Back to the future - Is the drug repositioning concept applicable to vaccines?

Vaccine. 2018 Apr 13;:

Authors: Schwamborn K

PMID: 29661583 [PubMed - as supplied by publisher]

SPIDR: small-molecule peptide-influenced drug repurposing.

BMC Bioinformatics. 2018 Apr 16;19(1):138

Authors: King MD, Long T, Pfalmer DL, Andersen TL, McDougal OM

Abstract
BACKGROUND: Conventional de novo drug design is costly and time consuming, making it accessible to only the best resourced research organizations. An emergent approach to new drug development is drug repurposing, in which compounds that have already gone through some level of clinical testing are examined for efficacy against diseases divergent than their original application. Repurposing of existing drugs circumvents the time and considerable cost of early stages of drug development, and can be accelerated by using software to screen existing chemical databases to identify suitable drug candidates.
RESULTS: Small-molecule Peptide-Influenced Drug Repurposing (SPIDR) was developed to identify small molecule drugs that target a specific receptor by exploring the conformational binding space of peptide ligands. SPIDR was tested using the potent and selective 16-amino acid peptide α-conotoxin MII ligand and the α3β2-nicotinic acetylcholine receptor (nAChR) isoform. SPIDR incorporates a genetic algorithm-based, heuristic search procedure, which was used to explore the ligand binding domain of the α3β2-nAChR isoform using a library consisting of 640,000 α-conotoxin MII peptide analogs. The peptides that exhibited the highest affinity for α3β2-nAChR were used as models for a small-molecule structure similarity search of the PubChem Compound database. SPIDR incorporates the SimSearcher utility, which generates shape distribution signatures of molecules and employs multi-level K-means clustering to insure fast database queries. SPIDR identified non-peptide drugs with estimated binding affinities nearly double that of the native α-conotoxin MII peptide.
CONCLUSIONS: SPIDR has been generalized and integrated into DockoMatic v 2.1. This software contains an intuitive graphical interface for peptide mutant screening workflow and facilitates mapping, clustering, and searching of local molecular databases, making DockoMatic a valuable tool for researchers in drug design and repurposing.

PMID: 29661129 [PubMed - in process]

Potential repositioning of exemestane as a neuroprotective agent for Parkinson's disease.

Free Radic Res. 2017 Jun;51(6):633-645

Authors: Son HJ, Han SH, Lee JA, Shin EJ, Hwang O

Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterised by selective degeneration of the nigral dopaminergic neurons, and neuroinflammation and oxidative stress are believed to be involved in its pathogenesis. In the present study, we provide data that the synthetic steroid exemestane, which is currently being used to treat breast cancer, may be useful for PD therapy. In BV-2 microglial cells, exemestane activated the transcription factor Nrf2 and induced expression of the Nrf2-dependent genes that encode the antioxidant enzymes NAD(P)H: quinone oxidoreductase 1, haem oxygenase-1, and glutamylcysteine ligase. It also downregulated gene expression of inducible nitric oxide (NO) synthase, lowered the levels of NO and reactive oxygen species, interleukin-1β and tumour necrosis factor-α in lipopolysaccharide-activated microglial cells. In CATH.a dopaminergic neuronal cells, exemestane also induced the same set of Nrf2-dependent antioxidant enzyme genes and provided neuroprotection against oxidative damage. In vivo, the drug protected the nigral dopaminergic neurons, decreased microglial activation, and prevented motor deficits in C57Bl/6 male mice that had been administered with the dopaminergic neurotoxin MPTP. Taken together, the results suggested a utility of repositioning exemestane towards disease-modifying therapy for PD.

PMID: 28770670 [PubMed - indexed for MEDLINE]

Exploring the molecular mechanisms of Traditional Chinese Medicine components using gene expression signatures and connectivity map.

