Is poor research the cause of the declining productivity of the pharmaceutical industry? An industry in need of a paradigm shift

Many are called, few are chosen: the role of science in drug development decisions

Pharmaceutical firms are extremely selective in deciding which patented drug candidates are taken up into clinical development, given the high costs and risks involved. We argue that the scientific base of drug candidates, and who was responsible for that scientific research, are key antecedents of take-up into clinical trials and whether the patent owner ('internal take-up') or another firm ('external take-up') leads the clinical development effort. We hypothesize that patented drug candidates that refer to scientific research are more likely to be taken up in development, and that in-house conducted scientific research is predominantly associated with internal take-up due to the ease of knowledge transfer within the firm. Examining 18,360 drug candidates patented by 136 pharmaceutical firms we find support for these hypotheses. In addition, drug candidates referring to in-house scientific research exhibit a higher probability of eventual drug development success. Our findings underline the importance of a 'rational drug design' approach that explicitly builds on scientific research. The benefits of internal scientific research in clinical development highlight the potential downside of pervasive organizational specialization in the life sciences in either scientific research or clinical development.

Large-scale phenotypic drug screen identifies neuroprotectants in zebrafish and mouse models of retinitis pigmentosa

Retinitis pigmentosa (RP) and associated inherited retinal diseases (IRDs) are caused by rod photoreceptor degeneration, necessitating therapeutics promoting rod photoreceptor survival. To address this, we tested compounds for neuroprotective effects in multiple zebrafish and mouse RP models, reasoning drugs effective across species and/or independent of disease mutation may translate better clinically. We first performed a large-scale phenotypic drug screen for compounds promoting rod cell survival in a larval zebrafish model of inducible RP. We tested 2934 compounds, mostly human-approved drugs, across six concentrations, resulting in 113 compounds being identified as hits. Secondary tests of 42 high-priority hits confirmed eleven lead candidates. Leads were then evaluated in a series of mouse RP models in an effort to identify compounds effective across species and RP models, that is, potential pan-disease therapeutics. Nine of 11 leads exhibited neuroprotective effects in mouse primary photoreceptor cultures, and three promoted photoreceptor survival in mouse rd1 retinal explants. Both shared and complementary mechanisms of action were implicated across leads. Shared target tests implicated parp1-dependent cell death in our zebrafish RP model. Complementation tests revealed enhanced and additive/synergistic neuroprotective effects of paired drug combinations in mouse photoreceptor cultures and zebrafish, respectively. These results highlight the value of cross-species/multi-model phenotypic drug discovery and suggest combinatorial drug therapies may provide enhanced therapeutic benefits for RP patients.

Beyond Pseudo-natural Products: Sequential Ugi/Pictet-Spengler Reactions Leading to Steroidal Pyrazinoisoquinolines That Trigger Caspase-Independent Death in HepG2 Cells

In this work, we describe how stereochemically complex polycyclic compounds can be generated by applying a synthetic sequence comprising an intramolecular Ugi reaction followed by a Pictet-Spengler cyclization on steroid-derived scaffolds. The resulting compounds, which combine a fragment derived from a natural product and a scaffold not found in nature. are both structurally distinct and globally similar to natural products at the same time, and interrogate an alternative region of the chemical space. One of the new compounds showed significant antiproliferative activity on HepG2 cells through a caspase-independent cell-death mechanism, an appealing feature when new antitumor compounds are searched.

How Do Pharmaceutical Companies Overcome a Corporate Productivity Crisis? Business Diversification into Medical Devices for Growth Potential

The purpose of this study was to analyze the performance of pharmaceutical companies’ business diversification into medical devices in terms of their technical efficiency (TE) as compared to that of traditional pharmaceutical companies. For a total of 174 externally audited pharmaceutical companies engaged in the drug product business between 2008 and 2019, pharmaceutical companies were classified into two groups according to medical device business diversification. The TE of pharmaceutical companies that diversify the medical device business was lower than that of traditional pharmaceutical companies. However, in terms of the meta-technology ratio (MTR) calculated using meta-frontier analysis, pharmaceutical companies diversified into medical devices showed higher MTR than the traditional pharmaceutical company group. The results imply that the corporate performance growth potential of traditional pharmaceutical companies is lower than that of pharmaceutical companies that have diversified into the medical device business.

Image-based high-content screening in drug discovery

While target-based drug discovery strategies rely on the precise knowledge of the identity and function of the drug targets, phenotypic drug discovery (PDD) approaches allow the identification of novel drugs based on knowledge of a distinct phenotype. Image-based high-content screening (HCS) is a potent PDD strategy that characterizes small-molecule effects through the quantification of features that depict cellular changes among or within cell populations, thereby generating valuable data sets for subsequent data analysis. However, these data can be complex, making image analysis from large HCS campaigns challenging. Technological advances in image acquisition, processing, and analysis as well as machine-learning (ML) approaches for the analysis of multidimensional data sets have rendered HCS as a viable technology for small-molecule drug discovery. Here, we discuss HCS concepts, current workflows as well as opportunities and challenges of image-based phenotypic screening and data analysis.

