiological phenotypes, contributing new insights into organ crosstalk and holistic homeostasis maintenance in biological systems. We discuss strategies and open questions for mining and biomimicking the microbial metabolite-targetome interactions for pharmacological manipulation, which may lead to a new paradigm of drug discovery.

Comparative beneficial effects of nebivolol and nebivolol/valsartan combination against mitochondrial dysfunction in angiotensin II-induced pathology in H9c2 cardiomyoblasts

OBJECTIVES

Considering the complementary nature of signalling mechanisms and the therapeutic effects of nebivolol, a β1-adrenoreceptor antagonist, and valsartan, an angiotensin receptor blocker (ARB), here we aimed to investigate whether nebivolol/valsartan combination would complement the cardioprotective effects of nebivolol on angiotensin II (ANG II)-induced pathology in H9c2 cardiomyoblasts.

METHODS

H9c2 cardiomyoblasts were used to investigate the protective effects of nebivolol and nebivolol and valsartan combination against ANG II-induced pathology. Reactive oxygen species (ROS) generation was determined by 2',7'-dichlorofluorescein diacetate (DCFDA) and MitoSOX Red staining. Real-time PCR and immunoblotting were employed to quantify the changes in mRNA and protein expression levels, respectively.

KEY FINDINGS

Our data revealed that pretreatment with nebivolol and nebivolol/valsartan combination significantly reduced ANG II-induced oxidative stress and mTORC1 signalling. Concurrently, ANG II-induced activation of inflammatory cytokines and fetal gene expressions were significantly suppressed by nebivolol and nebivolol/valsartan combination. Pretreatment with nebivolol and nebivolol/valsartan combination alleviated ANG II-induced impairment of mitochondrial biogenesis by restoring the gene expression levels of PGC-1α, TFAM, NRF-1 and SIRT3. Our data further show that nebivolol and nebivolol/valsartan combination mediated up-regulation in mitochondrial biogenesis is accompanied by decrease in ANG II-stimulated mitochondrial ROS generation as well as increase in expression of mitochondrial fusion genes MFN2 and OPA1, indicative of improved mitochondrial dynamics.

SUMMARY

These findings suggest that both nebivolol and nebivolol/valsartan combination exert protective effects on ANG II-induced mitochondrial dysfunction by alleviating its biogenesis and dynamics. Moreover, addition of valsartan to nebivolol do not produce any additive effects compared with nebivolol alone on ANG II-induced cardiac pathology.

DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations

MOTIVATION

Drug combination therapy has become an increasingly promising method in the treatment of cancer. However, the number of possible drug combinations is so huge that it is hard to screen synergistic drug combinations through wet-lab experiments. Therefore, computational screening has become an important way to prioritize drug combinations. Graph neural network has recently shown remarkable performance in the prediction of compound-protein interactions, but it has not been applied to the screening of drug combinations.

RESULTS

In this paper, we proposed a deep learning model based on graph neural network and attention mechanism to identify drug combinations that can effectively inhibit the viability of specific cancer cells. The feature embeddings of drug molecule structure and gene expression profiles were taken as input to multilayer feedforward neural network to identify the synergistic drug combinations. We compared DeepDDS (Deep Learning for Drug-Drug Synergy prediction) with classical machine learning methods and other deep learning-based methods on benchmark data set, and the leave-one-out experimental results showed that DeepDDS achieved better performance than competitive methods. Also, on an independent test set released by well-known pharmaceutical enterprise AstraZeneca, DeepDDS was superior to competitive methods by more than 16% predictive precision. Furthermore, we explored the interpretability of the graph attention network and found the correlation matrix of atomic features revealed important chemical substructures of drugs. We believed that DeepDDS is an effective tool that prioritized synergistic drug combinations for further wet-lab experiment validation.

AVAILABILITY AND IMPLEMENTATION

Source code and data are available at https://github.com/Sinwang404/DeepDDS/tree/master.

Calcium and Heart Failure: How Did We Get Here and Where Are We Going?

The occurrence and prevalence of heart failure remain high in the United States as well as globally. One person dies every 30 s from heart disease. Recognizing the importance of heart failure, clinicians and scientists have sought better therapeutic strategies and even cures for end-stage heart failure. This exploration has resulted in many failed clinical trials testing novel classes of pharmaceutical drugs and even gene therapy. As a result, along the way, there have been paradigm shifts toward and away from differing therapeutic approaches. The continued prevalence of death from heart failure, however, clearly demonstrates that the heart is not simply a pump and instead forces us to consider the complexity of simplicity in the pathophysiology of heart failure and reinforces the need to discover new therapeutic approaches.

