Rituximab: How approval history is reflected by a corresponding patent filing strategy

Because drug development is not a static process, a drug’s market authorisation may change over time. In many cases, the number of indications for which a drug is approved increases. Because this facet of drug development also comes at significant costs, a corresponding patent filing strategy is required to protect these investments. The strategy as applied to rituximab, which is approved for a variety of indications, is discussed in this review.     

药物重定位的计算分析方法

全新结构药物的研发存在周期长、耗资大、风险高的问题.通过各种技术预测已有药物的新适应症,即药物重定位,可以缩短药物研发时间、降低研发成本和风险.由于疾病种类和已知药物的数量繁多,完全通过实验筛选已知药物的新用途仍然具有很高的成本.随着组学和药物信息学数据的积累,药物重定位进入到了理性设计和实验筛选相结合的阶段,药物重定位的计算预测已经成为计算生物学和系统生物学的重要研究方向.本文将目前药物重定位计算分析的策略归纳为药物-靶标关系分析、药物-药物关系分析和药物-疾病关系分析,对已报道的技术方法及其成功应用实例进行了综述.     

PREDICT: a method for inferring novel drug indications with application to personalized medicine

Inferring potential drug indications, for either novel or approved drugs, is a key step in drug development. Previous computational methods in this domain have focused on either drug repositioning or matching drug and disease gene expression profiles. Here, we present a novel method for the large‐scale prediction of drug indications (PREDICT) that can handle both approved drugs and novel molecules. Our method is based on the observation that similar drugs are indicated for similar diseases, and utilizes multiple drug–drug and disease–disease similarity measures for the prediction task. On cross‐validation, it obtains high specificity and sensitivity (AUC=0.9) in predicting drug indications, surpassing existing methods. We validate our predictions by their overlap with drug indications that are currently under clinical trials, and by their agreement with tissue‐specific expression information on the drug targets. We further show that disease‐specific genetic signatures can be used to accurately predict drug indications for new diseases (AUC=0.92). This lays the computational foundation for future personalized drug treatments, where gene expression signatures from individual patients would replace the disease‐specific signatures.     

Drug repurposing for SARS-CoV-2 main protease: Molecular docking and molecular dynamics investigations

The current novel corona virus illness (COVID-19) is a developing viral disease that was discovered in 2019. There is currently no viable therapeutic strategy for this illness management. Because traditional medication development and discovery has lagged behind the threat of emerging and re-emerging illnesses like Ebola, MERS-CoV, and, more recently, SARS-CoV-2. Drug developers began to consider drug repurposing (or repositioning) as a viable option to the more traditional drug development method. The goal of drug repurposing is to uncover new uses for an approved or investigational medicine that aren't related to its original use. The main benefits of this strategy are that there is less developmental risk and that it takes less time because the safety and pharmacologic requirements are met. The main protease (Mpro) of corona viruses is one of the well-studied and appealing therapeutic targets. As a result, the current research examines the molecular docking of Mpro (PDB ID: 5R81) conjugated repurposed drugs. 12,432 approved drugs were collected from ChEMBL and drugbank libraries, and docked separately into the receptor grid created on 5R81, using the three phases of molecular docking including high throughput virtual screening (HTVS), standard precision (SP), and extra precision (XP). Based on docking scores and MM-GBSA binding free energy calculation, top three drugs (kanamycin, sulfinalol and carvedilol) were chosen for further analyses for molecular dynamic simulations.     

Approaches to antiviral drug development

At present, only a few drugs have been approved by the FDA for therapy of viral infections in humans. There is a great need for antiviral drugs with increased potency and decreased toxicity, as well as drugs to treat viral diseases for which no drug or vaccine is currently available. Two approaches for development of antiviral drugs are described--an empirical strategy and a rational strategy--with several examples of each. Although many compounds have potent antiviral activity in cell culture, only a small fraction of these will go on to become antiviral drugs for use in humans. At this time, only seven synthetic compounds and alpha interferon have been approved by the FDA for therapy of viral infections in humans. None of these approved drugs are without toxicities, however, and hence there is a great need for antiviral drugs with increased potency and decreased toxicity, as well as for drugs to treat viral diseases for which no drug or vaccine is currently available. Two approaches for the development of antiviral drugs--the empirical and the rational strategies--and their applications and future directions are discussed.     

