Multidrug Combination Research Articles

Biomarker-focused multi-drug combination therapy and repurposing trial in mdx mice.

Duchenne muscular dystrophy is initiated by dystrophin deficiency, but downstream pathophysiological pathways such as membrane instability, NFĸB activation, mitochondrial dysfunction, and induction of TGFβ fibrosis pathways are thought to drive the disability. Dystrophin replacement strategies are hopeful for addressing upstream dystrophin deficiency; however, all methods to date use semi-functional dystrophin proteins that are likely to trigger downstream pathways. Thus, combination therapies that can target multiple downstream pathways are important in treating DMD, even for dystrophin-replacement strategies. We sought to define blood pharmacodynamic biomarkers of drug response in the mdx mouse model of Duchenne muscular dystrophy using a series of repurposed drugs. Four-week-old mdx mice were treated for four weeks with four different drugs singly and in combination: vehicle, prednisolone, vamorolone, rituximab, β-aminoisobutyric acid (BAIBA) (11 treatment groups; n = 6/group). Blood was collected via cardiac puncture at study termination, and proteomic profiling was carried out using SOMAscan aptamer panels (1,310 proteins assayed). Prednisolone was tested alone and in combination with other drugs. It was found to have a good concordance of prednisolone-responsive biomarkers (56 increased by prednisolone, 39 decreased) focused on NFκB and TGFβ cascades. Vamorolone shared 45 (80%) of increased biomarkers and 13 (33%) of decreased biomarkers with prednisolone. Comparison of published human corticosteroid-responsive biomarkers to our mdx data showed 14% (3/22) concordance between mouse and human. Rituximab showed fewer drug-associated biomarkers, with the most significant being human IgG. On the other hand, BAIBA treatment (high and low dose) showed a drug-associated increase in 40 serum proteins and decreased 5 serum proteins. Our results suggest that a biomarker approach could be employed for assessing drug combinations in both mouse and human studies.

Network Pharmacology Interpretation of Fuzheng-Jiedu Decoction against Colorectal Cancer.

Introduction Traditional Chinese medicine (TCM) believes that the pathogenic factors of colorectal cancer (CRC) are “deficiency, dampness, stasis, and toxin,” and Fuzheng–Jiedu Decoction (FJD) can resist these factors. In this study, we want to find out the potential targets and pathways of FJD in the treatment of CRC and also explain from a scientific point of view that FJD multidrug combination can resist “deficiency, dampness, stasis, and toxin.” Methods We get the composition of FJD from the TCMSP database and get its potential target. We also get the potential target of colorectal cancer according to the OMIM Database, TTD Database, GeneCards Database, CTD Database, DrugBank Database, and DisGeNET Database. Subsequently, PPI analysis, KEGG pathways analysis, and GO biological processes analysis were carried out for the target of FJD in the therapy of colorectal cancer. In addition, we have also built a relevant network diagram. Results In this study, we identified four core compounds of FJD in the therapy of colorectal cancer, including quercetin, kaempferol, beta-sitosterol, and stigmasterol. At the same time, we also obtained 30 core targets, including STAT3, INS, TP53, VEGFA, AKT1, TNF, IL6, JUN, EGF, CASP3, MAPK3, MAPK1, MAPK8, SRC, IGF1, CCND1, ESR1, EGFR, PTEN, MTOR, FOS, PTGS2, CXCL8, HRAS, CDH1, BCL2L1, FN1, MMP9, ERBB2, and JAK2. FJD treatment of colorectal cancer mainly involves 112 KEGG pathways, including FoxO (hsa04068) signaling pathway, PI3K-Akt (hsa04151) signaling pathway, HIF-1 (hsa04066) signaling pathway, T cell receptor (hsa04660) signaling pathway, and ErbB (hsa04012) signaling pathway. At the same time, 330 GO biological processes were summarized, including cell proliferation, cell apoptosis, angiogenesis, inflammation, and immune. Conclusions In this study, we found that FJD can regulate cell proliferation, apoptosis, inflammation and immunity, and angiogenesis through PI3K-Akt signaling pathway to play an anti-CRC effect.