Comput Methods Programs Biomed. 2018 Apr 04;:

Authors: Yoo M, Shin J, Kim H, Kim J, Kang J, Tan AC

Abstract
BACKGROUND AND OBJECTIVE: Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the "multi-component, multi-target" nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map.
METHODS: We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource. We performed systematic data mining and analysis on the mechanism of action (MoA) of these TCM components based on the CMap results.
RESULTS: We clustered the 102 TCM components into four groups based on their MoAs using next generation CMap resource. We performed gene set enrichment analysis on these components to provide additional supports for explaining these molecular mechanisms. We also provided literature evidence to validate the MoAs identified through this bioinformatics analysis. Finally, we developed the Traditional Chinese Medicine Drug Repurposing Hub (TCM Hub) - a connectivity map resource to facilitate the elucidation of TCM MoA for drug repurposing research. TCMHub is freely available in http://tanlab.ucdenver.edu/TCMHub.
CONCLUSIONS: Molecular mechanisms of TCM could be uncovered by using gene expression signatures and connectivity map. Through this analysis, we identified many of the TCM components possess diverse MoAs, this may explain the applications of TCM in treating various symptoms and diseases.

PMID: 29650251 [PubMed - as supplied by publisher]

Realizing drug repositioning by adapting a recommendation system to handle the process.

BMC Bioinformatics. 2018 Apr 12;19(1):136

Authors: Ozsoy MG, Özyer T, Polat F, Alhajj R

Abstract
BACKGROUND: Drug repositioning is the process of identifying new targets for known drugs. It can be used to overcome problems associated with traditional drug discovery by adapting existing drugs to treat new discovered diseases. Thus, it may reduce associated risk, cost and time required to identify and verify new drugs. Nowadays, drug repositioning has received more attention from industry and academia. To tackle this problem, researchers have applied many different computational methods and have used various features of drugs and diseases.
RESULTS: In this study, we contribute to the ongoing research efforts by combining multiple features, namely chemical structures, protein interactions and side-effects to predict new indications of target drugs. To achieve our target, we realize drug repositioning as a recommendation process and this leads to a new perspective in tackling the problem. The utilized recommendation method is based on Pareto dominance and collaborative filtering. It can also integrate multiple data-sources and multiple features. For the computation part, we applied several settings and we compared their performance. Evaluation results show that the proposed method can achieve more concentrated predictions with high precision, where nearly half of the predictions are true.
CONCLUSIONS: Compared to other state of the art methods described in the literature, the proposed method is better at making right predictions by having higher precision. The reported results demonstrate the applicability and effectiveness of recommendation methods for drug repositioning.

PMID: 29649971 [PubMed - in process]

A systematic and prospectively validated approach for identifying synergistic drug combinations against malaria.

Malar J. 2018 Apr 11;17(1):160

Authors: KalantarMotamedi Y, Eastman RT, Guha R, Bender A

Abstract
BACKGROUND: Nearly half of the world's population (3.2 billion people) were at risk of malaria in 2015, and resistance to current therapies is a major concern. While the standard of care includes drug combinations, there is a pressing need to identify new combinations that can bypass current resistance mechanisms. In the work presented here, a combined transcriptional drug repositioning/discovery and machine learning approach is proposed.
METHODS: The integrated approach utilizes gene expression data from patient-derived samples, in combination with large-scale anti-malarial combination screening data, to predict synergistic compound combinations for three Plasmodium falciparum strains (3D7, DD2 and HB3). Both single compounds and combinations predicted to be active were prospectively tested in experiment.
RESULTS: One of the predicted single agents, apicidin, was active with the AC50 values of 74.9, 84.1 and 74.9 nM in 3D7, DD2 and HB3 P. falciparum strains while its maximal safe plasma concentration in human is 547.6 ± 136.6 nM. Apicidin at the safe dose of 500 nM kills on average 97% of the parasite. The synergy prediction algorithm exhibited overall precision and recall of 83.5 and 65.1% for mild-to-strong, 48.8 and 75.5% for moderate-to-strong and 12.0 and 62.7% for strong synergies. Some of the prospectively predicted combinations, such as tacrolimus-hydroxyzine and raloxifene-thioridazine, exhibited significant synergy across the three P. falciparum strains included in the study.
CONCLUSIONS: Systematic approaches can play an important role in accelerating discovering novel combinational therapies for malaria as it enables selecting novel synergistic compound pairs in a more informed and cost-effective manner.

PMID: 29642892 [PubMed - in process]

A two-tiered unsupervised clustering approach for drug repositioning through heterogeneous data integration.

