Liquid chromatography coupled to mass spectrometry for metabolite profiling in the field of drug discovery

Introduction: The identification and characterization of the metabolites during the early stages of discovery and development of new drug candidates are essential to establish the metabolic clearance as well as the potential pharmacological and/or toxicological effects. Hence, feasible methods of analysis, preferably rapid and simple, are required to satisfy the increasing demand of metabolite profiling studies.

Areas covered: This paper reviews the topic of metabolite profiling in drug discovery based on liquid chromatography, with especial emphasis on chromatographic modes and detectors. Features and possibilities of the different options are critically discussed.

Expert opinion: High performance analytical techniques are fundamental to gain unambiguous information on metabolites of new drugs. In this regard, liquid chromatography hyphenated to mass spectrometric detection is the most popular approach. The diversity of chromatographic modes and the great variety of separation columns available offer innumerable analytical possibilities to characterize and quantify compounds with a broad range of physicochemical properties.     

Inkjet dispensing technologies: recent advances for novel drug discovery

Introduction: Inkjet-dispensing printing is a promising additive manufacturing method for pharmaceutical applications such as drug discovery. The unique advantages of this technology, including low cost, programmability, high resolution, high throughput, high speed, and biocompatibility, may reduce the financial resources needed to discover new drug candidates. Sophisticated and miniaturized assays have been developed to accomplish drug discovery and drug screening using modern inkjet dispensing printers.

Areas covered: This paper reviews recent advancements in the field of inkjet printer technology for drug discovery. Various types of inkjet printers and their recent use for the drug discovery are summarized; physical and biological limitations of this technology are also examined. Furthermore, typical inks used in the inkjet printing technology are introduced.

Expert opinion: Inkjet bioprinting technology is a promising tool for many biological and pharmaceutical applications. Several bottlenecks associated with this technology need to be addressed before commercialization. For example, sophisticated inks need to be synthesized to meet both biological and engineering restrictions. Further progress of parallel technologies will enhance the performance and functionality of the printers. It is also worth emphasizing that inkjet printing technologies must meet the requirement of regulatory agencies (e.g. the US Food & Drug Administration) for commercialization by the pharmaceutical industry.     

How can we develop better antispasmodics for irritable bowel syndrome?

Introduction: Irritable bowel syndrome (IBS) is a prevalent gastrointestinal (GI) disease. Antispasmodics are a heterogeneous group of drugs that tackle IBS-associated altered bowel habit and abdominal pain. However, some studies have shown their failure to exhibit benefit over placebo. Considering the place of antispasmodics in managing key symptoms of IBS, there is a growing need for developing more efficacious and safe antispasmodics.

Areas covered: The authors discuss the role of rational drug design (RDD) in developing new antispasmodics with desired features. Furthermore, they review the potential pharmacological targets and herbal medicines with spasmolytic activity. In addition, the authors present the recent findings concerning novel mechanisms involved in GI motility modulation as well as the potential antispasmodic role of drugs used in other conditions.

Expert opinion: To develop better antispasmodics, it will be essential to gain a deeper insight into the underlying mechanisms involved in IBS-induced dysmotility and to uncover GI-specific receptors that regulating motility. New antispasmodics with GI-restricted and the multi-targeting features can be developed via implementation of RDD. Furthermore, the modification of current antispasmodics by formulation technologies might expedite the development of better antispasmodics. To conclude, the complex nature of IBS means that future successful drug discovery will require a multi-disciplinary approach.     

Anticancer drug discovery using multicellular tumor spheroid models

Introduction: Despite the increasing financial outlay on cancer research and drug discovery, many advanced cancers remain incurable. One possible strategy for increasing the approval rate of new anticancer drugs for use in clinical practice could be represented by three-dimensional (3D) tumor models on which to perform in vitro drug screening. There is a general consensus among the scientific community that 3D tumor models more closely recapitulate the complexity of tumor tissue architecture and biology than bi-dimensional cell cultures. In a 3D context, cells are connected to each other through tissue junctions and show proliferative and metabolic gradients that resemble the intricate milieu of organs and tumors.

Areas covered: The present review focuses on available techniques for generating tumor spheroids and discusses current and future applications in the field of drug discovery. The article is based on literature obtained from PubMed.

Expert opinion: Given the relative simplicity of spheroid models with respect to clinical tumors, we must be careful not to overestimate the reliability of their drug-response prediction capacity. The next challenge is to combine our knowledge of co-culture methodologies with high-content imaging and advanced microfluidic technologies to improve the readout and biomimetic potential of spheroid-based models.     