Network Patterns of Herbal Combinations in Traditional Chinese Clinical Prescriptions.

As a well-established multidrug combinations schema, traditional Chinese medicine (herbal prescription) has been used for thousands of years in real-world clinical settings. This paper uses a complex network approach to investigate the regularities underlying multidrug combinations in herbal prescriptions. Using five collected large-scale real-world clinical herbal prescription datasets, we construct five weighted herbal combination networks with herb as nodes and herbal combinational use in herbal prescription as links. We found that the weight distribution of herbal combinations displays a clear power law, which means that most herb pairs were used in low frequency and some herb pairs were used in very high frequency. Furthermore, we found that it displays a clear linear negative correlation between the clustering coefficients and the degree of nodes in the herbal combination network (HCNet). This indicates that hierarchical properties exist in the HCNet. Finally, we investigate the molecular network interaction patterns between herb related target modules (i.e., subnetworks) in herbal prescriptions using a network-based approach and further explore the correlation between the distribution of herb combinations and prescriptions. We found that the more the hierarchical prescription, the better the corresponding effect. The results also reflected a well-recognized principle called “Jun-Chen-Zuo-Shi” in TCM formula theories. This also gives references for multidrug combination development in the field of network pharmacology and provides the guideline for the clinical use of combination therapy for chronic diseases.

Mathematical Flaws of Commonly Used Calculating Methods of Multi-drug Combination and Solution Based on One Belt and One Line Model Method

Mathematical Flaws of Commonly Used Calculating Methods of Multi-drug Combination and Solution Based on One Belt and One Line Model Method

Hydrophilic hindering and hydrophobic growing: a vesicle glycometabolism multi-drug combination therapeutic against Alzheimer's disease.

Advanced drug vehicle exploitation and the sophisticated synergy mechanism revelation are two great difficulties in combination therapy. Compared with most readily available polymer micelles, some undiscovered complex chemical design principles limit the expanding research of polymer vesicles. Here, polycaprolactone (PCL)-g-Dextran vesicle that dextran brush steric hindrance guide PCL lamellae-aligned growth was synthesized. The effect of the glycometabolism multi-drug vesicle combination treatment and synergism mechanism were investigated on senescence-accelerated mouse prone 8 (SAMP8) mice. The main insulin sensitizer drug could improve the memory ability of mice to a small extent, and the main insulin secretion promoter drug had little beneficial effect. Moreover, the triple anti-insulin resistant drugs of insulin (INS), repaglinide (REP) and metformin hydrochloride (MET) activated the glycometabolism-related bio-signals, and the energy cycle was normalized successfully. The insulin intracellular uptake and utilization efficiency could be the reason for the gap. The upregulation of the brain-derived neurotrophic factor (BDNF) protein confirmed that the crosstalk between the mitochondria and synapse contributes to the nerve repair. This study provided an excellent drug combination vesicle to treat Alzheimer's disease (AD). The discovery of the combination mechanism leads to an improvement in the AD clinical treatment.

Hydrophilic polymer driven crystallization self-assembly: an inflammatory multi-drug combination nanosystem against Alzheimer's disease.

The hydrophobic polymer driven crystallization of self-assembled micelles is usually sufficient for their purposes in materials chemistry studies. However, with the state of smart drug delivery research, micelles alone are not enough. The principles of the self assembly driven by hydrophilic dextran brushes together with charged poly(3-acrylamidophenyl boronic acid) (PPBA) are uncovered in this study. A series of poly(ε-caprolactone)-block-poly(3-acrylamidophenyl boronic acid)-dextran (PCL-b-PPBA-Dex) micelles and vesicles are investigated as potential Alzheimer's disease (AD) treatments. Three inflammatory microenvironment responsive micelles, including celecoxib drug-loaded micelles (CEL), ibuprofen drug-loaded micelles (IBU) and telmisartan drug-loaded micelles (TEL), are developed. In vivo, CEL/IBU (mixture of CEL and IBU) and CEL/TEL (mixture of CEL and TEL) suppress the activation of glia and reduce the levels of inflammatory mediators through eliminating cyclooxygenase 2 (COX-2) signals. The CEL/TEL combination nanosystem is better at correcting neuroinflammation and improving the spatial memory ability of a senescence-accelerated mouse prone 8 model (SAMP8). We consider that the inflammation responsive combination nanosystem provides a new potential treatment for AD clinical patients.