Cocrystal of Apixaban-Quercetin: Improving Solubility and Bioavailability of Drug Combination of Two Poorly Soluble Drugs

Drug combinations have been the hotspot of the pharmaceutical industry, but the promising applications are limited by the unmet solubility and low bioavailability. In this work, novel cocrystals, consisting of two antithrombotic drugs with poor solubility and low bioavailability in vivo, namely, apixaban (Apx) and quercetin (Que), were developed to discover a potential method to improve the poor solubility and internal absorption of the drug combination. Compared with Apx, the dissolution behavior of Apx–Que (1:1) and Apx–Que–2ACN (1:1:2) was enhanced significantly, while the physical mixture of the chemicals failed to exhibit the advantages. The dissolution improvements of Apx–Que–2ACN could be explained by the fact that the solid dispersion-like structure and column-shaped cage of Que accelerated the access of the solvent to the inner layer of Apx. The fracture of the hydrogen bonds of Apx, which was the joint of the adjacent Que chains, facilitated the break-up of the structures. Besides, the bioavailability of Apx–Que was increased compared with the physical mixture and Apx, and Apx–Que remained stable in high temperature and illumination conditions. Therefore, a drug–drug cocrystal of two antithrombotic agents with poor solubility was developed, which exhibited greatly improved solubility, bioavailability and superior stability, indicating a novel method to overcome the shortages of drug combination.

Nebivolol for the Treatment of Essential Systemic Arterial Hypertension: A Systematic Review and Meta-Analysis

INTRODUCTION

Cardiovascular diseases are the main cause of mortality worldwide, and systemic arterial hypertension is associated with a large number of these cases. The objective of health professionals and health policies should be searching for the best therapeutics to control this disease. A recent consensus indicated that β-blockers have recently lost their place in initial indications for the treatment of systemic arterial hypertension and are now more indicated for the treatment of hypertension in association with other clinical situations such as angina, heart failure and arrhythmia; however, it is known that this approach was based on studies that evaluated older β-blockers such as atenolol.

OBJECTIVE

The main objective of this study was to perform a systematic review with subsequent meta-analysis on the use of nebivolol for hypertensive disease treatment, comparing it with drugs of the main antihypertensive classes.

METHODS

This systematic review was based on a search of the MEDLINE (via Pubmed), Scopus, Cochrane, International Pharmaceuticals Abstracts (IPA), and Lilacs databases for randomized and double-blind clinical trials. In addition, we also searched for gray literature studies, to 31 July 2015. Next, a cumulative meta-analysis was performed, with studies being added in a sequential manner, evaluating their impact on the combined effect. For this project, we only meta-analyzed direct comparisons of random effect.

RESULTS

Overall, 981 clinical trials were included in this systematic review. After careful analysis, 34 randomized and double-blind clinical trials were included to investigate the efficacy of nebivolol on systolic (SBP) and diastolic blood pressure (DBP) control and adverse effects. The study population comprised 12,465 patients with systemic arterial hypertension (SAH) aged between 18 and 85 years; 17% of subjects were of Black ethnicity, approximately 55% were men, and almost 10% had diabetes. In SBP management, nebivolol was superior to other β-blockers and diuretics and showed no difference in efficacy when compared with angiotensin receptor blockers or calcium channel blockers. There were insufficient studies on angiotensin-converting enzyme inhibitors for adequate comparison of both SBP and DBP control. For DBP control, nebivolol was more efficient than other β-blockers, angiotensin receptor blockers, diuretics, and calcium channel blockers.

DISCUSSION

Nebivolol is a third-generation β-blocker with additional capabilities to improve blood pressure levels in patients with arterial hypertension, because it acts by additional mechanisms such as endothelium-dependent vasodilation associated with L-arginine and oxide nitric acid, nitric oxide activity on smooth muscle cells, decreasing platelet aggregation, and leukocyte adhesion in the endothelium, decreasing oxidative stress. Although nebivolol has shown good results in controlling hypertension in this study (with few adverse events when compared with placebo treatment) and has an unquestionable benefit in individuals with heart failure (mainly with reduced ejection fraction), there is a lack of studies proving the benefit of this drug for controlling hypertension and reducing clinical outcomes such as cardiovascular (or general) mortality, acute myocardial infarction, or stroke.

CONCLUSIONS

Nebivolol demonstrated at least similar control of blood pressure levels in hypertensive individuals when compared with drugs of the most used classes. In addition, in relation to the control of arterial hypertension, studies with clinical outcomes should be performed to ensure the use of this drug in detriment to others with these well-established results.