BMC Bioinformatics. 2018 Apr 11;19(1):129

Authors: Hameed PN, Verspoor K, Kusljic S, Halgamuge S

Abstract
BACKGROUND: Drug repositioning is the process of identifying new uses for existing drugs. Computational drug repositioning methods can reduce the time, costs and risks of drug development by automating the analysis of the relationships in pharmacology networks. Pharmacology networks are large and heterogeneous. Clustering drugs into small groups can simplify large pharmacology networks, these subgroups can also be used as a starting point for repositioning drugs. In this paper, we propose a two-tiered drug-centric unsupervised clustering approach for drug repositioning, integrating heterogeneous drug data profiles: drug-chemical, drug-disease, drug-gene, drug-protein and drug-side effect relationships.
RESULTS: The proposed drug repositioning approach is threefold; (i) clustering drugs based on their homogeneous profiles using the Growing Self Organizing Map (GSOM); (ii) clustering drugs based on drug-drug relation matrices based on the previous step, considering three state-of-the-art graph clustering methods; and (iii) inferring drug repositioning candidates and assigning a confidence value for each identified candidate. In this paper, we compare our two-tiered clustering approach against two existing heterogeneous data integration approaches with reference to the Anatomical Therapeutic Chemical (ATC) classification, using GSOM. Our approach yields Normalized Mutual Information (NMI) and Standardized Mutual Information (SMI) of 0.66 and 36.11, respectively, while the two existing methods yield NMI of 0.60 and 0.64 and SMI of 22.26 and 33.59. Moreover, the two existing approaches failed to produce useful cluster separations when using graph clustering algorithms while our approach is able to identify useful clusters for drug repositioning. Furthermore, we provide clinical evidence for four predicted results (Chlorthalidone, Indomethacin, Metformin and Thioridazine) to support that our proposed approach can be reliably used to infer ATC code and drug repositioning.
CONCLUSION: The proposed two-tiered unsupervised clustering approach is suitable for drug clustering and enables heterogeneous data integration. It also enables identifying reliable repositioning drug candidates with reference to ATC therapeutic classification. The repositioning drug candidates identified consistently by multiple clustering algorithms and with high confidence have a higher possibility of being effective repositioning candidates.

PMID: 29642848 [PubMed - in process]

Emerging drugs for primary progressive multiple sclerosis.

Expert Opin Emerg Drugs. 2018 Apr 11;:

Authors: Narayan RN, Forsthuber T, Stüve O

Abstract
INTRODUCTION: While substantial progress has been made in the past three decades in treating relapsing forms of multiple sclerosis, the identification of effective therapies for progressive forms of multiple sclerosis (MS) has remained mostly elusive, and remains a priority and challenge for the global MS community. Although axonal degeneration in a setting of demyelination, failure of remyelination, neuronal death, axonal energy failure have been implicated in this disease process, a more complete understanding of the mechanisms involved in the pathogenesis of these MS phenotypes, animal models that incorporate these pathogenic characteristics, novel trial designs, drug repurposing strategies, and new models of collaboration between clinical and basic science personnel may be required in identifying effective therapies. Areas covered: Here, we review the current knowledge on putative pathogenic mechanisms in primary progressive MS (PPMS). Also, the rationale and outcomes of key phase II or III trial initiatives in PPMS are summarized. Future perspectives are outlined. Expert opinion: The recent approval of ocrelizumab is a major milestone forward in the therapy of PPMS. One reason for success of this drug is appropriate patient selection. The ultimate goal in PPMS therapy should be the reversal of disability, and the arrest of disease progression. However, a more realistic and reasonable short to mid-term goal could be to slow down disability. Our current understanding of PPMS suggests that a combination of immune-modulatory, myelin-restorative, and neuro-regenerative therapies particularly early in the disease course would be a reasonable strategy. Finally, selection of appropriate patients, selection of appropriate outcomes and monitoring therapy is again crucial for success of therapeutic strategies.

PMID: 29638150 [PubMed - as supplied by publisher]

Polypharmacology in the treatment of Chagas disease.

Curr Med Chem. 2018 Apr 09;:

Authors: Aguilera E, Alvarez G, Cerecetto H, Gonzalez M

Abstract
The current treatment of Chagas disease is based on monopharmacology where the used drugs have limited efficacy and severe side effects. In order to overcome these limitations some tools have been described including development or isolation of new drugs, drug repositioning, and polypharmacology. Here we review the polypharmacology strategy where compounds belonging to different structural chemotypes were combined in order to affect different biochemical pathways of T. cruzi parasite. Therefore ergosterol biosynthesis inhibitors, anti-inflammatory agents, cardiac dysfunction drugs, trypanothione reductase inhibitors, vitamins, between others, were combined looking for new anti-Chagas treatment. Natural products were also used in the application of this strategy.