Multi-drug combination designs with experiments in silico

Multi-drug combination designs with experiments in silico

Combination Therapy of Alpha-Glucosidase Inhibitor, Thiazolidinedione and Sodium Glucose Co-Transporter-2 Inhibitor in Japanese Type 2 Diabetes Patients

Background: We additionally administered selective inhibitor of sodium glucose co-transporter-2 (SGLT2) inhibitor to type 2 diabetic patients on alpha-glucosidase inhibitor (alpha-GI) and/or thiazolidinedione (TZD), to determine whether the multi-drug combination therapy including SGLT2 inhibitor further improved the glycemic control in Japanese patients with diabetes mellitus. Methods: The subjects were divided into four groups. Group I was administered an SGLT2 inhibitor in addition to ongoing treatment using hypoglycemic agents other than alpha-GI and SGLT2 inhibitor. Group II was administered an SGLT2 inhibitor in addition to an alpha-GI. Group III was administered an SGLT2 inhibitor in addition to a TZD. Group IV was administered an SGLT2 inhibitor in addition to an alpha-GI and TZD. The body weight and biochemical parameters were measured before and 1, 2 and 3 years after the start of SGLT2 inhibitor treatment. Results: In patients receiving alpha-GI or TZD, additional administration of an SGLT2 inhibitor resulted in a reduction of the body weight, body mass index (BMI) and serum uric acid level, but had little effect on the glucose or lipid metabolism. On the other hand, additional administration of SGLT2 inhibitor in patients receiving both alpha-GI and TZD (three-drug combination therapy) resulted not only in a reduction of the body weight, BMI and serum uric acid, but also in improvement of the glucose and lipid metabolism, with a reduction of the hemoglobin A1c level and increase of the serum high-density lipoprotein cholesterol level. Conclusion: The results suggest that three-drug combination therapy with alpha-GI, TZD and SGLT2 inhibitor, each of which has different mechanism of action, is beneficial for the treatment of type 2 diabetes mellitus. J Endocrinol Metab. 2020;10(6):167-172 doi: https://doi.org/10.14740/jem708

Predicting and Quantifying Antagonistic Effects of Natural Compounds Given with Chemotherapeutic Agents: Applications for High-Throughput Screening.

Simple SummaryIncreasing numbers of cancer patients are turning to complementary and alternative medicines (CAM) to facilitate or replace their cancer treatments, or they are obtaining natural products in their diet. This is concerning, as there is evidence of molecular interactions between these bioactive compounds and cancer drugs that can impede or reverse their efficacy and prevent cancer regression. High-throughput drug screening and deep learning techniques have successfully been applied in the past to evaluate synergistic cancer drug and natural product combinations. However, these techniques should be applied more commonly in the context of drug antagonism to uncover potentially harmful interactions and drive safer recommendations for cancer patients. In this review, we evaluate the antagonistic interactions between natural products and chemotherapeutics and highlight how the application of high-throughput screening and deep learning techniques can strengthen this area of research. Natural products have been used for centuries to treat various human ailments. In recent decades, multi-drug combinations that utilize natural products to synergistically enhance the therapeutic effects of cancer drugs have been identified and have shown success in improving treatment outcomes. While drug synergy research is a burgeoning field, there are disagreements on the definitions and mathematical parameters that prevent the standardization and proper usage of the terms synergy, antagonism, and additivity. This contributes to the relatively small amount of data on the antagonistic effects of natural products on cancer drugs that can diminish their therapeutic efficacy and prevent cancer regression. The ability of natural products to potentially degrade or reverse the molecular activity of cancer therapeutics represents an important but highly under-emphasized area of research that is often overlooked in both pre-clinical and clinical studies. This review aims to evaluate the body of work surrounding the antagonistic interactions between natural products and cancer therapeutics and highlight applications for high-throughput screening (HTS) and deep learning techniques for the identification of natural products that antagonize cancer drug efficacy.