美国生物制品中孤儿药的研发现状 及对中国孤儿药研发策略的思考

过去30 年, 美国在全球第一部《孤儿药法案》推动和相关政策法规引导下,生物科技飞速发展,尤其在孤儿药研发领域,成果卓著。 对这30 年来美国FDA 批准的生物制品中孤儿药产品作一解析,回顾美国对生物制品中孤儿药的研发策略,介绍孤儿药开发的新型商业 模式,同时反思中国孤儿药研发策略。     

Multiple independent analyses reveal only transcription factors as an enriched functional class associated with microRNAs

Background

The process of drug discovery and development is time-consuming and costly, and the probability of success is low. Therefore, there is rising interest in repositioning existing drugs for new medical indications. When successful, this process reduces the risk of failure and costs associated with de novo drug development. However, in many cases, new indications of existing drugs have been found serendipitously. Thus there is a clear need for establishment of rational methods for drug repositioning.

Results

In this study, we have established a database we call “PharmDB” which integrates data associated with disease indications, drug development, and associated proteins, and known interactions extracted from various established databases. To explore linkages of known drugs to diseases of interest from within PharmDB, we designed the Shared Neighborhood Scoring (SNS) algorithm. And to facilitate exploration of tripartite (Drug-Protein-Disease) network, we developed a graphical data visualization software program called phExplorer, which allows us to browse PharmDB data in an interactive and dynamic manner. We validated this knowledge-based tool kit, by identifying a potential application of a hypertension drug, benzthiazide (TBZT), to induce lung cancer cell death.

Conclusions

By combining PharmDB, an integrated tripartite database, with Shared Neighborhood Scoring (SNS) algorithm, we developed a knowledge platform to rationally identify new indications for known FDA approved drugs, which can be customized to specific projects using manual curation. The data in PharmDB is open access and can be easily explored with phExplorer and accessed via BioMart web service (http://www.i-pharm.org/, http://biomart.i-pharm.org/).     

Drug discovery and development focusing on existing medicines: drug re-profiling strategy

As a new strategy for drug discovery and development, I focus on drug re-profiling as a way to identify new treatments for diseases. In this strategy, the actions of existing medicines, whose safety and pharmacokinetic effects in humans have already been confirmed clinically and approved for use, are examined comprehensively at the molecular level and the results used for the development of new medicines. This strategy is based on the fact that we still do not understand the underlying mechanisms of action of many existing medicines, and as such the cellular responses that give rise to their main effects and side effects are yet to be elucidated. To this extent, identification of the mechanisms underlying the side effects of medicines offers a means for us to develop safer drugs. The results can also be used for developing existing drugs for use as medicines for the treatment of other diseases. Promoting this research strategy could provide breakthroughs in drug discovery and development.     

The transthyretin amyloidoses: from delineating the molecular mechanism of aggregation linked to pathology to a regulatory-agency-approved drug

Transthyretin (TTR) is one of the many proteins that are known to misfold and aggregate (i.e., undergo amyloidogenesis) in vivo. The process of TTR amyloidogenesis causes nervous system and/or heart pathology. While several of these maladies are associated with mutations that destabilize the native TTR quaternary and/or tertiary structure, wild-type TTR amyloidogenesis also leads to the degeneration of postmitotic tissue. Over the past 20 years, much has been learned about the factors that influence the propensity of TTR to aggregate. This biophysical information led to the development of a therapeutic strategy, termed "kinetic stabilization," to prevent TTR amyloidogenesis. This strategy afforded the drug tafamidis which was recently approved by the European Medicines Agency for the treatment of TTR familial amyloid polyneuropathy, the most common familial TTR amyloid disease. Tafamidis is the first and currently the only medication approved to treat TTR familial amyloid polyneuropathy. Here we review the biophysical basis for the kinetic stabilization strategy and the structure-based drug design effort that led to this first-in-class pharmacologic agent.     

生物信息技术加速开发旧药新用途

传统的技术路线研发新药,不仅周期很长而且耗资巨大,开发已获批准药物新的治疗用途,又称为药物重定位,比传统的新药研发具有明显的优势．基于芯片的基因表达谱分析,已常规地广泛用于各种人类疾病的临床研究,提供了在全基因组水平描述疾病状态的特征信号．同时,基因芯片也广泛地用于对比药物处理前后细胞基因表达模式的变化,这也提供了反映药物效应的高质量信号．最近出版的Science Translational Medicine杂志同时发表了一个研究组的两篇论文,为我们展示了如何利用生物信息学手段重新解析和比较全基因组基因表达谱数据,以高效地预测药物的新用途．这两篇论文使用了公共数据库中的100种疾病基因表达谱数据,以及164种药物处理前后细胞基因表达谱数据,通过比较和配对疾病与药物基因表达谱,得到了一些可以逆转疾病异常表达基因的药物,其中证实了一些已知的药物-疾病组合,也预测了一些新的药物-疾病组合．最后通过实验验证了抗溃疡药可用于治疗肺癌,而抗癫痫药可治疗炎症性肠道疾病,进一步证实了他们所采用研究策略的正确性．于是,肺癌和炎性肠道疾病这两种临床上难治的疾病有了新的候选治疗药物,我们也有了一种挖掘已有数据快速发现药物新用途的思路和方法．     