DataWarrior: an evaluation of the open-source drug discovery tool

Introduction: DataWarrior is open and interactive software for data analysis and visualization that integrates well-established and novel chemoinformatics algorithms in a single environment. Since its public release in 2014, DataWarrior has been used by research groups in universities, government, and industry.

Areas covered: Herein, the authors discuss, in a critical manner, the tools and distinct technical features of DataWarrior and analyze the areas of opportunity. Authors also present the most common applications as well as emerging uses in research areas beyond drug discovery with an emphasis on multidisciplinary projects.

Expert opinion: In the era of big data and data-driven science, DataWarrior stands out as a technology that combines prediction of physicochemical properties of pharmaceutical interest, cheminformatics calculations, multivariate data analysis, and interactive visualization with dynamic plots. The well-established chemoinformatics tools implemented in DataWarrior, as well as the innovative algorithms, make the technology useful and attractive as revealed by the increasing number of documented applications.     

Advances with support vector machines for novel drug discovery

Introduction: Novel drug discovery remains an enormous challenge, with various computer-aided drug design (CADD) approaches having been widely employed for this purpose. CADD, specifically the commonly used support vector machines (SVMs), can employ machine learning techniques. SVMs and their variations offer numerous drug discovery applications, which range from the classification of substances (as active or inactive) to the construction of regression models and the ranking/virtual screening of databased compounds.

Areas covered: Herein, the authors consider some of the applications of SVMs in medicinal chemistry, illustrating their main advantages and disadvantages, as well as trends in their utilization, via the available published literature. The aim of this review is to provide an up-to-date review of the recent applications of SVMs in drug discovery as described by the literature, thereby highlighting their strengths, weaknesses, and future challenges.

Expert opinion: Techniques based on SVMs are considered as powerful approaches in early drug discovery. The ability of SVMs to classify active or inactive compounds has enabled the prioritization of substances for virtual screening. Indeed, one of the main advantages of SVMs is related to their potential in the analysis of nonlinear problems. However, despite successes in employing SVMs, the challenges of improving accuracy remain.     

Advances in distributed computing with modern drug discovery

Introduction: Computational chemistry dramatically accelerates the drug discovery process and high-performance computing (HPC) can be used to speed up the most expensive calculations. Supporting a local HPC infrastructure is both costly and time-consuming, and, therefore, many research groups are moving from in-house solutions to remote-distributed computing platforms.

Areas covered: The authors focus on the use of distributed technologies, solutions, and infrastructures to gain access to HPC capabilities, software tools, and datasets to run the complex simulations required in computational drug discovery (CDD).

Expert opinion: The use of computational tools can decrease the time to market of new drugs. HPC has a crucial role in handling the complex algorithms and large volumes of data required to achieve specificity and avoid undesirable side-effects. Distributed computing environments have clear advantages over in-house solutions in terms of cost and sustainability. The use of infrastructures relying on virtualization reduces set-up costs. Distributed computing resources can be difficult to access, although web-based solutions are becoming increasingly available. There is a trade-off between cost-effectiveness and accessibility in using on-demand computing resources rather than free/academic resources. Graphics processing unit computing, with its outstanding parallel computing power, is becoming increasingly important.     

A new wave of innovation in Semantic web tools for drug discovery

Introduction: The use of semantic web technologies to aid drug discovery has gained momentum over recent years. Researchers in this domain have realized that semantic web technologies are key to dealing with the high levels of data for drug discovery. These technologies enable us to represent the data in a formal, structured, interoperable and comparable way, and to tease out undiscovered links between drug data (be it identifying new drug-targets or relevant compounds, or links between specific drugs and diseases).

Areas covered: This review focuses on explaining how semantic web technologies are being used to aid advances in drug discovery. The main types of semantic web technologies are explained, outlining how they work and how they can be used in the drug discovery process, with a consideration of how the use of these technologies has progressed from their initial usage.

Expert opinion: The increased availability of shared semantic resources (tools, data and importantly the communities) have enabled the application of semantic web technologies to facilitate semantic (context dependent) search across multiple data sources, which can be used by machine learning to produce better predictions by exploiting the semantic links in knowledge graphs and linked datasets.     