LINC-12. COMBINED ADULT AND PAEDIATRIC NEURO-ONCOLOGY LONG-TERM SURVIVOR CLINIC EXPERIENCE FROM A TERTIARY CANCER CENTRE IN A LOW-MIDDLE-INCOME COUNTRY

NeuroOncology survivor clinics (NOS) is uncommon in low-middle-income countries. We started combined (paediatric and adult) NOS clinic in our tertiary a cancer centre (Jan-2017) and review here the demographic, clinical-pathological and treatment spectrum for our paediatric (0-18years) and adult (>18years) survivors (>5years since their initial diagnosis) till date. Of total 312 patients registered, 198 (63.5%) were adults while 114 (36.5%) were paediatric at-diagnosis with median age (IQR) at presentation: 34 (23–41) and 9(6 – 13) years respectively. In both groups, only 33% were females. The median (IQR) time since diagnosis was 9 (9–14) and 8 (6–12) years respectively with 60% of paediatric turning into adult survivors. The commonest paediatric tumours were glioma (52, 45.6%), embryonal (34, 29.8%), and ependymoma (12, 10.5%) versus gliomas (114, 57.6%) and benign tumours (42, 21.2%) in adults. The low-grade-glioma comprised 90.4% of all pediatric gliomas and intermediate-grade (90%) in adults. The primary treatment consisted of radiotherapy and chemotherapy in 95% and 43% versus 99% and 36% in adults versus paediatric patients respectively. Temozolomide and multi-drug combinations were the commonest chemotherapy used in adults and paediatrics respectively. Relapse and retreatments were seen in 16.6 and 14% of adults and paediatric patients. There were two deaths each in each group since registration (median 12 months). Although the baseline diagnosis/treatment characteristics are different, survivors of both group had a similar number of retreatments and deaths. Combined survivor clinics may present an interesting and unique opportunity to learn and provide challenging service in this part of the world.

Epidemiology and microbiology of Gram-negative bloodstream infections in a tertiary-care hospital in Beijing, China: a 9-year retrospective study

ABSTRACT Background: Gram-negative bacterial bloodstream infections (BSIs) are associated with high morbidity and mortality. The present study examines the incidence, clinical characteristics, microbiological features, drug resistance and mortality associated with Gram-negative bacterial BSIs at a tertiary-care hospital in Beijing, China. Methods: This retrospective cohort study of patients with Gram-negative bacterial BSIs was performed between 1 January 2010 and 31 December 2018 at the Chinese People,s Liberation Army General Hospital. Results: A total of 6867 episodes of Gram-negative bacterial BSIs occurred among 3199 patients over 9 years. The overall incidence of Gram-negative bacterial BSIs fluctuated from 2.30 to 2.55 episodes per 1000 admissions over 9 years. Escherichia coli was the major pathogen (34.3%). The antibiotic resistance of ESBLs-producing E. coli was higher than non-ESBLs producing E. coli including the majority of antibiotics, but to carbapenems (0.7% VS 5.1%). Between 2010 and 2018, the overall mortality of Gram-negative bacterial BSIs decreased from 11.41% to 9.05% (X2 = 6.95, P = 0.434). Conclusions: Cephalosporins and carbapenem antibiotics were considered as the optimal treatment for patients with Gram-negative bacterial BSIs except for A. baumannii, which was treated according to the drug sensitivity or multidrug combination.