Adaptation of robust Z' factor for assay quality assessment in microelectrode array based screening using adult dorsal root ganglion neurons

BACKGROUND

Cell-based assays comprising primary sensory neurons cultured in vitro are an emerging tool for the screening and identification of potential analgesic compounds and chronic pain treatments. High-content screening (HCS) platforms for drug screening are characterized by a measure of assay quality indicator, such as the Z'-factor, which considers the signal dynamic range and data variation using control compounds only. Although widely accepted as a quality metric in high throughput screening (HTS), standard Z'-factor are not well-suited to indicate the quality of complex cell-based assays.

NEW METHOD

The present study describes a method to assess assay quality in the context of extracellular recordings from dorsal root ganglion (DRG) sensory neurons cultured on multi-well microelectrode arrays. Data transformations are applied to electrophysiological parameters, such as electrode and well spike rates, for valid normality assumptions and suitability for use as a sample signal. Importantly, using transformed well-wide metrics, a robust version of the Z'-factor was applied, based on the median and median absolute deviation, to indicate assay quality and assess hit identification of putative pharmacological compounds.

RESULTS

Application of appropriately scaled data and robust statistics ensured insensitivity to data variation and approximation of normal distribution. The use median and median absolute deviation of log transformed well spike rates in computing the Z'-factor revealed a value of 0.61, which is accepted as an "excellent assay." Known antagonists of nociceptor-specific voltage-gated sodium ion channels were identified as true hits in the present assay format under both spontaneous and thermally stimulated conditions.

COMPARISON WITH EXISTING METHODS

The present approach demonstrated a large signal dynamic range and reduced sensitivity to data variation compared to standard Z'-factor used widely in HTS.

CONCLUSION

Overall, the present study provides a statistical basis for the implementation of a HCS platform utilizing adult DRG neurons on microelectrode arrays.

Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics

Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.

The Convergence of Stem Cell Technologies and Phenotypic Drug Discovery

Recent advances in induced pluripotent stem cell technologies and phenotypic screening shape the future of bioactive small-molecule discovery. In this review we analyze the impact of small-molecule phenotypic screens on drug discovery as well as on the investigation of human development and disease biology. We further examine the role of 3D spheroid/organoid structures, microfluidic systems, and miniaturized on-a-chip systems for future discovery strategies. In highlighting representative examples, we analyze how recent achievements can translate into future therapies. Finally, we discuss remaining challenges that need to be overcome for the adaptation of the next generation of screening approaches.

Automated De Novo Drug Design: Are We Nearly There Yet?

Medicinal chemistry and, in particular, drug design have often been perceived as more of an art than a science. The many unknowns of human disease and the sheer complexity of chemical space render decision making in medicinal chemistry exceptionally demanding. Computational models can assist the medicinal chemist in this endeavour. Provided here is an overview of recent examples of automated de novo molecular design, a discussion of the concepts and computational approaches involved, and the daring prediction of some of the possibilities and limitations of drug design using machine intelligence.

Reframing the Biological Basis of Neuroprotection Using Functional Genomics: Differentially Weighted, Time-Dependent Multifactor Pathogenesis of Human Ischemic Brain Damage

Background: Neuroprotection studies are generally unable to demonstrate efficacy in humans. Our specific hypothesis is that multiple pathophysiologic pathways, of variable importance, contribute to ischemic brain damage. As a corollary to this, we discuss the broad hypothesis that a multifaceted approach will improve the probability of efficacious neuroprotection. But to properly test this hypothesis the nature and importance of the multiple contributing pathways needs elucidation. Our aim is to demonstrate, using functional genomics, in human cardiac surgery procedures associated with cerebral ischemia, that the pathogenesis of perioperative human ischemic brain damage involves the function of multiple variably weighted proteins involving several pathways. We then use these data and literature to develop a proposal for rational design of human neuroprotection protocols.

Methods: Ninety-four patients undergoing deep hypothermic circulatory arrest (DHCA) and/or aortic valve replacement surgery had brain damage biomarkers, S100β and neurofilament H (NFH), assessed at baseline, 1 and 24 h post-cardiopulmonary bypass (CPB) with analysis for association with 92 single nucleotide polymorphisms (SNPs) (selected by co-author WAK) related to important proteins involved in pathogenesis of cerebral ischemia.