Nebivolol/valsartan combination for the treatment of hypertension: a review

Nebivolol (N) is a β₁-adrenoreceptor antagonist that is approved for treatment of hypertension in the USA. Effective treatment of hypertension is becoming an increasingly difficult process that often requires multiple drug combinations to meet target guidelines. This has resulted in the increasing introduction of multidrug single-pill combinations (SPCs) to facilitate cost and compliance issues. Some of the SPCs have added valsartan (V), an angiotensin receptor blocker, which is an increasingly advocated antihypertensive class. Pharmacological profiles of N and V, alone and combined, are well characterized. In 2007, the SPC of N and V, 5 and 80 mg, respectively, was approved by the US FDA for treatment of hypertension. This paper will summarize and update key issues in pharmacology, clinical use and benefit.

LigBuilder V3: A Multi-Target de novo Drug Design Approach

With the rapid development of systems-based pharmacology and poly-pharmacology, method development for rational design of multi-target drugs has becoming urgent. In this paper, we present the first de novo multi-target drug design program LigBuilder V3, which can be used to design ligands to target multiple receptors, multiple binding sites of one receptor, or various conformations of one receptor. LigBuilder V3 is generally applicable in de novo multi-target drug design and optimization, especially for the design of concise ligands for protein targets with large difference in binding sites. To demonstrate the utility of LigBuilder V3, we have used it to design dual-functional inhibitors targeting HIV protease and HIV reverse transcriptase with three different strategy, including multi-target de novo design, multi-target growing, and multi-target linking. The designed compounds were computational validated by MM/GBSA binding free energy estimation as highly potential multi-target inhibitors for both HIV protease and HIV reverse transcriptase. The LigBuilder V3 program can be downloaded at “http://www.pkumdl.cn/ligbuilder3/”.

A Critical Review of Nebivolol and its Fixed-Dose Combinations in the Treatment of Hypertension

β-Adrenergic receptor blockers (β-blockers) are well-known useful and cost-effective drugs for managing hypertensive patients with coronary heart disease, stroke, and heart failure. However, it is often difficult to use β-blockers for patients with asthma or chronic obstructive pulmonary disease (COPD). Moreover, most β-blockers negatively influence glucose or lipid metabolism. Nebivolol is a third-generation lipophilic β-1 receptor-selective blocker with nitric oxide-mediated vasodilatory effects, metabolically neutral and usually well tolerated by patients with asthma or COPD. Nebivolol has significant effects of reduction in central blood pressure and improvements in endothelial dysfunction and arterial stiffness. To summarize the merits and demerits of nebivolol in different clinical situations, we conducted a review using the word 'nebivolol' on Pubmed and Embase, limiting the search to hypertension, clinical trials, and meta-analyses. This review summarizes the clinical studies on nebivolol itself and on the combination of nebivolol with other antihypertensive drugs, such as hydrochlorothiazide, angiotensin-converting enzyme inhibitors or angiotensin-receptor blockers, and amlodipine. Most studies showed the safety and well-tolerated profile of nebivolol and the combination of nebivolol with other antihypertensive drugs, which suggests that new fixed combinations of nebivolol with other antihypertensive drugs would be useful for patients who are unable to tolerate traditional β-blockers.

Network-based prediction of drug combinations

Drug combinations, offering increased therapeutic efficacy and reduced toxicity, play an important role in treating multiple complex diseases. Yet, our ability to identify and validate effective combinations is limited by a combinatorial explosion, driven by both the large number of drug pairs as well as dosage combinations. Here we propose a network-based methodology to identify clinically efficacious drug combinations for specific diseases. By quantifying the network-based relationship between drug targets and disease proteins in the human protein-protein interactome, we show the existence of six distinct classes of drug-drug-disease combinations. Relying on approved drug combinations for hypertension and cancer, we find that only one of the six classes correlates with therapeutic effects: if the targets of the drugs both hit disease module, but target separate neighborhoods. This finding allows us to identify and validate antihypertensive combinations, offering a generic, powerful network methodology to identify efficacious combination therapies in drug development.