PMID: 29637852 [PubMed - as supplied by publisher]

Drug repurposing in kidney disease.

Kidney Int. 2018 Apr 06;:

Authors: Panchapakesan U, Pollock C

Abstract
Drug repurposing, is the re-tasking of known medications for new clinical indications. Advantages, compared to de novo drug development, include reduced cost and time to market plus the added benefit of a known pharmacokinetic and safety profiles. Suitable drug candidates are identified through serendipitous observations, data mining, or increased understanding of disease mechanisms. This review highlights drugs suited for repurposing in kidney disease. The main cause of mortality in patients with chronic kidney disease is cardiovascular disease. Hence, we have included CV endpoints for the drugs. This review begins with candidates in acute kidney injury: vasodilators levosimendan and vitamin D, followed by candidates in CKD, with particular focus on diabetic kidney disease, autosomal dominant polycystic kidney disease, and focal segmental glomerulosclerosis. Examples include glucose-lowering drugs (sodium glucose co-transporter 2 inhibitors, glucagon-like peptide 1 agonists, and metformin), which have mechanistic potential for cardiac and/or renal protection beyond glucose lowering, with broader applicability to the nondiabetic population; xanthine oxidase inhibitors (allopurinol, febuxostat), selective endothelin receptor A antagonist (atrasentan), Janus kinase inhibitor (baricitinib), selective costimulation modulator (abatacept), pentoxyfylline, and the DNA demethylating agent/vasodilator (hydralazine).

PMID: 29628139 [PubMed - as supplied by publisher]

Identification of ST3AGL4, MFHAS1, CSNK2A2 and CD226 as loci associated with systemic lupus erythematosus (SLE) and evaluation of SLE genetics in drug repositioning.

Ann Rheum Dis. 2018 Apr 06;:

Authors: Wang YF, Zhang Y, Zhu Z, Wang TY, Morris DL, Shen JJ, Zhang H, Pan HF, Yang J, Yang S, Ye DQ, Vyse TJ, Cui Y, Zhang X, Sheng Y, Lau YL, Yang W

Abstract
OBJECTIVES: Systemic lupus erythematosus (SLE) is a prototype autoimmune disease with a strong genetic component in its pathogenesis. Through genome-wide association studies (GWAS), we recently identified 10 novel loci associated with SLE and uncovered a number of suggestive loci requiring further validation. This study aimed to validate those loci in independent cohorts and evaluate the role of SLE genetics in drug repositioning.
METHODS: We conducted GWAS and replication studies involving 12 280 SLE cases and 18 828 controls, and performed fine-mapping analyses to identify likely causal variants within the newly identified loci. We further scanned drug target databases to evaluate the role of SLE genetics in drug repositioning.
RESULTS: We identified three novel loci that surpassed genome-wide significance, including ST3AGL4 (rs13238909, pmeta=4.40E-08), MFHAS1 (rs2428, pmeta=1.17E-08) and CSNK2A2 (rs2731783, pmeta=1.08E-09). We also confirmed the association of CD226 locus with SLE (rs763361, pmeta=2.45E-08). Fine-mapping and functional analyses indicated that the putative causal variants in CSNK2A2 locus reside in an enhancer and are associated with expression of CSNK2A2 in B-lymphocytes, suggesting a potential mechanism of association. In addition, we demonstrated that SLE risk genes were more likely to be interacting proteins with targets of approved SLE drugs (OR=2.41, p=1.50E-03) which supports the role of genetic studies to repurpose drugs approved for other diseases for the treatment of SLE.
CONCLUSION: This study identified three novel loci associated with SLE and demonstrated the role of SLE GWAS findings in drug repositioning.

PMID: 29625966 [PubMed - as supplied by publisher]

Simvastatin Therapy for Drug Repositioning to Reduce the Risk of Prostate Cancer Mortality in Patients With Hyperlipidemia.