Results: At the nominal significance level of 0.05, changes in S100β and in NFH at 1 and 24 h post-CPB were associated with multiple SNPs involving several prospectively determined pathophysiologic pathways, but were not individually significant after multiple comparison adjustments. Variable weights for the several evaluated SNPs are apparent on regression analysis and, notably, are dissimilar related to the two biomarkers and over time post CPB. Based on our step-wise regression model, at 1 h post-CPB, SOD2, SUMO4, and GP6 are related to relative change of NFH while TNF, CAPN10, NPPB, and SERPINE1 are related to the relative change of S100B. At 24 h post-CPB, ADRA2A, SELE, and BAX are related to the relative change of NFH while SLC4A7, HSPA1B, and FGA are related to S100B.

Conclusions: In support of the proposed hypothesis, association SNP data suggest function of specific disparate proteins, as reflected by genetic variation, may be more important than others with variation at different post-insult times after human brain ischemia. Such information may support rational design of post-insult time-sensitive multifaceted neuroprotective therapies.

The Oncopig Cancer Model as a Complementary Tool for Phenotypic Drug Discovery

The screening of potential therapeutic compounds using phenotypic drug discovery (PDD) is being embraced once again by researchers and pharmaceutical companies as an approach to enhance the development of new effective therapeutics. Before the genomics and molecular biology era and the consecutive emergence of targeted-drug discovery approaches, PDD was the most common platform used for drug discovery. PDD, also known as phenotypic screening, consists of screening potential compounds in either in vitro cellular or in vivo animal models to identify compounds resulting in a desirable phenotypic change. Using this approach, the biological targets of the compounds are not taken into consideration. Suitable animal models are crucial for the continued validation and discovery of new drugs, as compounds displaying promising results in phenotypic in vitro cell-based and in vivo small animal model screenings often fail in clinical trials. Indeed, this is mainly a result of differential anatomy, physiology, metabolism, immunology, and genetics between humans and currently used pre-clinical small animal models. In contrast, pigs are more predictive of therapeutic treatment outcomes in humans than rodents. In addition, pigs provide an ideal platform to study cancer due to their similarities with humans at the anatomical, physiological, metabolic, and genetic levels. Here we provide a mini-review on the reemergence of PDD in drug development, highlighting the potential of porcine cancer models for improving pre-clinical drug discovery and testing. We also present precision medicine based genetically defined swine cancer models developed to date and their potential as biomedical models.

Phenotypic Screen Identifies a Small Molecule Modulating ERK2 and Promoting Stem Cell Proliferation

Stem cells display a fundamentally different mechanism of proliferation control when compared to somatic cells. Uncovering these mechanisms would maximize the impact in drug discovery with a higher translational applicability. The unbiased approach used in phenotype-based drug discovery (PDD) programs can offer a unique opportunity to identify such novel biological phenomenon. Here, we describe an integrated phenotypic screening approach, employing a combination of in vitro and in vivo PDD models to identify a small molecule increasing stem cell proliferation. We demonstrate that a combination of both in vitro and in vivo screening models improves hit identification and reproducibility of effects across various PDD models. Using cell viability and colony size phenotype measurement we characterize the structure activity relationship of the lead molecule, and identify that the small molecule inhibits phosphorylation of ERK2 and promotes stem cell proliferation. This study demonstrates a PDD approach that employs combinatorial models to identify compounds promoting stem cell proliferation.

The Burden of the "False-Negatives" in Clinical Development: Analyses of Current and Alternative Scenarios and Corrective Measures

The “false‐negatives” of clinical development are the effective treatments wrongly determined ineffective. Statistical errors leading to “false‐negatives” are larger than those leading to “false‐positives,” especially in typically underpowered early‐phase trials. In addition, “false‐negatives” are usually eliminated from further testing, thereby limiting the information available on them. We simulated the impact of early‐phase power on economic productivity in three developmental scenarios. Scenario 1, representing the current status quo, assumed 50% statistical power at phase II and 90% at phase III. Scenario 2 assumed increased power (80%), and Scenario 3, increased stringency of alpha (1%) at phase II. Scenario 2 led, on average, to a 60.4% increase in productivity and 52.4% increase in profit. Scenario 3 had no meaningful advantages. Our results suggest that additional costs incurred by increasing the power of phase II studies are offset by the increase in productivity. We discuss the implications of our results and propose corrective measures.

Comparison of the Psychopharmacological Effects of Tiletamine and Ketamine in Rodents

The glutamate N-methyl-d-aspartate (NMDA) receptor antagonist ketamine (KET) produces rapid and sustained antidepressant effects in patients. Tiletamine (TIL; 2-ethylamino-2-thiophen-2-yl-cyclohexan-1-one) is another uncompetitive NMDA receptor antagonist, used in a medical (veterinary) setting as an anesthetic tranquilizer. Here, we compared the behavioral actions of KET and TIL in a variety of tests, focusing on antidepressant-like and dissociative-like effects in mice and rats. The minimum effective doses of KET and TIL were 10 mg/kg to reduce mouse forced swim test immobility and 15 mg/kg to reduce marble-burying behavior. However, at similar doses, both compounds diminished locomotor activity and disturbed learning processes in the mouse passive avoidance test and the rat novel object recognition test. KET and TIL also reduced social behavior and accompanying 50-kHz “happy” ultrasonic vocalizations (USVs) in rats. TIL (5–15 mg/kg) displayed additional anxiolytic-like effects in the four-plate test. Neither KET nor TIL affected pain response in the hot plate test. Examination of the “side effects” revealed that only at the highest doses investigated did both compounds produce motor deficits in the rotarod test in mice. While KET produced behavioral effects at doses comparable between species, in the rats, TIL was ~10 times more potent than in the mice. In summary, antidepressant-like properties of both KET and TIL are similar, as are their adverse effect liabilities. We suggest that TIL could be an alternative to KET as an antidepressant with an additional anxiolytic-like profile.