Prediction of drug combinations by integrating molecular and pharmacological data

Combinatorial therapy is a promising strategy for combating complex disorders due to improved efficacy and reduced side effects. However, screening new drug combinations exhaustively is impractical considering all possible combinations between drugs. Here, we present a novel computational approach to predict drug combinations by integrating molecular and pharmacological data. Specifically, drugs are represented by a set of their properties, such as their targets or indications. By integrating several of these features, we show that feature patterns enriched in approved drug combinations are not only predictive for new drug combinations but also provide insights into mechanisms underlying combinatorial therapy. Further analysis confirmed that among our top ranked predictions of effective combinations, 69% are supported by literature, while the others represent novel potential drug combinations. We believe that our proposed approach can help to limit the search space of drug combinations and provide a new way to effectively utilize existing drugs for new purposes.     

A computational approach to analyze the mechanism of action of the kinase inhibitor bafetinib

Prediction of drug action in human cells is a major challenge in biomedical research. Additionally, there is strong interest in finding new applications for approved drugs and identifying potential side effects. We present a computational strategy to predict mechanisms, risks and potential new domains of drug treatment on the basis of target profiles acquired through chemical proteomics. Functional protein-protein interaction networks that share one biological function are constructed and their crosstalk with the drug is scored regarding function disruption. We apply this procedure to the target profile of the second-generation BCR-ABL inhibitor bafetinib which is in development for the treatment of imatinib-resistant chronic myeloid leukemia. Beside the well known effect on apoptosis, we propose potential treatment of lung cancer and IGF1R expressing blast crisis.     

Single-dose azithromycin microsphere formulation: a novel delivery system for antibiotics

Azithromycin extended release (Zmax, Pfizer Inc) is a novel single-dose administration formulation of azithromycin which won FDA approval in June 2005 and is currently approved for the treatment of community acquired pneumonia and acute bacterial sinusitis. Azitromycin is incorporated into sustained-release microspheres which release the drug slowly through 200 microm pores. Because of this sustained release mechanism, most of the drug is released into the lower gastrointestinal tract, reducing gastrointestinal side-effects, and allowing for a higher dose to be administered. The unique pharmacological properties and extremely long half-life of azithromycin make this drug well suited to single-dose administration but gastrointestinal side effects have previously hampered single-dose therapy.     

1- 磷酸鞘氨醇受体调节剂的研发现状

1- 磷酸鞘氨醇（S1P）具有多种生物学功能,S1P 受体（S1PR）调节剂可以用于治疗多种免疫性疾病。芬戈莫德是首个上市的 S1PR 调节剂,用于治疗多发性硬化症（MS）,2015 年销售额达到27 亿美元。药渡网数据显示：目前全球有14 个S1PR 调节剂进入临床, 适应证包括MS、银屑病、类风湿性关节炎和炎症性肠病等。国内目前针对S1PR 靶点的药物有1 个新药奥芬米洛已获批临床,另1 个 新药CBP-307 处于临床在审评阶段。简介S1PR 的生物学功能和S1PR 调节剂在国内外的开发情况,为靶向S1PR 的药物开发提供参考。     

2015 年 9 月美国、欧盟和日本新批准药物概述

2015 年 9 月,美国、欧盟和日本共批准 46 个新药,包括新分子实体、新有效成分、新生物制品、新增适应证及新剂型药物。 本文对全球首次获得批准的新分子实体、新有效成分、新生物制品进行分析,重点介绍这些药物的临床研究结果和研发历史进程。     

Magnetic resonance imaging,pacemakers and implantable cardioverter-defibrillators: current situation and clinical perspective

New developments and expanding indications have resulted in a significant increase in the number of patients with pacemakers and internal cardioverterdefibrillators (ICDs). Because of its unique capabilities, magnetic resonance imaging (MRI) has become one of the most important imaging modalities for evaluation of the central nervous system, tumours, musculoskeletal disorders and some cardiovascular diseases. As a consequence of these developments, an increasing number of patients with implanted devices meet the standard indications for MRI examination. Due to the presence of potential life-threatening risks and interactions, however, pacemakers and ICDs are currently not approved by the Food and Drug Administration (FDA) for use in an MRI scanner. Despite these limitations and restrictions, a limited but still growing number of studies reporting on the effects and safety issues of MRI and implanted devices have been published. Because physicians will be increasingly confronted with the issue of MRI in patients with implanted devices, this overview is given. The effects of MRI on an implanted pacemaker and/or ICDs and vice versa are described and, based on the current literature, a strategy for safe performance of MRI in these patients is proposed. (Neth Heart J 2010;18:31-7.)     