Advances in Drug Therapy for Alzheimer\u2019s Disease

SummaryAlzheimer’s disease (AD) is a chronic neurodegenerative disease that mainly causes dementia. It is a serious threat to the health of the global elderly population. Considerable money and effort has been invested in the development of drug therapy for AD worldwide. Many drug therapies are currently under development or in clinical trials, based on two known mechanisms of AD, namely, Aβ toxicity and the abnormal Tau hyperphosphorylation. Numerous drugs are also being developed for other AD associated mechanisms such as neuroinflammation, neurotransmitter imbalance, oxidative damage and mitochondrial dysfunction, neuron loss and degeneration. Even so, the number of drugs that can successfully improve symptoms or delay the progression of the disease remains very limited. However, multi-drug combinations may provide a new avenue for drug therapy for AD. In addition, early diagnosis of AD and timely initiation of treatment may allow drugs that act on the early pathological processes of AD to help improve the symptoms and prevent the progression of the condition.

Compromise design for combination experiment of two drugs

Preclinical experiment on two-drug combination is a stepping stone to multi-drug combination studies. Experimental designs have been proposed in the literature to test the presence of synergism between the combined drugs. However, a design that is efficient for synergy testing is not necessarily desirable for dose–response modeling and the latter is important for future development on drug interaction analysis. This work proposes an experimental design, called a compromise design to meet the dual requirements on synergy testing and dose–response modeling. The key idea of the design is to spread the design points uniformly on a pair of design regions where synergy testing and dose–response modeling are respectively carried out. Simulations and two illustrative examples are given to demonstrate the usefulness of the compromise design. In the illustrative examples, the good balance of the proposed design is visualized by 2-D projections of the design points. The simulation results indicate that the compromise design performs satisfactorily in terms of both testing power and model prediction accuracy.

A review of current progress in triple-negative breast cancer therapy.

Triple-negative breast cancer (TNBC) is a particularly aggressive subtype known for its extremely high drug resistance, progression, poor prognosis, and lack of clear therapeutic targets. Researchers are aiming to advance TNBC treatment worldwide. In the past 2–3 years, more positive results have emerged in the clinical research on TNBC treatment. Based on the results, several impressive drugs have been approved to benefit patients with TNBC, including the PARP inhibitors olaparib and talazoparib for germline BRCA mutation-associated breast cancer (gBRCAm-BC) and immunotherapy using the checkpoint inhibitor atezolizumab in combination with nab-paclitaxel for programmed cell death-ligand 1-positive (PD-L1+) advanced TNBC. Although neoadjuvant therapy has focused on combinations of systemic agents to optimize pathologically complete response, metastatic TNBC still has a poor prognosis. Innovative multidrug combination systemic therapies based on neoadjuvants and adjuvants have led to significant improvements in outcomes, particularly over the past decade.

Treatment Options for Newly Diagnosed Frail and Transplant-Ineligible Patients with Multiple Myeloma: A Systematic Review