Multidimensional Complexity of Cancer. Simple Solutions Are Needed

Cancer is a complex system. Tumor complexity is determined not only by genetic and epigenetic heterogeneity, but also by a huge number of interactions between cancer and normal cells. The heterogeneity and complexity of a tumor causes failure of molecular targeting therapy as a tool for fighting cancer. This review considers the concepts of malignant tumors as organisms that have common characteristics despite all heterogeneity. This leads to the idea that one of the most promising strategies for fighting cancer is the use of the patient's immune system.

High Throughput Screening for Colorectal Cancer Specific Compounds

The development of new anti-cancer therapeutic agents is necessary to improve antitumor efficacy and reduce toxicities. Here we report using a systematic anticancer drug screening approach we developed previously, to concurrently screen colon and glioma cancer cell lines for 2000 compounds with known bioactivity and 1920 compounds with unknown activity. The hits specific to each tumor cell line were then selected, and further tested with the same cells transfected with EGFP (Enhanced Green Fluorescent Protein) alone. By comparing the percentage of signal reduction from the same cells transfected with the sensor-conjugated reporter system; hits preferably causing apoptosis were identified. Among the known lead compounds, many cardiac glycosides used as cardiotonic drugs were found to effectively and specifically kill colon cancer cells, while statins (hypolipidemic agents) used as cholesterol lowering drugs were relatively more effective in killing glioma cells.

Plate-based diversity subset screening generation 2: an improved paradigm for high-throughput screening of large compound files

High-throughput screening (HTS) is an effective method for lead and probe discovery that is widely used in industry and academia to identify novel chemical matter and to initiate the drug discovery process. However, HTS can be time consuming and costly and the use of subsets as an efficient alternative to screening entire compound collections has been investigated. Subsets may be selected on the basis of chemical diversity, molecular properties, biological activity diversity or biological target focus. Previously, we described a novel form of subset screening: plate-based diversity subset (PBDS) screening, in which the screening subset is constructed by plate selection (rather than individual compound cherry-picking), using algorithms that select for compound quality and chemical diversity on a plate basis. In this paper, we describe a second-generation approach to the construction of an updated subset: PBDS2, using both plate and individual compound selection, that has an improved coverage of the chemical space of the screening file, whilst only selecting the same number of plates for screening. We describe the validation of PBDS2 and its successful use in hit and lead discovery. PBDS2 screening became the default mode of singleton (one compound per well) HTS for lead discovery in Pfizer.

A novel 384-multiwell microelectrode array for the impedimetric monitoring of Tau protein induced neurodegenerative processes

Over the last decades, countless bioelectronic monitoring systems were developed for the analysis of cells as well as complex tissues. Most studies addressed the sensitivity and specificity of the bioelectronic detection method in comparison to classical molecular biological assays. In contrast, the up scaling as a prerequisite for the practical application of these novel bioelectronic monitoring systems is mostly only discussed theoretically. In this context, we developed a novel 384-multiwell microelectrode array (MMEA) based measurement system for the sensitive label-free real-time monitoring of neurodegenerative processes by impedance spectroscopy. With respect to the needs of productive screening systems for robust and reproducible measurements on high numbers of plates, we focused on reducing the critical contacting of more than 400 electrodes for a 384-MMEA. Therefore, we introduced an on top array of immersive counter electrodes that are individually addressed by a multiplexer and connected all measurement electrodes on the 384-MMEA to a single contact point. More strikingly, our novel approach provided a comparable signal stability and sensitivity similar to an array with integrated counter electrodes. Next, we optimized a SH-SY5Y cell based tauopathy model by introducing a novel 5-fold Tau mutation eliminating the need of artificial tauopathy induction. In combination with our novel 384-MMEA based measurement system, the concentration and time dependent neuroregenerative effect of the kinase inhibitor SRN-003-556 could be quantitatively monitored. Thus, our novel screening system could be a useful tool to identify and develop potential novel therapeutics in the field of Tau-related neurodegenerative diseases.