Front Pharmacol. 2018;9:225

Authors: Chen YA, Lin YJ, Lin CL, Lin HJ, Wu HS, Hsu HY, Sun YC, Wu HY, Lai CH, Kao CH

Abstract
Prostate cancer (PCa) is one of the most commonly diagnosed cancers in the western world, and the mortality rate from PCa in Asia has been increasing recently. Statins are potent inhibitors of 3-hydroxy-3-methyl glutaryl coenzyme A (HMG-CoA) reductase and are commonly used for treating hyperlipidemia, with beneficial effects for cardiovascular disease and they also exhibit anti-cancer activity. However, the protective effects of statins against PCa are controversial. In this study, we investigated the effect of two types of statins (simvastatin and lovastatin) and the mortality rate of PCa patients by using the Taiwan National Health Insurance Research Database (NHIRD). A total of 15,264 PCa patients with hyperlipidemia records and medical claims from the Registry of Catastrophic Illness were enrolled. The patients were divided into two cohorts based on their statin use before the diagnosis of PCa: statin users (n = 1,827) and non-statin users (n = 1,826). The results showed that patients who used statins exhibited a significantly reduced risk of mortality from PCa [adjusted hazard ratio (HR) = 0.84, 95% CI = 0.73-0.97]. Analysis of the cumulative defined daily dose (DDD) indicated that patients who were prescribed simvastatin ≥ 180 DDD had a dramatically decreased risk of death from PCa (adjusted HR = 0.63; 95% CI = 0.51-0.77). This population-based cohort study demonstrated that statin use significantly decreased the mortality of PCa patients, and that this risk was inversely associated with the cumulative DDD of simvastatin therapy. The results of this study revealed that statins may be used for drug repositioning and in the development of a feasible approach to prevent death from PCa.

PMID: 29623039 [PubMed]

Repositioning of difluorinated propanediones as inhibitors of histone methyltransferases and their biological evaluation in human leukemic cell lines.

Anticancer Agents Med Chem. 2018 Apr 04;:

Authors: Pal T, Sharda A, Khade B, Ramaa CS, Gupta S

Abstract
Cancer chemotherapy is associated with limitations like dose dependent host-tissue toxicity, multiple drug resistance and tumor heterogeneity. Hence, it is imperative to unearth novel targets to cure cancer. At present, 'pharmaco-epigenomics' constitutes the hope in cancer treatment owing to epigenetic deregulation- a reversible process, suspected of playing a role in malignancy. In this research work, we have used the fundamentals of drug repurposing for a set of our previously synthesized difluorinated propanediones and evaluated them for their histone methyltransferase inhibitory potential in leukemic cell lines. A small molecule inhibitor PR-4, at a concentration of 1 and 10μM, has shown to alter the methylation levels in two leukemic cell lines, one of histiocytic lymphoma (U937) and other of acute T-cell leukemia (JURKAT). Treatment with the compound shows an increase in G2/M population and a subsequent decrease in the G0/G1 population 24h post treatment in U937. In JURKAT, an increase in both G2/M and S phase population at 16 and 24h time point was observed. The sub-G1 population showed a steady rise with increase in dose and prolonged time intervals in U937 and JURKAT cell lines. In SRB assay, the moiety showed a cell growth of 42.6 % and 53.4% comparable to that of adriamycin; 44.5% and 53.2% in U937 and JURKAT, respectively. The apoptosis pattern suggests that this molecule could emerge as a potential anticancer agent by targeting histone methyltransferases. The molecule PR-4 could be a lead in developing more histone lysine methyltransferases inhibitors with potential to be anti-carcinogenic agents.

PMID: 29623853 [PubMed - as supplied by publisher]

Repurposing tofacitinib as an anti-myeloma therapeutic to reverse growth-promoting effects of the bone marrow microenvironment.