Collaboration between patient and pharmacovigilance organizations to gain insight into adults’ experiences with drug use and ADRs for the treatment of ADHD

Background: Patient organizations have good access to patients, which can be of interest in gaining knowledge about patients’ experiences with drugs. The aim of this study is to investigate if a collaboration between a pharmacovigilance center and an ADHD patient organization can give more insight in patients’ experiences with drug use and ADRs for the treatment of AD(H)D.

Methods: Pharmacovigilance Centre Lareb and ADHD patient organization Impuls & Woortblind created a web-based questionnaire asking about patients’ experiences with drug use and ADRs. Patients were approached to participate by e-mail and an open web-link. They were also asked to report ADRs through the official reporting form of Lareb.

Results: A total of 1160 patients completed the questionnaire, of which 75.2% of the respondents experienced ADRs and 60.7% discontinued treatment because of an ADR. More than 70% experienced positive effects of their drugs. Additionally, 5.0% of the respondents reported their ADRs to Lareb.

Conclusions: Collaboration with patient organizations provide useful insight into patients’ experiences with drug use and ADRs taking into account establishing clear ‘rules of engagement’. An active approach to collaborate with patient organizations is a way forward to gain more information about drug use and ADRs in a selective cohort.     

Novel approaches for designing drugs that interfere with pH regulation

Introduction: In all living species, pH regulation is a tightly controlled process, with a plethora of proteins involved in its regulation. These include sodium-proton exchangers, carbonic anhydrases, anion exchangers, bicarbonate transporters/cotransporters, H⁺-ATPases, and monocarboxylate transporters. All of them play crucial roles in acid-base balancing, both in eukaryotic as well as in prokaryotic organisms, making them interesting drug targets for the management of pathological events (in)directly involved in pH regulation.

Areas covered: Interfering with pH regulation for the treatment of tumors and microbial infections is the main focus of this review, with particular attention paid to inhibitors targeting the above-mentioned proteins. The latest advances in each field id reviewed.

Expert opinion: Interfering with the pH regulation of tumor cells is a validated approach to tackle primary tumors and metastases growth. Carbonic anhydrases are the most investigated proteins of those aforementioned, with several inhibitors in clinical development. Recent advances in the characterization of proteins involved in pH homeostasis of various pathogens evidenced their crucial role in the survival and virulence of bacterial, fungal, and protozoan microorganisms. Some encouraging results shed light on the possibility to target such proteins for obtaining new anti-infectives, overcoming the extensive drug resistance problems of clinically used drugs.     

Drugs that target aging: how do we discover them?

Introduction: Biology of aging is focused on elucidating the biochemical and genetic pathways that contribute to cellular damage accumulation over time. Thirty years of research are beginning to bear fruit as the first pharmacological interventions based on biology of aging go through clinical trials. Evolutionary theories of aging suggest that naturally selected traits believed to impart fitness in young organisms may be damaging in later life. Three major areas of focus in biology of aging are lifespan, healthspan, and rejuvenation.

Areas covered: Aging research has produced several validated pharmacological interventions currently in clinical trials. Herein, the authors consider two representative case studies: 1) rapamycin analogs and their effect on the mTORC1 pathway, and 2) small molecules that target and kill senescent cells. The authors also provide their expert current and future perspectives on aging targeting drug discovery.

Expert opinion: Aging-related therapeutic interventions will continue to emerge at an accelerating pace, both from research in biology of aging, as well as from coordinated biomedical research in aging-related chronic conditions.     

Novel antiviral drug discovery strategies to tackle drug-resistant mutants of influenza virus strains

Introduction: The emergence of drug-resistant influenza virus strains highlights the need for new antiviral therapeutics to combat future pandemic outbreaks as well as continuing seasonal cycles of influenza.

Areas covered: This review summarizes the mechanisms of current FDA-approved anti-influenza drugs and patterns of resistance to those drugs. It also discusses potential novel targets for broad-spectrum antiviral drugs and recent progress in novel drug design to overcome drug resistance in influenza.

Expert opinion: Using the available structural information about drug-binding pockets, research is currently underway to identify molecular interactions that can be exploited to generate new antiviral drugs. Despite continued efforts, antivirals targeting viral surface proteins like HA, NA, and M2, are all susceptible to developing resistance. Structural information on the internal viral polymerase complex (PB1, PB2, and PA) provides a new avenue for influenza drug discovery. Host factors, either at the initial step of viral infection or at the later step of nuclear trafficking of viral RNP complex, are being actively pursued to generate novel drugs with new modes of action, without resulting in drug resistance.     