Preclinical animal anxiety research - flaws and prejudices

The current tests of anxiety in mice and rats used in preclinical research include the elevated plus-maze (EPM) or zero-maze (EZM), the light/dark box (LDB), and the open-field (OF). They are currently very popular, and despite their poor achievements, they continue to exert considerable constraints on the development of novel approaches. Hence, a novel anxiety test needs to be compared with these traditional tests, and assessed against various factors that were identified as a source of their inconsistent and contradictory results. These constraints are very costly, and they are in most cases useless as they originate from flawed methodologies. In the present report, we argue that the EPM or EZM, LDB, and OF do not provide unequivocal measures of anxiety; that there is no evidence of motivation conflict involved in these tests. They can be considered at best, tests of natural preference for unlit and/or enclosed spaces. We also argued that pharmacological validation of a behavioral test is an inappropriate approach; it stems from the confusion of animal models of human behavior with animal models of pathophysiology. A behavioral test is developed to detect not to produce symptoms, and a drug is used to validate an identified physiological target. In order to overcome the major methodological flaws in animal anxiety studies, we proposed an open space anxiety test, a 3D maze, which is described here with highlights of its various advantages over to the traditional tests.

Developing predictive assays: the phenotypic screening "rule of 3"

Phenotypic drug discovery approaches can positively affect the translation of preclinical findings to patients. However, not all phenotypic assays are created equal. A critical question then follows: What are the characteristics of the optimal assays? We analyze this question and propose three specific criteria related to the disease relevance of the assay-system, stimulus, and end point-to help design the most predictive phenotypic assays.

When Quality Beats Quantity: Decision Theory, Drug Discovery, and the Reproducibility Crisis

A striking contrast runs through the last 60 years of biopharmaceutical discovery, research, and development. Huge scientific and technological gains should have increased the quality of academic science and raised industrial R&D efficiency. However, academia faces a "reproducibility crisis"; inflation-adjusted industrial R&D costs per novel drug increased nearly 100 fold between 1950 and 2010; and drugs are more likely to fail in clinical development today than in the 1970s. The contrast is explicable only if powerful headwinds reversed the gains and/or if many "gains" have proved illusory. However, discussions of reproducibility and R&D productivity rarely address this point explicitly. The main objectives of the primary research in this paper are: (a) to provide quantitatively and historically plausible explanations of the contrast; and (b) identify factors to which R&D efficiency is sensitive. We present a quantitative decision-theoretic model of the R&D process. The model represents therapeutic candidates (e.g., putative drug targets, molecules in a screening library, etc.) within a "measurement space", with candidates' positions determined by their performance on a variety of assays (e.g., binding affinity, toxicity, in vivo efficacy, etc.) whose results correlate to a greater or lesser degree. We apply decision rules to segment the space, and assess the probability of correct R&D decisions. We find that when searching for rare positives (e.g., candidates that will successfully complete clinical development), changes in the predictive validity of screening and disease models that many people working in drug discovery would regard as small and/or unknowable (i.e., an 0.1 absolute change in correlation coefficient between model output and clinical outcomes in man) can offset large (e.g., 10 fold, even 100 fold) changes in models' brute-force efficiency. We also show how validity and reproducibility correlate across a population of simulated screening and disease models. We hypothesize that screening and disease models with high predictive validity are more likely to yield good answers and good treatments, so tend to render themselves and their diseases academically and commercially redundant. Perhaps there has also been too much enthusiasm for reductionist molecular models which have insufficient predictive validity. Thus we hypothesize that the average predictive validity of the stock of academically and industrially "interesting" screening and disease models has declined over time, with even small falls able to offset large gains in scientific knowledge and brute-force efficiency. The rate of creation of valid screening and disease models may be the major constraint on R&D productivity.

Drug discovery in ophthalmology: past success, present challenges, and future opportunities

BACKGROUND

Drug discovery has undergone major transformations in the last century, progressing from the recognition and refinement of natural products with therapeutic benefit, to the systematic screening of molecular libraries on whole organisms or cell lines and more recently to a more target-based approach driven by greater knowledge of the physiological and pathological pathways involved. Despite this evolution increasing challenges within the drug discovery industry are causing escalating rates of failure of development pipelines.

DISCUSSION

We review the challenges facing the drug discovery industry, and discuss what attempts are being made to increase the productivity of drug development, including a refocusing on the study of the basic biology of the disease, and an embracing of the concept of 'translational research'. We consider what ophthalmic drug discovery can learn from the sector in general and discuss strategies to overcome the present limitations. This includes advances in the understanding of the pathogenesis of disease; improvements in animal models of human disease; improvements in ophthalmic drug delivery and attempts at patient stratification within clinical trials. As we look to the future, we argue that investment in ophthalmic drug development must continue to cover the whole translational spectrum (from 'bench to bedside and back again') with recognition that both biological discovery and clinical understanding will drive drug discovery, providing safe and effective therapies for ocular disease.