Nebivolol/Valsartan: A Novel Antihypertensive Fixed-Dose Combination Tablet

Data Sources: A PubMed (1966 to October 2018) search was conducted using the following keywords: nebivolol, valsartan, and hypertension (HTN). Additional sources were identified by references. Study Selection and Data Extraction: Articles written in English were included if they evaluated the pharmacology, pharmacokinetics, efficacy, safety, or place in therapy of nebivolol/valsartan in human subjects. Data Synthesis: Most patients with HTN require combination therapy; however, β-adrenergic antagonists and AII type 1 receptor blockers have been considered less effective because of overlapping mechanisms of action. A phase III, randomized trial demonstrated that nebivolol/valsartan produced statistically significant blood pressure (BP) lowering as compared with monotherapy with the individual components or placebo. Substudy analyses confirmed this among subgroups and demonstrated that nebivolol/valsartan decreased plasma renin and aldosterone levels. One trial reported continued BP lowering at 52 weeks. Another study showed that nebivolol/valsartan had similar additivity scores as compared with other antihypertensive combinations. Relevance to Patient Care and Clinical Practice: This review discusses drug information, efficacy, and safety of nebivolol/valsartan and discusses its clinical relevance as a novel combination product in managing patients with HTN. Conclusion: Nebivolol/valsartan combination may offer a benefit to patients with an indication for both classes who desire to decrease pill burden. Although BP lowering was statistically significant in comparison to the individual components as monotherapy, the combination does not offer clinically significant benefits that would elevate its place in HTN management.

Rationale for nebivolol/valsartan combination for hypertension: review of preclinical and clinical data

To treat hypertension, combining two or more antihypertensive drugs from different classes is often necessary. β-Blockers and renin–angiotensin–aldosterone system inhibitors, when combined, have been deemed ‘less effective’ based on partially overlapping mechanisms of action and limited evidence. Recently, the single-pill combination (SPC) of nebivolol (Neb) 5 mg – a vasodilatory β1-selective antagonist/β3 agonist – and valsartan 80 mg, an angiotensin II receptor blocker, was US Food and Drug Administration-approved for hypertension. Pharmacological profiles of Neb and valsartan, alone and combined, are well characterized. In addition, a large 8-week randomized trial in stages I–II hypertensive patients (N = 4161) demonstrated greater blood pressure-reducing efficacy for Neb/valsartan SPCs than component monotherapies with comparable tolerability. In a biomarkers substudy (N = 805), Neb/valsartan SPCs prevented valsartan-induced increases in plasma renin, and a greater reduction in plasma aldosterone was observed with the highest SPC dose vs. valsartan 320 mg/day. This review summarizes preclinical and clinical evidence supporting Neb/valsartan as an efficacious and well tolerated combination treatment for hypertension.

Combination of β Adrenergic Receptor Block and Renin-Angiotensin System Inhibition Diminished the Angiotensin II-Induced Vasoconstriction and Increased Bradykinin-Induced Vasodilation in Hypertension

In hypertension, the combination therapy is frequently used to obtain a better therapeutic effect and reduce adverse effects. One effective combination is with inhibitors and β-blockers of renin–angiotensin system. Although the mechanisms of action of each drug are already known, the antihypertensive mechanism is more complex and therefore the combined treatment mechanism is unclear. Specifically, the effect of the treatments of angiotensin-converting enzyme inhibitor or AT₁ receptor antagonist with β-blocker on the angiotensin II and bradykinin reactivity has not been studied. For this reason, we evaluated the interaction between propranolol and captopril or losartan on vascular reactivity to bradykinin and angiotensin II in spontaneously hypertensive rat. We constructed concentration–response curves to angiotensin II and bradykinin after treatment of SHR with propranolol–captopril or propranolol–losartan by using rat aortic rings. While losartan or captopril with propranolol potentiated bradykinin-induced vasodilation effect, the propranolol–losartan interaction decreased the angiotensin II-induced vasoconstriction. In addition, the combinations did not reduce the heart rate significantly. These results suggest that the combined therapy decreased blood pressure to normotensive values and showed less effect for angiotensin II and greater effect for bradykinin than monotherapy which could contribute in the antihypertensive effect.

Additivity of nebivolol/valsartan single-pill combinations versus other single-pill combinations for hypertension

The single‐pill combination (SPC) comprising nebivolol (5 mg), a vasodilatory β₁‐selective antagonist/β₃‐agonist, and valsartan (80 mg), a renin‐angiotensin‐aldosterone system inhibitor, is the only Food and Drug Administration–approved β‐blocker/renin‐angiotensin‐aldosterone system inhibitor SPC for hypertension. Additive effects of four nebivolol/valsartan SPC doses (5 mg/80 mg, 5/160 mg, 10/160 mg, 10/320 mg nebivolol/valsartan) were compared with five Food and Drug Administration–approved non–β‐blocker/renin‐angiotensin‐aldosterone system inhibitor SPCs (aliskiren/hydrochlorothiazide, aliskiren/amlodipine, valsartan/amlodipine, aliskiren/valsartan, and telmisartan/amlodipine). Additivity is the ratio of placebo‐adjusted SPC blood pressure (BP) reduction to the placebo‐adjusted monotherapy component BP reduction sums. A weighted average of comparator scores was calculated and compared vs nebivolol/valsartan. Additivity ratio scores for nebivolol/valsartan SPCs (diastolic BP range: 0.735–0.866; systolic BP range: 0.717–0.822) were similar to the comparator weighted average (diastolic BP: 0.837; systolic BP: 0.825). Among the nebivolol/valsartan SPCs, 5/80 mg had the greatest additivity (diastolic BP: 0.866; systolic BP: 0.822). BP reduction contributions with monotherapy were similar for nebivolol/valsartan 5/80 mg SPC. Additivity scores for nebivolol/valsartan and select non–β‐blocker/renin‐angiotensin‐aldosterone system inhibitor SPCs were comparable.