The compromise of virtual screening and its impact on drug discovery

Introduction: Docking and structure-based virtual screening (VS) have been standard approaches in structure-based design for over two decades. However, our understanding of the limitations, potential, and strength of these techniques has enhanced, raising expectations.

Areas covered: Based on a survey of reports in the past five years, we assess whether VS: (1) predicts binding poses in agreement with crystallographic data (when available); (2) is a superior screening tool, as often claimed; (3) is successful in identifying chemical scaffolds that can be starting points for subsequent lead optimization cycles. Data shows that knowledge of the target and its chemotypes in postprocessing lead to viable hits in early drug discovery endeavors.

Expert opinion: VS is capable of accurate placements in the pocket for the most part, but does not consistently score screening collections accurately. What matters is capitalization on available resources to get closer to a viable lead or optimizable series. Integration of approaches, subjective hit selection guided by knowledge of the receptor or endogenous ligand, libraries driven by experimental guides, validation studies to identify the best docking/scoring that reproduces experimental findings, constraints regarding receptor–ligand interactions, thoroughly designed methodologies, and predefined cutoff scoring criteria strengthen VS’s position in pharmaceutical research.     

Developing animal models of Zika virus infection for novel drug discovery

Introduction: Just before the Brazilian outbreak, Zika virus was related to a mild infection, causing fever and skin rash. Congenital Zika Syndrome was first described in Brazil, causing microcephaly and malformations in newborns. Three years after the outbreak, the mechanisms of Zika pathogenesis are still not completely elucidated. Moreover, as of today, there is still no approved vaccine that can be administered to the susceptible population. Considering the unmet clinical need, animal models represent an unprecedented opportunity to study Zika pathophysiology and test drugs for the treatment and prevention of vertical transmission.

Areas covered: The authors explore the current knowledge about Zika through animal models and advancements in drug discovery by highlighting drugs with the greatest potential to treat ZIKV infection and block vertical transmission.

Expert opinion: Some drugs used to treat other infections have been repurposed to treat Zika infection, reducing the cost and time for clinical application. One promising example is Sofosbuvir, which protected mice models against Zika pathogenesis by preventing vertical transmission. Importantly, there is a lack on exploration on the long-term effects of Zika Congenital Syndrome, as well as the possible ways to treat its sequelae.     

Drug use among British Bangladeshis in London: a macro-structural perspective focusing on disadvantages contributing to individuals’ drug use trajectories and engagement with treatment services

Aims: The main aim of our study was to produce an understanding of factors contributing to drug-using trajectories among men and women from a Bangladeshi background living in East London.

Methods: Fifteen semi-structured, one-to-one interviews were conducted with male and female Bangladeshi drug users accessing treatment services. A macro-structural lens was adopted to interpret participants’ accounts of their drug use and explored the intersecting factors that at a micro, meso, and macro level impacted on their drug-using trajectories.

Findings: Problem drug use (heroin and crack cocaine) among participants was the result of inter-related factors such as their friendship networks and the embeddedness of drugs in drug-using networks, the structural disadvantages participants experienced, and the need for concealment of their drug use which impacted on participants’ effective utilisation of drug treatment services. Problem drug use was a functional way of responding to and dealing with social, economic, and cultural disconnection from mainstream institutions as participants faced severe multiple disadvantages engendering stigma and shame.

Conclusions: We propose a ‘life-focused’ intervention aimed at creating extra opportunities and making critically-needed resources available in the marginalised environment of the study’s participants, which are key to restoring and maintaining agency and sustaining well-being.     

Binding site comparisons for target-centered drug discovery

Introduction: The success of binding site comparisons in drug discovery is based on the recognized fact that many different proteins have similar binding sites. Indeed, binding site comparisons have found many uses in drug development and have the potential to dramatically cut the cost and shorten the time necessary for the development of new drugs.

Areas covered: The authors review recent methods for comparing protein binding sites and their use in drug repurposing and polypharmacology. They examine emerging fields including the use of binding site comparisons in precision medicine, the prediction of structured water molecules, the search for targets of natural compounds, and their application in the development of protein-based drugs by loop modeling and for comparison of RNA binding sites.

Expert opinion: Binding site comparisons have produced many interesting results in drug development, but relatively little work has been done on protein–protein interaction sites, which are particularly relevant in view of the success of biological drugs. Growth of protein loop modeling for modulating biological drugs is anticipated. The fusion of currently distinct methods for the comparison of RNA and protein binding sites into a single comprehensive approach could allow the search for new selective ribosomal antibiotics and initiate pharmaceutical research into other nucleoproteins.     