Regulatory aspects of small molecule drugs for heart regeneration

Even though recent discoveries prove the existence of cardiac progenitor cells, internal regenerative capacity of the heart is minimal. As cardiovascular disease is the leading cause of deaths in the United States, a number of approaches are being used to develop treatments for heart repair and regeneration. Small molecule drugs are of particular interest as they are suited for oral administration and can be chemically synthesized. However, the regulatory process for the development of new treatment modalities is protracted, complex and expensive. One of the hurdles to development of appropriate therapies is the need for predictive preclinical models. The use of patient-derived cardiomyocytes from iPSC cells represents a novel tool for this purpose. Among other concepts for induction of heart regeneration, the most advanced is the combination of DPP-IV inhibitors with stem cell mobilizers. This review will focus on regulatory aspects as well as preclinical hurdles of development of new treatments for heart regeneration.

Neuropharmacology beyond reductionism - A likely prospect

Neuropharmacology had several major past successes, but the last few decades did not witness any leap forward in the drug treatment of brain disorders. Moreover, current drugs used in neurology and psychiatry alleviate the symptoms, while hardly curing any cause of disease, basically because the etiology of most neuro-psychic syndromes is but poorly known. This review argues that this largely derives from the unbalanced prevalence in neuroscience of the analytic reductionist approach, focused on the cellular and molecular level, while the understanding of integrated brain activities remains flimsier. The decline of drug discovery output in the last decades, quite obvious in neuropharmacology, coincided with the advent of the single target-focused search of potent ligands selective for a well-defined protein, deemed critical in a given pathology. However, all the widespread neuro-psychic troubles are multi-mechanistic and polygenic, their complex etiology making unsuited the single-target drug discovery. An evolving approach, based on systems biology considers that a disease expresses a disturbance of the network of interactions underlying organismic functions, rather than alteration of single molecular components. Accordingly, systems pharmacology seeks to restore a disturbed network via multi-targeted drugs. This review notices that neuropharmacology in fact relies on drugs which are multi-target, this feature having occurred just because those drugs were selected by phenotypic screening in vivo, or emerged from serendipitous clinical observations. The novel systems pharmacology aims, however, to devise ab initio multi-target drugs that will appropriately act on multiple molecular entities. Though this is a task much more complex than the single-target strategy, major informatics resources and computational tools for the systemic approach of drug discovery are already set forth and their rapid progress forecasts promising outcomes for neuropharmacology.

Resolution Pharmacology: Opportunities for Therapeutic Innovation in Inflammation

Current medicines for the clinical management of inflammatory diseases act by inhibiting specific enzymes or antagonising specific receptors or blocking their ligands. In the past decade, a new paradigm in our understanding of the inflammatory process has emerged with the appreciation of genetic, molecular, and cellular mechanisms that are engaged to actively resolve inflammation. The 'resolution of acute inflammation' is enabled by counter-regulatory checkpoints to terminate the inflammatory reaction, promoting healing and repair. It may be possible to harness this knowledge for innovative approaches to the treatment of inflammatory pathologies. Here we discuss current translational attempts to develop agonists at proresolving targets as a strategy to rectify chronic inflammatory status. We reason this new approach will lead to the identification of better drugs that will establish a new branch of pharmacology, 'resolution pharmacology'.

Anticancer metallohelices: nanomolar potency and high selectivity

New optically pure helicate-like architectures are extremely active against cancer cell lines, with IC₅₀ values as low as 40 nM, but nearly three orders of magnitude less active against healthy cells. There is also low toxicity to microbes and amoeba.

A range of new helicate-like architectures have been prepared via highly diastereoselective self-assembly using readily accessible starting materials. Six pairs of enantiomers [Fe₂L₃]Cl₄·nH₂O (L = various bidentate ditopic ligands NN–NN) show very good water solubility and stability. Their activity against a range of cancer cell lines in vitro is structure-dependent and gives IC₅₀ values as low as 40 nM. In an isogenic pair of HCT116 colorectal cancer cells, preferential activity was observed against cell lines that lack functional p53. Selectivity is also excellent, and against healthy human retinal pigment epithelial (ARPE19) and lung fibroblast (WI38) cells IC₅₀ values are nearly three orders of magnitude higher. Cisplatin is unselective in the same tests. The compounds also appear to have low general toxicity in a number of models: there is little if any antimicrobial activity against methicillin-resistant Staphylococcus aureus and Escherichia coli; Acanthamoeba polyphaga is unaffected at 25 μg mL^–1 (12.5 μM); Manduca sexta larvae showed clear evidence of systemic distribution of the drug, and rather than any observation of adverse effects they exhibited a significant mean weight gain vs. controls. Investigation of the mode of action revealed no significant interaction of the molecules with DNA, and stimulation of substantial cell death by apoptosis.