Asymmetric inner wedge group sequential tests with applications to verifying whether effective drug concentrations are similar in adults and children

Extrapolating from information available on one patient group to support conclusions about another is common in clinical research. For example, the findings of clinical trials, often conducted in highly selective patient cohorts, are routinely extrapolated to wider populations by policy makers. Meanwhile, the results of adult trials may be used to support conclusions about the effects of a medicine in children. For example, if the effective concentration of a drug can be assumed to be similar in adults and children, an appropriate paediatric dosing rule may be found by 'bridging', that is, by matching the adult effective concentration. However, this strategy may result in children receiving an ineffective or hazardous dose if, in fact, effective concentrations differ between adults and children. When there is uncertainty about the equality of effective concentrations, some pharmacokinetic-pharmacodynamic data may be needed in children to verify that differences are small. In this paper, we derive optimal group sequential tests that can be used to verify this assumption efficiently. Asymmetric inner wedge tests are constructed that permit early stopping to accept or reject an assumption of similar effective drug concentrations in adults and children. Asymmetry arises because the consequences of under- and over-dosing may differ. We show how confidence intervals can be obtained on termination of these tests and illustrate the small sample operating characteristics of designs using simulation. Copyright © 2016 John Wiley & Sons, Ltd.

Efficacy of nebivolol-valsartan single-pill combination in obese and nonobese patients with hypertension

Antihypertensive efficacy of single-pill combinations (SPCs) consisting of a β₁ -selective adrenergic blocker with vasodilatory properties via β₃ -agonism (nebivolol) and an angiotensin II receptor blocker (valsartan) was demonstrated in an 8-week phase 3 trial (NCT01508026). In this post hoc analysis, seated blood pressure, heart rate, 24-hour ambulatory blood pressure monitoring, plasma aldosterone, estimated glomerular filtration rate, and safety measures were assessed in obese (body mass index >32 kg/m² ; n=1823) and nonobese (body mass index <27 kg/m² ; n=847) adults with hypertension (stage I or II) treated with nebivolol-valsartan SPCs, nebivolol or valsartan monotherapy, or placebo. At week 8, reductions from baseline in blood pressure and ambulatory blood pressure monitoring were greater with SPCs and most nebivolol and valsartan monotherapy doses vs placebo regardless of obesity status. Aldosterone declined with all active treatments and estimated glomerular filtration rate remained steady. The nebivolol-valsartan 5/80 mg/d SPC was efficacious regardless of degree of obesity.

Combination therapeutics in complex diseases

The biological redundancies in molecular networks of complex diseases limit the efficacy of many single drug therapies. Combination therapeutics, as a common therapeutic method, involve pharmacological intervention using several drugs that interact with multiple targets in the molecular networks of diseases and may achieve better efficacy and/or less toxicity than monotherapy in practice. The development of combination therapeutics is complicated by several critical issues, including identifying multiple targets, targeting strategies and the drug combination. This review summarizes the current achievements in combination therapeutics, with a particular emphasis on the efforts to develop combination therapeutics for complex diseases.

A Single-Center, Open-Label, 3-Way Crossover Trial to Determine the Pharmacokinetic and Pharmacodynamic Interaction Between Nebivolol and Valsartan in Healthy Volunteers at Steady State

Combining different classes of antihypertensives is more effective for reducing blood pressure (BP) than increasing the dose of monotherapies. The aims of this phase I study were to investigate pharmacokinetic and pharmacodynamic interactions between nebivolol, a vasodilatory β1-selective blocker, and valsartan, an angiotensin II receptor blocker, and to assess safety and tolerability of the combination. This was a single-center, randomized, open-label, multiple-dose, 3-way crossover trial in 30 healthy adults aged 18-45 years. Participants were randomized into 1 of 6 treatment sequences (1:1:1:1:1:1) consisting of three 7-day treatment periods followed by a 7-day washout. Once-daily oral treatments comprised nebivolol (20 mg), valsartan (320 mg), and nebivolol-valsartan combination (20/320 mg). Outcomes included AUC0-τ,ss, Cmax,ss, Tmax,ss, changes in BP, pulse rate, plasma angiotensin II, plasma renin activity, 24-hour urinary aldosterone, and adverse events. Steady-state pharmacokinetic interactions were observed but deemed not clinically significant. Systolic and diastolic BP reduction was significantly greater with nebivolol-valsartan combination than with either monotherapy. The mean pulse rate associated with nebivolol and nebivolol-valsartan treatments was consistently lower than that associated with valsartan monotherapy. A sharp increase in mean day 7 plasma renin activity and plasma angiotensin II that occurred in valsartan-treated participants was significantly attenuated with concomitant nebivolol administration. Mean 24-hour urine aldosterone at day 7 was substantially decreased after combined treatment, as compared with either monotherapy. All treatments were safe and well tolerated. In conclusion, nebivolol and valsartan coadministration led to greater reductions in BP compared with either monotherapy; nebivolol and valsartan lower BP through complementary mechanisms.