Introduction: With progressive aging of the worldwide population, the number of newly diagnosed multiple myeloma (NDMM) cases are anticipated to escalate. Disease management for elderly, frail, and transplant-ineligible patients still remains a challenge. With our systematic review, we plan to summarize the available therapeutic options for frail, elderly, and transplant-ineligible NDMM patients. Methods: A comprehensive literature search was performed on May 27, 2020 on PubMed, Cochrane Library, and ClinicalTrials.gov. The search was not limited to any geographical area, date, or language. The keywords used in the search were: newly diagnosed, multiple myeloma, frail, elderly, transplant-ineligible, and treatment outcome. After subsequent screening, following the PRISMA guidelines, 24 ongoing/completed studies (n= 10,095) were included in the review. Results: Two and three drug combination regimens: Among the two and three drug combinations (see tables 1 and 2), lenalidomide (R) and dexamethasone (d) (Rd) combination (n=1445) and bortezomib (V), melphalan (M) and prednisone (P) (VMP) combination (n=1059) have been the most extensively studied combinations thus far. In a phase 2 trial, Takezako et al. (2016) used 9 cycles of VMP followed by bortezomib maintenance exclusively in frail patients, which yielded an ORR of 87%, CR rate of 25%, and PFS of 36 months. The addition of bortezomib (V) to Rd (VRd) was also studied in a phase 3 (SWOG S0777) trial by Durie et al. (2017) (n=471) in transplant-ineligible patients, which showed superior therapeutic response rates (PFS 43 months, OS of 75 months, and ORR of 82%) in the VRd group compared to Rd (PFS of 30 months, OS of 64 months and ORR of 72%) alone. However, the three-drug combination of daratumumab (Dara)+Rd has overall shown the best treatment results (ORR 92.9%, CR 47.6% and VGPR 31.8%) as evidenced by Facon et. al (2019) (n=368). Although, when compared to Rd, Dara-Rd was associated with more neutropenia (50% versus 35.3%); however, Dara-Rd had an overall lower incidence of infections (32.1% versus 73.4%) and hence, lower discontinuation rate (32.4% versus 56.7%) when compared to Rd, respectively. Four or five drug combination regimens: Four and five drug combinations have been studied in two phase II/III trials (n=933) in transplant-ineligible patients. A phase two trial (Mateos, 2015) studying VMPRd in frail patients resulted in an ORR of 68%, CR 20%, and PFS of 25 months after 35 days of VMPRd induction, followed by dose de-escalation to twice monthly bortezomib-only maintenance until disease progression. Dara-VMP was compared with VMP alone in a phase 3 trial (Mateos, 2017) (n=700), in which 9 cycles of Dara-VMP (42 days each) were de-escalated to daratumumab-only maintenance. Thisshowed superior results in Dara-VMP (ORR 90.9% versus 73.9%, CR 42.6% versus 24.4%, and PFS was not reached in Dara-VMP group versus 18.1 months) compared to the VMP group. Moreover, this dose de-escalation also seemed to improve treatment tolerability, as the discontinuation rate due to adverse effects was also lower (4.9%). Currently, various trials are ongoing to explore the connection between frailty status and associated treatment outcomes (table 3). Conclusion: Combination regimens, including agents like daratumumab and bortezomib, have exhibited promising results both in terms of superior efficacy and reduced adverse effects profiles. In addition, dose de-escalated maintenance therapies following induction therapies based on multidrug combinations have exhibited noteworthy success, with comparable efficacy and reduced toxicity rates in frail and transplant-ineligible NDMM patients. However, there remains an opportunity to further tailor the dose and type of drug combinations on a 'frailty-adjusted' basis, with trials designed around this risk stratification providing the highest quality data. Disclosures Anwer: Incyte, Seattle Genetics, Acetylon Pharmaceuticals, AbbVie Pharma, Astellas Pharma, Celegene, Millennium Pharmaceuticals.: Honoraria, Research Funding, Speakers Bureau.

A Systematic Review of High Dose Chemotherapy with Autologous Transplantation in Secondary CNS Lymphoma