Haematologica. 2018 Apr 05;:

Authors: Lam C, Ferguson ID, Mariano MC, Lin YT, Murnane M, Liu H, Smith GA, Wong SW, Taunton J, Liu JO, Mitsiades CS, Hann BC, Aftab BT, Wiita AP

Abstract
The myeloma bone marrow microenvironment promotes proliferation of malignant plasma cells and resistance to therapy. Activation of JAK/STAT signaling is thought to be a central component of these microenvironment-induced phenotypes. In a prior drug repurposing screen, we identified tofacitinib, a pan-JAK inhibitor FDA-approved for rheumatoid arthritis, as an agent that may reverse the tumor-stimulating effects of bone marrow mesenchymal stromal cells. Here, we validated in vitro, in stromal-responsive human myeloma cell lines, and in vivo, in orthotopic disseminated xenograft models of myeloma, that tofacitinib showed efficacy in myeloma models. Furthermore, tofacitinib strongly synergized with venetoclax in co-culture with marrow stromal cells but not in monoculture. Surprisingly, we found that ruxolitinib, an FDA-approved agent targeting JAK1 and JAK2, did not lead to the same anti-myeloma effects. Combination with a novel irreversible JAK3-selective inhibitor also did not enhance ruxolitinib effects. RNA-seq and unbiased phosphoproteomics revealed that marrow stromal cells stimulate a JAK/STAT-mediated proliferative program in myeloma plasma cells, and tofacitinib reversed the large majority of these pro-growth signals. Taken together, our results suggest that tofacitinib reverses the growth-promoting effects of the tumor microenvironment. As tofacitinib is already FDA-approved, these results can be rapidly translated into potential clinical benefits for myeloma patients.

PMID: 29622655 [PubMed - as supplied by publisher]

Why Do Promising Therapies Stall in Development and How Can We Move Them Forward?

Int J Toxicol. 2017 Jul/Aug;36(4):340-349

Authors: Wegner CD, Goodwin A, Cook JC, Allamneni K, Sohn J, McVean M

Abstract
There are many reasons that molecules fail to progress to market and various principles of risk-benefit decisions that can help drive the molecule through development. This symposium included discussions on global strategies involved in pushing promising molecules to market, what to do when a molecule stalls in its progress to market, and options for rescuing the molecule and pushing it forward again. Innovative partnerships that bring stalled drugs back into clinical development were also addressed. A regulatory perspective on common reasons for a molecule to fail in its forward progress was presented. In addition, situations arise when a third-party advisory committee can provide input to help overcome issues identified by a regulatory agency. Using examples from the private and public domain, presentations centered on how to repurpose a molecule and when more science is needed.

PMID: 28578602 [PubMed - indexed for MEDLINE]

A systems pharmacology-oriented discovery of a new therapeutic use of the TCM formula Liuweiwuling for liver failure.

Sci Rep. 2018 Apr 04;8(1):5645

Authors: Wang JB, Cui HR, Wang RL, Zhang CE, Niu M, Bai ZF, Xu GH, Li PY, Jiang WY, Han JJ, Ma X, Cai GM, Li RS, Zhang LP, Xiao XH

Abstract
Multiple components of traditional Chinese medicine (TCM) formulae determine their treatment targets for multiple diseases as opposed to a particular disease. However, discovering the unexplored therapeutic potential of a TCM formula remains challenging and costly. Inspired by the drug repositioning methodology, we propose an integrated strategy to feasibly identify new therapeutic uses for a formula composed of six herbs, Liuweiwuling. First, we developed a comprehensive systems approach to enrich drug compound-liver disease networks to analyse the major predicted diseases of Liuweiwuling and discover its potential effect on liver failure. The underlying mechanisms were subsequently predicted to mainly attribute to a blockade of hepatocyte apoptosis via a synergistic combination of multiple effects. Next, a classical pharmacology experiment was designed to validate the effects of Liuweiwuling on different models of fulminant liver failure induced by D-galactosamine/lipopolysaccharide (GalN/LPS) or thioacetamide (TAA). The results indicated that pretreatment with Liuweiwuling restored liver function and reduced lethality induced by GalN/LPS or TAA in a dose-dependent manner, which was partially attributable to the abrogation of hepatocyte apoptosis by multiple synergistic effects. In summary, the integrated strategy discussed in this paper may provide a new approach for the more efficient discovery of new therapeutic uses for TCM formulae.

PMID: 29618826 [PubMed - in process]

Pimping up Drugs Recovered, Superannuated and Under Exploited Drugs - An Introduction to the Basics of Drug Reprofiling.