Updates on drug-target network; facilitating polypharmacology and data integration by growth of DrugBank database

Network pharmacology elucidates the relationship between drugs and targets. As the identified targets for each drug increases, the corresponding drug-target network (DTN) evolves from solely reflection of the pharmaceutical industry trend to a portrait of polypharmacology. The aim of this study was to evaluate the potentials of DrugBank database in advancing systems pharmacology. We constructed and analyzed DTN from drugs and targets associations in the DrugBank 4.0 database. Our results showed that in bipartite DTN, increased ratio of identified targets for drugs augmented density and connectivity of drugs and targets and decreased modular structure. To clear up the details in the network structure, the DTNs were projected into two networks namely, drug similarity network (DSN) and target similarity network (TSN). In DSN, various classes of Food and Drug Administration-approved drugs with distinct therapeutic categories were linked together based on shared targets. Projected TSN also showed complexity because of promiscuity of the drugs. By including investigational drugs that are currently being tested in clinical trials, the networks manifested more connectivity and pictured the upcoming pharmacological space in the future years. Diverse biological processes and protein-protein interactions were manipulated by new drugs, which can extend possible target combinations. We conclude that network-based organization of DrugBank 4.0 data not only reveals the potential for repurposing of existing drugs, also allows generating novel predictions about drugs off-targets, drug-drug interactions and their side effects. Our results also encourage further effort for high-throughput identification of targets to build networks that can be integrated into disease networks.

Top 100 bestselling drugs represent an arena struggling for new FDA approvals: drug age as an efficiency indicator

We analyzed a list of the top 100 bestselling drugs as a struggling market for new FDA approvals. Using the time from drug approval by the FDA as a measure of drug age, our analysis showed that the top 100 bestselling drugs are getting older. This reflects the stalled launch of new drugs into the market during recent years.

60 years of advances in neuropsychopharmacology for improving brain health, renewed hope for progress

Pharmacotherapy is effective in helping many patients suffering from psychiatric and neurological disorders, and both psychotherapeutic and stimulation-based techniques likewise have important roles to play in their treatment. However, therapeutic progress has recently been slow. Future success for improving the control and prevention of brain disorders will depend upon deeper insights into their causes and pathophysiological substrates. It will also necessitate new and more rigorous methods for identifying, validating, developing and clinically deploying new treatments. A field of Research and Development (R and D) that remains critical to this endeavour is Neuropsychopharmacology which transformed the lives of patients by introducing pharmacological treatments for psychiatric disorder some 60 years ago. For about half of this time, the European College of Neuropsychopharmacology (ECNP) has fostered efforts to enhance our understanding of the brain, and to improve the management of psychiatric disorders. Further, together with partners in academia and industry, and in discussions with regulators and patients, the ECNP is implicated in new initiatives to achieve this goal. This is then an opportune moment to survey the field, to analyse what we have learned from the achievements and failures of the past, and to identify major challenges for the future. It is also important to highlight strategies that are being put in place in the quest for more effective treatment of brain disorders: from experimental research and drug discovery to clinical development and collaborative ventures for reinforcing "R and D". The present article sets the scene, then introduces and interlinks the eight articles that comprise this Special Volume of European Neuropsychopharmacology. A broad-based suite of themes is covered embracing: the past, present and future of "R and D" for psychiatric disorders; complementary contributions of genetics and epigenetics; efforts to improve the treatment of depression, neurodevelopmental and neurodegenerative disorders; and advances in the analysis and neuroimaging of cellular and cerebral circuits.

Learning from the past and looking to the future: Emerging perspectives for improving the treatment of psychiatric disorders

Modern neuropsychopharmacology commenced in the 1950s with the serendipitous discovery of first-generation antipsychotics and antidepressants which were therapeutically effective yet had marked adverse effects. Today, a broader palette of safer and better-tolerated agents is available for helping people that suffer from schizophrenia, depression and other psychiatric disorders, while complementary approaches like psychotherapy also have important roles to play in their treatment, both alone and in association with medication. Nonetheless, despite considerable efforts, current management is still only partially effective, and highly-prevalent psychiatric disorders of the brain continue to represent a huge personal and socio-economic burden. The lack of success in discovering more effective pharmacotherapy has contributed, together with many other factors, to a relative disengagement by pharmaceutical firms from neuropsychiatry. Nonetheless, interest remains high, and partnerships are proliferating with academic centres which are increasingly integrating drug discovery and translational research into their traditional activities. This is, then, a time of transition and an opportune moment to thoroughly survey the field. Accordingly, the present paper, first, chronicles the discovery and development of psychotropic agents, focusing in particular on their mechanisms of action and therapeutic utility, and how problems faced were eventually overcome. Second, it discusses the lessons learned from past successes and failures, and how they are being applied to promote future progress. Third, it comprehensively surveys emerging strategies that are (1), improving our understanding of the diagnosis and classification of psychiatric disorders; (2), deepening knowledge of their underlying risk factors and pathophysiological substrates; (3), refining cellular and animal models for discovery and validation of novel therapeutic agents; (4), improving the design and outcome of clinical trials; (5), moving towards reliable biomarkers of patient subpopulations and medication efficacy and (6), promoting collaborative approaches to innovation by uniting key partners from the regulators, industry and academia to patients. Notwithstanding the challenges ahead, the many changes and ideas articulated herein provide new hope and something of a framework for progress towards the improved prevention and relief of psychiatric and other CNS disorders, an urgent mission for our Century.