Introduction: Secondary Central Nervous System Lymphoma (SCNSL) is the spread of a lymphoma to the CNS, the primary focus of which is situated elsewhere in the body. Most commonly, it is a non-Hodgkin lymphoma which either presents as a CNS involvement due to systemic relapse or progression, or as an isolated relapse in the CNS despite systemic remission. Traditionally, it has been treated by intrathecal or systemic chemotherapy and/or WBRT (Whole-brain radiation therapy) but recently, the use of high-dose chemotherapy (HDT) with autologous stem cell transplantation (ASCT) has shown encouraging results. We present a systematic review of literature displaying the treatment outcomes of HDT/ASCT in SCNSL. Methods: We performed a comprehensive literature search (following PRISMA guidelines) on July 08 2020 on PubMed, Cochrane Library and Clinicaltrials.Gov by using the relevant MeSH terms of high-dose chemotherapy, autologous stem cell transplantation, CNS lymphoma, efficacy and safety. Following screening by 2 reviewers, we selected 12 published studies (n=353) and included data from these studies in our systematic review. We manually extracted data summarized the results. Results: 232/353 patients eventually underwent sequential HDT+ASCT who were evaluable for treatment response out of which 190 patients had SCNSL (see table 1). Carmustine (BCNU) based HDT: BCNU based regimens have been the most extensively studied HDT among SCNSL patients (n=81). Korfel et al. in a phase 2 trial (2013, n=30) used HDT combination of BCNU, thiotepa and etoposide followed by ASCT in SCNSL patients. No patient was given whole brain radiation therapy (WBRT). The results yielded a PR of 8%, CR of 63% and 2-year OS of 63%. 1 toxicity related mortality (TRM) was noted and >grade 4 adverse effects included infection (4%) and stomatitis (13%). Ferreri et al. (2015, n=38) in a phase 2 trial use HDT with BCNU plus thiotepa on 38 patients 20 of whom underwent subsequent ASCT. The results showed CR of 100%, event free survival (EFS) of 40% ±9% and OS of 41% ±8% at 5 years with four patients suffering TRM. Thiotepa, busulfan and cyclophosphamide (TBC) based HDT: The combination based on TBC has been a popular option for SCNSL patients (n=53). In a retrospective analysis by Welch et al. (2014, n=17), TBC combination followed by sequential ASCT was studied in both primary and SCNSL patients (primary malignancy being diffuse large B-cell lymphoma) and the collective results showed complete response (CR) of 100%, PFS of 93% (95% CI: 61-99%) and OS of 93% (95% CI: 61-99%) at 3 years. In addition to the excellent efficacy response, no TRM or grade 4 toxicities were documented. Chen et al. (2015, n=12) in a phase 2 trial used HDT with rituximab and TBC (R-TBC) combination followed by ASCT rescue in 12 SCNSL patients. At 2 years, the progression free survival (PFS) was 51% (95% CI: 18-77%) and overall survival (OS) was 83% (95% CI: 48-96%). Two patients developed neurotoxicity and one TRM was recorded. Methotrexate (MTX) based HDT: MTX based combinations have also been widely used as HDT preceding ASCT in SCNSL patients (n=51). Fischer et al. (2008, n=20) studied HDT of MTX plus ifosfamide (IFO) in a retrospective analysis which showed PR of 30%, CR of 60% and median OS of 8.7 months and two TRM (due to sepsis in neutropenia) in SCNSL patients. Lee et al. (2015, n=31) in a prospective cohort study evaluated HDT with MTX based multidrug combination with ASCT in SCNSL patients which yielded a PR of 41.6%, CR of 50% and OS of 9 months (95% CI: 5-12 months). Five patients had suffered TRM. Conclusion: The combination of HDT with ASCT has yielded promising treatment outcomes both in terms of favorable efficacy rates and reduced rates of toxicity in SCNSL patients proving to be a comparable alternative to traditionally used chemo-radiation. However, the data at present is limited to few phase 2 trials with some being displayed collectively with data of primary CNS lymphoma patients. There is an increased need to carry out randomized phase 3 trials exclusively on SCNSL patients to better predict the efficacy and safety profile of HDT/ASCT in these patients. Disclosures Anwer: Incyte, Seattle Genetics, Acetylon Pharmaceuticals, AbbVie Pharma, Astellas Pharma, Celegene, Millennium Pharmaceuticals.: Honoraria, Research Funding, Speakers Bureau.

Novel SARS-CoV-2 and COVID-2019 Outbreak: Current Perspectives on Plant-Based Antiviral Agents and Complementary Therapy