Neurophysiological assessment of sympathetic cardiovascular activity after loss of postganglionic neurons in the anesthetized rat

The goal of this study was to determine the degree of sympathetic postganglionic neuronal loss required to impair cardiovascular-related sympathetic activity. To produce neuronal loss separate groups of rats were treated daily with guanethidine for either 5days or 11days, followed by a recovery period. Sympathetic activity was measured by renal sympathetic nerve activity (RSNA). Stereology of thoracic (T13) ganglia was performed to determine neuronal loss. Despite loss of more than two thirds of neurons in T13 ganglia in both treated groups no effect on resting blood pressure (BP) or heart rate (HR) was detected. Basal RSNA in rats treated for 5days (0.61±0.10μV∗s) and 11days (0.37±0.08μV∗s) was significantly less than vehicle-treated rats (0.99±0.13μV∗s, p<0.05). Increases in RSNA by baroreceptor unloading were significantly lower in 5-day (1.09±0.19μV∗s) and 11-day treated rats (0.59±0.11μV∗s) compared with vehicle-treated rats (1.82±0.19μV∗s, p<0.05). Increases in RSNA to chemoreceptor stimulation were significantly lower in 5-day treated rats (1.54±0.25μV∗s) compared with vehicle-treated rats (2.69±0.23μV∗s, p<0.05). Increases in RSNA in 11-day treated rats were significantly lower (0.75±0.15μV∗s, p<0.05) compared with both vehicle-treated and 5-day treated rats. A positive correlation of neurons to sympathetic responsiveness but not basal activity was detected. These data suggest that diminished capacity for reflex sympathetic responsiveness rather than basal activity alone must be assessed for complete detection of neurophysiological cardiovascular impairment.

Blood pressure lowering efficacy of beta-1 selective beta blockers for primary hypertension

BACKGROUND

Beta blockers are commonly used to treat hypertension. The blood pressure reading is the primary tool for physicians and patients to assess the efficacy of the treatment. The blood pressure lowering effect of beta-1 selective blockers is not known.

OBJECTIVES

To quantify the dose-related effects of various doses and types of beta-1 selective adrenergic receptor blockers on systolic and diastolic blood pressure versus placebo in people with primary hypertension.

SEARCH METHODS

We searched the Database of Abstracts of Reviews of Effectiveness (DARE) for related reviews.We searched the following databases for primary studies: the Cochrane Hypertension Specialised Register (All years to 15 October 2015), CENTRAL via the Cochrane Register of Studies Online (2015, Issue 10), Ovid MEDLINE (1946 to 15 October 2015), Ovid EMBASE (1974 to 15 October 2015) and ClinicalTrials.gov (all years to 15 October 2015).The Hypertension Group Specialised Register includes controlled trials from searches of CAB Abstracts, CINAHL, Cochrane Central Register of Controlled Trials, EMBASE, Food Science and Technology Abstracts (FSTA), Global Health, LILACS, MEDLINE, ProQuest Dissertations & Theses, PsycINFO, Web of Science and the WHO International Clinical Trials Registry Platform (ICTRP).Electronic databases were searched using a strategy combining the Cochrane Highly Sensitive Search Strategy for identifying randomized trials in MEDLINE: sensitivity-maximizing version (2008 revision) with selected MeSH terms and free text terms. No language restrictions were used. The MEDLINE search strategy was translated into CENTRAL, EMBASE, the Hypertension Group Specialised Register and ClinicalTrials.gov using the appropriate controlled vocabulary as applicable. Full strategies are in Appendix 1.

SELECTION CRITERIA

Randomised, double-blind, placebo-controlled parallel or cross-over trials. Studies had to contain a beta blocker monotherapy arm with fixed dose. People enrolled into the studies had to have primary hypertension at baseline. Duration of studies had to be between 3 weeks to 12 weeks. Drugs in this class of beta blockers are atenolol, betaxolol, bevantolol, bisoprolol, esmolol, metoprolol, nebivolol, pafenolol, practolol.