A Synergetic Screening Approach with Companion Effector for Combination Therapy: Application to Retinoblastoma

For many cancers, the lack of potency and the toxicity of current drugs limits the dose achievable in patients and the efficacy of treatment. Among them, retinoblastoma is a rare cancer of the eye for which better chemotherapeutic options are needed. Combination therapy is a compelling approach to enhance the efficacy of current treatment, however clinical trials to test rationally designed combinations of approved drugs are slow and expensive, and limited by our lack of in-depth knowledge of drug specificity. Since many patients already turn to nutraceuticals in hopes of improving their condition, we hypothesized that certain approved drugs could potentially synergize with widely consumed supplements. Following this hypothesis, we devised an alternative screening strategy aimed at taking advantage of a bait compound such as a nutraceutical with potential therapeutic benefits but low potency, by screening chemical libraries for approved drugs that synergize with this companion effector. As a proof of concept, we sought to identify approved drugs with synergetic therapeutic effects toward retinoblastoma cells in combination with the antioxidant resveratrol, popular as a supplement. We systematically tested FDA-approved drugs and known bioactives seeking to identify such pairs, which led to uncovering only a few additive combinations; but to our surprise, we identified a class of anticancer drugs widely used in the clinic whose therapeutic effect is antagonized with resveratrol. Our observations could explain in part why some patients do not respond well to treatment. Our results validate this alternative approach, and we expect that our companion effector strategy could significantly impact both drug discovery and the nutraceutical industry.     

Nanoscale Reaction Vessels Designed for Synthesis of Copper-Drug Complexes Suitable for Preclinical Development

The development of copper-drug complexes (CDCs) is hindered due to their very poor aqueous solubility. Diethyldithiocarbamate (DDC) is the primary metabolite of disulfiram, an approved drug for alcoholism that is being repurposed for cancer. The anticancer activity of DDC is dependent on complexation with copper to form copper bis-diethyldithiocarbamate (Cu(DDC)₂), a highly insoluble complex that has not been possible to develop for indications requiring parenteral administration. We have resolved this issue by synthesizing Cu(DDC)₂ inside liposomes. DDC crosses the liposomal lipid bilayer, reacting with the entrapped copper; a reaction that can be observed through a colour change as the solution goes from a light blue to dark brown. This method is successfully applied to other CDCs including the anti-parasitic drug clioquinol, the natural product quercetin and the novel targeted agent CX-5461. Our method provides a simple, transformative solution enabling, for the first time, the development of CDCs as viable candidate anticancer drugs; drugs that would represent a brand new class of therapeutics for cancer patients.     

FDA approved drugs complexed to their targets: evaluating pose prediction accuracy of docking protocols

Efficient drug discovery programs can be designed by utilizing existing pools of knowledge from the already approved drugs. This can be achieved in one way by repositioning of drugs approved for some indications to newer indications. Complex of drug to its target gives fundamental insight into molecular recognition and a clear understanding of putative binding site. Five popular docking protocols, Glide, Gold, FlexX, Cdocker and LigandFit have been evaluated on a dataset of 199 FDA approved drug-target complexes for their accuracy in predicting the experimental pose. Performance for all the protocols is assessed at default settings, with root mean square deviation (RMSD) between the experimental ligand pose and the docked pose of less than 2.0?? as the success criteria in predicting the pose. Glide (38.7?%) is found to be the most accurate in top ranked pose and Cdocker (58.8?%) in top RMSD pose. Ligand flexibility is a major bottleneck in failure of docking protocols to correctly predict the pose. Resolution of the crystal structure shows an inverse relationship with the performance of docking protocol. All the protocols perform optimally when a balanced type of hydrophilic and hydrophobic interaction or dominant hydrophilic interaction exists. Overall in 16 different target classes, hydrophobic interactions dominate in the binding site and maximum success is achieved for all the docking protocols in nuclear hormone receptor class while performance for the rest of the classes varied based on individual protocol.