Abstract: The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused the novel Corona Virus Disease 2019 (COVID-19), which has been defined as a pandemic by the World Health Organization (WHO) in 2020. The rapid global spread of SARS-CoV-2 virus as a global health emergency has emphasized to findeffective treatment strategies in clinical trials. The several drug trials including Lopinavir (LPV) and Ritonavir, Chloroquine (CLQ), Hydroxychloroquine, Favipiravir (FPV), Remdevisir (RDV), Nitazoxanide, Ivermectin and Interferon, have been explored in COVID-19 patients and some of the drugs have been waiting clinical approval for their anti-SARS-CoV-2 activities. Clinical trials are still ongoing to discover promising new multidrug combination treatment for COVID-19 patients. Considering the difficulties to ascertain efficient drug candidates and the lack of specific anti-viral therapies against COVID-19 outbreak, the current management of SARS-CoV-2 should mainly be supportive. From this point of view, enhancing the immune system through medicinal plants with wide range of bioactive compounds, which exhibit antiviral activities, can play significant roles to increase defense barrier in COVID-19 patients. On the other hand, plant-based agents as complementary and alternative therapies have potential advantages to reduce symptoms of this life-threatening disease and could promote the public health. Recently, there has been a remarkable progress in the field of antiviral herbal therapy owing to increasing concerns about the development of drug resistance and limited advances in the field of antiviral drug discovery. This review provides an overview of published information onbiology, genomic structure, replication cycle and pathogenesis of SARS-CoV-2. It also aims to assemble the fact and a scientific intellectual groundwork on development of antiviral herbal therapy on the bases of extensive literature collection. Key words: SARS-CoV-2, COVID-19, Outbreak, Medicinal plants, Antiviral.

Investigations on a polyherbal formulation for treatment of cognitive impairment in a cholinergic dysfunctional rodent model

Alzheimer's disease is a multifactorial neurodegenerative condition manifested through acute cognitive decline, amyloid plaque deposits and neurofibrillary tangles. Complete cure for this disease remains elusive as the conventional drugs address only a single molecular target while Alzheimer's disease involves a complex interplay of different sets of molecular targets and signaling networks. In this context, the possibility of employing multi-drug combinations to rescue neurons from the dysregulated metabolic changes is being actively investigated. The present work investigates a poly-herbal formulation, Brahmi Nei that has been traditionally used for anxiolytic disorders and immunomodulatory effects, for its efficiency in ameliorating cognitive decline through a combination of behavioral, biochemical, histopathological, gene and protein expression analyses. Our results reveal that the formulation shows excellent neuroregenerative properties, rescues neurons from inflammatory damage, reduces neuritic plaque deposits and improves working memory in rodent models with scopolamine-induced dementia. The microarray analysis shows that the formulation induces the expression of pro-survival pathways and positively modulates genes involved in memory consolidation, axonal growth and proliferation in a concentration-dependent manner with therapeutic concentrations restoring the normal conditions in the brain of the diseased animals. The neuritic spine morphology confirms the long-term memory potentiation through improved mushroom spine density, increased dendritic length and connectivity. Taken together, our study provides mechanistic evidence to prove that the traditional formulation can be a superior therapeutic strategy to treat cognitive decline when compared to the conventional mono-drug treatment.

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

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

Subset Analysis for Screening Drug-Drug Interaction Signal Using Pharmacovigilance Database.

Many patients require multi-drug combinations, and adverse event profiles reflect not only the effects of individual drugs but also drug–drug interactions. Although there are several algorithms for detecting drug–drug interaction signals, a simple analysis model is required for early detection of adverse events. Recently, there have been reports of detecting signals of drug–drug interactions using subset analysis, but appropriate detection criterion may not have been used. In this study, we presented and verified an appropriate criterion. The data source used was the Japanese Adverse Drug Event Report (JADER) database; “hypothetical” true data were generated through a combination of signals detected by three detection algorithms. The accuracy of the signal detection of the analytic model under investigation was verified using indicators used in machine learning. The newly proposed subset analysis confirmed that the signal detection was improved, compared with signal detection in the previous subset analysis, on the basis of the indicators of Accuracy (0.584 to 0.809), Precision (= Positive predictive value; PPV) (0.302 to 0.596), Specificity (0.583 to 0.878), Youden’s index (0.170 to 0.465), F-measure (0.399 to 0.592), and Negative predictive value (NPV) (0.821 to 0.874). The previous subset analysis detected many false drug–drug interaction signals. Although the newly proposed subset analysis provides slightly lower detection accuracy for drug–drug interaction signals compared to signals compared to the Ω shrinkage measure model, the criteria used in the newly subset analysis significantly reduced the amount of falsely detected signals found in the previous subset analysis.