Curr Drug Discov Technol. 2017;14(2):121-126

Authors: Dilly SJ, Morris GS

Abstract
Drug development has moved along way forward from the days of with doctors peddling cauldrons of herbs and spices, however, the process can still miss opportunities for full exploitation of a drug's potential. Drug reprofiling provides a chance for an established or a forgotten drug to move into a new area of therapy, whether related to the known effects or in a completely new area. In an era of environmental awareness and spiraling costs for traditional drug development, a strategy to squeeze every benefit out of drugs with known safety, tolerability and pharmacological parameters must be a strategically sound desire. We explore examples of success in reprofiling, draw comparisons between techniques, and finally provide two examples from the Valirx plc development pipeline currently undergoing the process.

PMID: 28124597 [PubMed - indexed for MEDLINE]

Drug Repositioning in Glioblastoma: A Pathway Perspective.

Front Pharmacol. 2018;9:218

Authors: Tan SK, Jermakowicz A, Mookhtiar AK, Nemeroff CB, Schürer SC, Ayad NG

Abstract
Glioblastoma multiforme (GBM) is the most malignant primary adult brain tumor. The current standard of care is surgical resection, radiation, and chemotherapy treatment, which extends life in most cases. Unfortunately, tumor recurrence is nearly universal and patients with recurrent glioblastoma typically survive <1 year. Therefore, new therapies and therapeutic combinations need to be developed that can be quickly approved for use in patients. However, in order to gain approval, therapies need to be safe as well as effective. One possible means of attaining rapid approval is repurposing FDA approved compounds for GBM therapy. However, candidate compounds must be able to penetrate the blood-brain barrier (BBB) and therefore a selection process has to be implemented to identify such compounds that can eliminate GBM tumor expansion. We review here psychiatric and non-psychiatric compounds that may be effective in GBM, as well as potential drugs targeting cell death pathways. We also discuss the potential of data-driven computational approaches to identify compounds that induce cell death in GBM cells, enabled by large reference databases such as the Library of Integrated Network Cell Signatures (LINCS). Finally, we argue that identifying pathways dysregulated in GBM in a patient specific manner is essential for effective repurposing in GBM and other gliomas.

PMID: 29615902 [PubMed]

Computational repositioning and preclinical validation of mifepristone for human vestibular schwannoma.

Sci Rep. 2018 Apr 03;8(1):5437

Authors: Sagers JE, Brown AS, Vasilijic S, M Lewis R, Sahin MI, Landegger LD, Perlis RH, Kohane IS, Welling DB, Patel CJ, Stankovic KM

Abstract
The computational repositioning of existing drugs represents an appealing avenue for identifying effective compounds to treat diseases with no FDA-approved pharmacotherapies. Here we present the largest meta-analysis to date of differential gene expression in human vestibular schwannoma (VS), a debilitating intracranial tumor, and use these data to inform the first application of algorithm-based drug repositioning for this tumor class. We apply an open-source computational drug repositioning platform to gene expression data from 80 patient tumors and identify eight promising FDA-approved drugs with potential for repurposing in VS. Of these eight, mifepristone, a progesterone and glucocorticoid receptor antagonist, consistently and adversely affects the morphology, metabolic activity, and proliferation of primary human VS cells and HEI-193 human schwannoma cells. Mifepristone treatment reduces VS cell viability more significantly than cells derived from patient meningiomas, while healthy human Schwann cells remain unaffected. Our data recommend a Phase II clinical trial of mifepristone in VS.

PMID: 29615643 [PubMed - in process]

Symptomatic thinking: the current state of Phase III and IV clinical trials for cognition in schizophrenia.

Drug Discov Today. 2017 Jul;22(7):1017-1026

Authors: Talpos JC

Abstract
Research indicates that relieving the cognitive and negative symptoms of schizophrenia is crucial for improving patient quality of life. However effective pharmacotherapies for cognitive and negative symptoms do not currently exist. A review of ongoing Phase III clinical trials indicates that, despite numerous compounds being investigated for cognition in schizophrenia, few are actually novel and most are not backed by empirically driven preclinical research efforts. Based on these trials, and a general disinvestment in development of novel therapies for schizophrenia, the likelihood of a major advancement in treating cognitive differences in schizophrenia does not look promising. Possible ways in which the remaining resources for development of novel treatment for schizophrenia can best be leveraged are discussed.

PMID: 28461223 [PubMed - indexed for MEDLINE]