DATA COLLECTION AND ANALYSIS

Two authors confirmed the inclusion of studies and extracted the data independently. Review Manager (RevMan) 5.3.5 was used to synthesise data.

MAIN RESULTS

We identified 56 RCTs (randomised controlled trials) that examined the blood pressure (BP) lowering efficacy of beta-1 selective blockers (beta-1 blocker) in 7812 primary hypertensive patients. Among the included trials, 26 RCTs were parallel studies and 30 RCTs were cross-over studies, examining eight beta-1 blockers. Overall, the majority of beta-1 blockers studied significantly lowered systolic blood pressure (SBP) and diastolic blood pressure (DBP). In people with mild to moderate hypertension, beta-1 selective blockers lowered BP by an average of -10/-8 mmHg and reduced heart rate by 11 beats per minute. The maximum BP reduction of beta-1 blockers occurred at twice the starting dose. Individual beta-1 blockers did not exhibit a graded dose-response effect on SBP and DBP over the recommended dose range.Most beta-1 blockers tested significantly lowered heart rate. A graded dose-response of beta-1 blockers on heart rate was evident. Higher dose beta-1 blockers lowered heart rate more than lower doses. Individually and overall beta-1 blockers did not affect pulse pressure, which distinguishes them from other classes of drugs.

AUTHORS' CONCLUSIONS

This review provides low quality evidence that in people with mild to moderate hypertension, beta-1 selective blockers lowered BP by an average of -10/-8 mmHg and reduced heart rate by 11 beats per minute as compared to placebo. The effect of beta-1 blockers at peak hours, -12/-9 mmHg, was greater than the reduction at trough hours, -8/-7 mmHg. Beta-1 selective blockers lowered BP by a greater magnitude than dual receptor beta-blockers and partial agonist beta-blockers, lowered BP similarly to nonselective beta-blockers. Beta-1 selective blockers lowered SBP by a similar degree and lowered DBP by a greater degree than diuretics, angiotensin converting enzyme inhibitors and angiotensin receptor blockers. Because DBP is lowered by a similar extent to SBP, beta-1 selective blockers do not reduce pulse pressure.

The comparative efficacy and safety of the angiotensin receptor blockers in the management of hypertension and other cardiovascular diseases

All national guidelines for the management of hypertension recommend angiotensin receptor blockers (ARBs) as an initial or add-on antihypertensive therapy. The eight available ARBs have variable clinical efficacy when used for control of hypertension. Additive blood pressure-lowering effects have been demonstrated when ARBs are combined with thiazide diuretics or dihydropyridine calcium channel blockers, augmenting hypertension control. Furthermore, therapeutic use of ARBs goes beyond their antihypertensive effects, with evidence-based benefits in heart failure and diabetic renal disease particularly among angiotensin-converting enzyme inhibitor-intolerant patients. On the other hand, combining renin-angiotensin system blocking agents, a formerly common practice among medical subspecialists focusing on the management of hypertension, has ceased, as there is not only no evidence of cardiovascular benefit but also modest evidence of harm, particularly with regard to renal dysfunction. ARBs are very well tolerated as monotherapy, as well as in combination with other antihypertensive medications, which improve adherence to therapy and have become a mainstay in the treatment of stage 1 and stage 2 hypertension.

Correlations of plasma renin activity and aldosterone concentration with ambulatory blood pressure responses to nebivolol and valsartan, alone and in combination, in hypertension

After demonstration of the antihypertensive efficacy of the combination of the beta-blocker nebivolol and the angiotensin receptor blocker valsartan in an 8-week, randomized, placebo-controlled trial (N = 4161), we now report the effects of this treatment on the renin-angiotensin-aldosterone system in a substudy (n = 805). Plasma renin activity increased with valsartan (54%-73%) and decreased with nebivolol (51%-65%) and the combination treatment (17%-39%). Plasma aldosterone decreased with individual treatments (valsartan, 11%-22%; nebivolol, 20%-26%), with the largest reduction (35%) observed with maximum combination dose (20 mg nebivolol/320 mg valsartan). Baseline ln(plasma renin activity) correlated with the 8-week reductions in 24-hour systolic and diastolic BP following treatments with the combination (all doses combined, P = .003 and P < .001) and nebivolol (both, P < .001), but not with valsartan. Baseline ln(aldosterone) correlated with 24-hour systolic and diastolic BP reductions following combination treatment only (P < .001 and P = .005). The implications of the renin-angiotensin-aldosterone system effects of this beta blocker-angiotensin receptor blocker combination should be explored further.