Fidelity by design: Yoctoreactor and binder trap enrichment for small-molecule DNA-encoded libraries and drug discovery

DNA-encoded small-molecule library (DEL) technology allows vast drug-like small molecule libraries to be efficiently synthesized in a combinatorial fashion and screened in a single tube method for binding, with an assay readout empowered by advances in next generation sequencing technology. This approach has increasingly been applied as a viable technology for the identification of small-molecule modulators to protein targets and as precursors to drugs in the past decade. Several strategies for producing and for screening DELs have been devised by both academic and industrial institutions. This review highlights some of the most significant and recent strategies along with important results. A special focus on the production of high fidelity DEL technologies with the ability to eliminate screening noise and false positives is included: using a DNA junction called the Yoctoreactor, building blocks (BBs) are spatially confined at the center of the junction facilitating both the chemical reaction between BBs and encoding of the synthetic route. A screening method, known as binder trap enrichment, permits DELs to be screened robustly in a homogeneous manner delivering clean data sets and potent hits for even the most challenging targets.

Addressing the Right Targets in Oncology

Translating existing and emerging knowledge of cancer biology into effective novel therapies remains a great challenge in drug discovery. A firm understanding of the target biology, confidence in the supporting preclinical research, and access to diverse chemical matter is required to lower attrition rates and prosecute targets effectively. Understanding past successes and failures will aid in refining this process to deliver further therapeutic benefit to patients. In this review, we suggest that early oncology drug discovery should focus on selection and prosecution of cancer targets with strong disease biology rather than on more chemically “druggable” targets with only modest disease-linkage. This approach offers higher potential benefit but also increases the need for innovative and alternative approaches. These include using different methods to validate novel targets and identify chemical matter, as well as raising the standards and our interpretation of the scientific literature. The combination of skills required for this emphasizes the need for broader early collaborations between academia and industry.

Integrating human pluripotent stem cells into drug development

Integration of physiologically relevant in vitro assays at the earliest stages of drug discovery may improve the likelihood of successfully translating preclinical discoveries to the clinic. Assays based on in vitro-differentiated, human pluripotent stem cell (IVD hPSC)-derived cells, which may better model human physiology, are starting to impact the drug discovery process, but their implementation has been slower than originally anticipated. In this Perspective, we discuss imperatives for incorporating IVD hPSCs into drug discovery and the associated challenges.

Extending in silico mechanism-of-action analysis by annotating targets with pathways: application to cellular cytotoxicity readouts

Background: An in silico mechanism-of-action analysis protocol was developed, comprising molecule bioactivity profiling, annotation of predicted targets with pathways and calculation of enrichment factors to highlight targets and pathways more likely to be implicated in the studied phenotype. Results: The method was applied to a cytotoxicity phenotypic endpoint, with enriched targets/pathways found to be statistically significant when compared with 100 random datasets. Application on a smaller apoptotic set (10 molecules) did not allowed to obtain statistically relevant results, suggesting that the protocol requires modification such as analysis of the most frequently predicted targets/annotated pathways. Conclusion: Pathway annotations improved the mechanism-of-action information gained by target prediction alone, allowing a better interpretation of the predictions and providing better mapping of targets onto pathways.

Toxins and drug discovery

Components from venoms have stimulated many drug discovery projects, with some notable successes. These are briefly reviewed, from captopril to ziconotide. However, there have been many more disappointments on the road from toxin discovery to approval of a new medicine. Drug discovery and development is an inherently risky business, and the main causes of failure during development programmes are outlined in order to highlight steps that might be taken to increase the chances of success with toxin-based drug discovery. These include having a clear focus on unmet therapeutic needs, concentrating on targets that are well-validated in terms of their relevance to the disease in question, making use of phenotypic screening rather than molecular-based assays, and working with development partners with the resources required for the long and expensive development process.

Integrative approach in the era of failing drug discovery and development

The productivity decline in drug discovery and development is mainly caused by two factors; higher regulatory hurdles and low-hanging fruits being all picked. In addition, the recent target-based approach is thought to be increasing the price of innovation. Although target-based approach had many successes, a postreductionism method, which is systems biology, is on the rise. In this review, we discuss the foundations of two distinct approaches in finding a new drug.

Pain: novel analgesics from traditional Chinese medicines

The search for analgesics with fewer side effects and less abuse potential has had limited success. A recent study identifies an analgesic alkaloid compound from Corydalis yanhusuo, a traditional Chinese medicinal herb that has a surprising mechanism of action.