Factors that facilitate reporting of adverse drug reactions by pharmacists in Saudi Arabia

Objectives: Adverse drug reactions (ADRs) are a pervasive global problem, and its management is integral to patient safety and healthcare quality. Pharmacists play a pivotal role in monitoring and reporting ADRs, which has a direct impact on patient care. The aim of this study was to identify potential factors that facilitate pharmacists in community and hospital settings to report ADRs.

Methods: A cross-sectional, online survey using a validated questionnaire was administered to pharmacists working in community and hospital pharmacies in Saudi Arabia.

Results: 1,717 community and 153 hospital pharmacists participated in this study. Only 10.2% and 26.8% of community and hospital pharmacists, respectively, admitted ever reporting an ADR. The most reported factors that may facilitate ADRs reporting have included ongoing improvements in therapeutic knowledge about ADRs, attending educational programs with continuous medical education credits, the seriousness of the experienced ADRs and accessibility to patients’ medical profile. The impact of peers by seeing colleagues reporting ADRs and ADRs due to herbal or traditional medicine were the least important factors reported by pharmacists.

Conclusion: The study identified factors that can effectively address the under-reporting of ADRs by pharmacists. A multi-stakeholder, multi-pronged approach of ADR reporting is needed to develop greater awareness of this issue among pharmacists.     

Combining stem cell-derived hepatocytes with impedance sensing to better predict human drug toxicity

Background: The liver plays a central role in human drug metabolism. To model drug metabolism, the major cell type of the liver, the hepatocyte, is commonly used. Hepatocytes can be derived from human and animal sources, including pluripotent stem cells. Cell-based models have shown promise in modeling human drug exposure. The assays used in those studies are normally ‘snap-shot’ in nature, and do not provide the complete picture of human drug exposure.

Research design and methods: In this study, we employ stem cell-derived hepatocytes and impedance sensing to model human drug toxicity. This impedance-based stem cell assay reports hepatotoxicity in real time after treatment with compounds provided by industry.

Results: Using electric cell-substrate impedance Sensing (ECIS), we were able to accurately measure drug toxicity post-drug exposure in real time and more quickly than gold standard biochemical assays.

Conclusions: ECIS is robust and non-destructive methodology capable of monitoring human drug exposure with superior performance to current gold standard ‘snapshot’ assays. We believe that the methodology presented within this article could prove valuable in the quest to better predict off-target effects of drugs in humans.     

Omics of antimicrobials and antimicrobial resistance

Introduction: The development of new antimicrobials has become an urgent priority because of a global challenge emerging from the rise of antimicrobial resistant pathogens.

Areas covered: In this review, the authors discuss the opportunities offered by modern omics approaches to address the challenge and the use of this approach in antimicrobial development. Specifically, the authors focus on the role of omics technologies and bioinformatics for the revelation of the effects of antimicrobials in a variety of microbial cellular processes, as well as the identification of potential cellular targets, the mechanisms of antimicrobial resistance, and the development of new antimicrobials.

Expert opinion: Prevention of antimicrobial resistance does not only depend on rational drug design such as narrow-spectrum antimicrobials but on several factors. It is the opinion of the authors that the use of a multi-omics bioinformatics approach should become an integral part of antimicrobial drug discovery as well as in the prevention of antimicrobial resistance.     

The quality of spontaneous adverse drug reaction reports from the pharmacovigilance centre in western China

Background: High-quality adverse drug reaction (ADR) reports are essential for conducting drug safety monitoring in pharmacovigilance. The study aim was to assess the current quality of ADR reports in western China, and to identify problems with ADR report quality.

Research design and methods: A sample of 1139 reports received by the Shaanxi ADR Monitoring Center from January 2015 to December 2017 was selected. ADR report quality was evaluated using an ADR report quality evaluation system.

Results: None of the reports were rated as excellent and 1.40% (n = 16) as good. Report quality was better for new and serious reports than for general reports. Medical institutions generated higher quality reports than pharmaceutical manufacturers. Nurses generated higher quality reports than doctors, pharmacists, and other professionals. Reporters of different occupations showed significant differences in the quality of the indicators Reporting time limit, Intervention ADR time, ADR termination time, ADR intervention measures, Original disease, and Cause of medication (P = 0.000).

Conclusions: The ADR data quality was poor in western China, and of lower quality than reported data from previous research in other regions. Improvements in the quality and availability of ADR reports are urgently needed.