A Review of Nebivolol Pharmacology and Clinical Evidence

Nebivolol is a highly selective β1-adrenergic receptor antagonist with a pharmacologic profile that differs from those of other drugs in its class. In addition to cardioselectivity mediated via β1 receptor blockade, nebivolol induces nitric oxide-mediated vasodilation by stimulating endothelial nitric oxide synthase via β3 agonism. This vasodilatory mechanism is distinct from those of other vasodilatory β-blockers (carvedilol, labetalol), which are mediated via α-adrenergic receptor blockade. Nebivolol is approved for the treatment of hypertension in the US, and for hypertension and heart failure in Europe. While β-blockers are not recommended within the current US guidelines as first-line therapy for treatment of essential hypertension, nebivolol has shown comparable efficacy to currently recommended therapies in lowering peripheral blood pressure in adults with hypertension with a very low rate of side effects. Nebivolol also has beneficial effects on central blood pressure compared with other β-blockers. Clinical data also suggest that nebivolol may be useful in patients who have experienced erectile dysfunction while on other β-blockers. Here we review the pharmacological profile of nebivolol, the clinical evidence supporting its use in hypertension as monotherapy, add-on, and combination therapy, and the data demonstrating its positive effects on heart failure and endothelial dysfunction.

Nebivolol and valsartan as a fixed-dose combination for the treatment of hypertension

INTRODUCTION

The fixed-dose combination of nebivolol and valsartan drug has been clinically evaluated and demonstrated to represent a unique combination of nebivolol, a selective β1-adrenoceptor antagonist and a β3-adrenoceptor agonist; β3 receptor activation increases endothelial nitric oxide and produces vasodilation. Valsartan is highly selective angiotensin AT1 receptor blocker and exerts its major pharmacological effect by decreasing angiotensin II-induced vasoconstriction and production of aldosterone. The addition of nebivolol counteracts the effects of increased angiotensin II concentrations resulting from potent AT1 blockade. This review describes a recently completed trial establishing the efficacy of the nebivolol/valsartan combination.

AREAS COVERED

This review provides a literature search of pertinent pharmacological and clinical data that describes the mechanisms of both drugs individually and the results of a clinical trial comparing fixed-dose combinations of nebivolol with valsartan as compared with each drug as monotherapy.

EXPERT OPINION

Fixed-dose combination drugs are intended to improve patient compliance and reduce drug costs, as well as to reduce long-term cardiovascular event rates and block counter-regulatory effects due to monotherapy. The vast majority of hypertensive patients will require at least two medications. We believe that the clinical evidence suggests that the combination of nebivolol with valsartan offers a definite clinical benefit, combining β1-adrenoceptor and angiotensin AT1 receptor blockade with β3 receptor activation and resultant increase in nitric oxide and vasodilation.

Recent advances in the management of resistant hypertension

And suddenly, following the preliminary results of renal denervation and carotid baroreceptor stimulation, a big interest in resistant hypertension rose, and all interventionists, many of them with no previous experience with hypertension, fell in love with hypertension and especially resistant hypertension. In the European Society of Hypertension/International Society of Hypertension (ESH/ISH) 2014 Joint Hypertension meeting in Athens, there were no more than four to five sessions related to resistant hypertension and renal denervation, while in the 2014 EuroPCR meeting there were more than 60 renal denervation sessions! In light of the growing scientific interest in the treatment of this patient group, an update on the treatment available and some concerns regarding the definition and treatment of resistant hypertension is presented.

Clinical utility of fixed-dose combinations in hypertension: evidence for the potential of nebivolol/valsartan

Despite significant advances in pharmacologic approaches to treat hypertension during the last decades, hypertension- and hypertension-related organ damage are still a high health and economic burden because a large proportion of patients with hypertension do not achieve optimal blood pressure control. There is now general agreement that combination therapy with two or more antihypertensive drugs is required for targeted blood pressure accomplishment and reduction of global cardiovascular risk. The goals of combination therapies are to reduce long-term cardiovascular events by targeting different mechanism underlying hypertension and target organ disease, to block the counterregulatory pathways activated by monotherapies, to improve tolerability and decrease the adverse effects of up-titrated single agents, and to increase persistence and adherence with antihypertensive therapy. Multiple clinical trials provide evidence that fixed-dose combinations in a single pill offer several advantages when compared with loose-dose combinations. This review discusses the advances in hypertension control and associated cardiovascular disease as they relate to the prospect of combination therapy targeting a third-generation beta (β) 1-adrenergic receptor (nebivolol) and an angiotensin II receptor blocker (valsartan) in fixed-dose single-pill formulations.