Institution
Eli Lilly and Company
Company•Indianapolis, Indiana, United States•
About: Eli Lilly and Company is a company organization based out in Indianapolis, Indiana, United States. It is known for research contribution in the topics: Population & Receptor. The organization has 17826 authors who have published 22835 publications receiving 946714 citations. The organization is also known as: Eli Lily.
Topics: Population, Receptor, Placebo, Insulin, Agonist
Papers published on a yearly basis
Papers
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Christian R. Marshall1, Daniel P. Howrigan2, Daniele Merico1, Bhooma Thiruvahindrapuram1 +252 more•Institutions (87)
TL;DR: A collaborative effort in which a centralized analysis pipeline is applied to a SCZ cohort, finding support at a suggestive level for nine additional candidate susceptibility and protective loci, which consist predominantly of CNVs mediated by non-allelic homologous recombination (NAHR).
Abstract: Genomic copy number variants (CNVs) have been strongly implicated in the etiology of schizophrenia (SCZ). However, apart from a small number of risk variants, elucidation of the CNV contribution to risk has been difficult due to the rarity of risk alleles, all occurring in less than 1% of cases. We sought to address this obstacle through a collaborative effort in which we applied a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. We observed a global enrichment of CNV burden in cases (OR=1.11, P=5.7e-15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7e-6). CNV burden is also enriched for genes associated with synaptic function (OR = 1.68, P = 2.8e-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3e-5). We identified genome-wide significant support for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. We find support at a suggestive level for nine additional candidate susceptibility and protective loci, which consist predominantly of CNVs mediated by non-allelic homologous recombination (NAHR).
764 citations
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TL;DR: An Alzheimer's Association Research Roundtable was convened in the spring of 2010 to review what is known about NPS in Alzheimer's disease, to discuss classification and underlying neuropathogenesis and vulnerabilities, and to formulate recommendations for new approaches to tailored therapeutics.
Abstract: Neuropsychiatric symptoms (NPS) are core features of Alzheimer's disease and related dementias. Once thought to emerge primarily in people with late-stage disease, these symptoms are currently known to manifest commonly in very early disease and in prodromal phases, such as mild cognitive impairment. Despite decades of research, reliable treatments for dementia-associated NPS have not been found, and those that are in widespread use present notable risks for people using these medications. An Alzheimer's Association Research Roundtable was convened in the spring of 2010 to review what is known about NPS in Alzheimer's disease, to discuss classification and underlying neuropathogenesis and vulnerabilities, and to formulate recommendations for new approaches to tailored therapeutics.
754 citations
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TL;DR: P predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans are generated.
Abstract: Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.
753 citations
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TL;DR: Piog Litazone compared with rosiglitazone is associated with significant improvements in triglycerides, HDL cholesterol, LDL particle concentration, and LDL particle size, and Pioglitazones compared withrosig litazone has significantly different effects on plasma lipids independent of glycemic control or concomitant lipid-lowering or other antihyperglycemic therapy.
Abstract: OBJECTIVE—Published reports suggest that pioglitazone and rosiglitazone have different effects on lipids in patients with type 2 diabetes. However, these previous studies were either retrospective chart reviews or clinical trials not rigorously controlled for concomitant glucose- and lipid-lowering therapies. This study examines the lipid and glycemic effects of pioglitazone and rosiglitazone. RESEARCH DESIGN AND METHODS—We enrolled subjects with a diagnosis of type 2 diabetes (treated with diet alone or oral monotherapy) and dyslipidemia (not treated with any lipid-lowering agents). After a 4-week placebo washout period, subjects randomly assigned to the pioglitazone arm (n = 400) were treated with 30 mg once daily for 12 weeks followed by 45 mg once daily for an additional 12 weeks, whereas subjects randomly assigned to rosiglitazone (n = 402) were treated with 4 mg once daily followed by 4 mg twice daily for the same intervals. RESULTS—Triglyceride levels were reduced by 51.9 ± 7.8 mg/dl with pioglitazone, but were increased by 13.1 ± 7.8 mg/dl with rosiglitazone (P CONCLUSIONS—Pioglitazone and rosiglitazone have significantly different effects on plasma lipids independent of glycemic control or concomitant lipid-lowering or other antihyperglycemic therapy. Pioglitazone compared with rosiglitazone is associated with significant improvements in triglycerides, HDL cholesterol, LDL particle concentration, and LDL particle size.
753 citations
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TL;DR: The intent is to define a minimal best practice for in vitro and in vivo pharmacokinetic drug-drug interaction studies targeted to development (not discovery support) and to defined a data package that can be expected by regulatory agencies in compound registration dossiers.
Abstract: Current regulatory guidances do not address specific study designs for in vitro and in vivo drug-drug interaction studies. There is a common desire by regulatory authorities and by industry sponsors to harmonize approaches, to allow for a better assessment of the significance of findings across different studies and drugs. There is also a growing consensus for the standardization of cytochrome P450 (P450) probe substrates, inhibitors and inducers and for the development of classification systems to improve the communication of risk to health care providers and to patients. While existing guidances cover mainly P450-mediated drug interactions, the importance of other mechanisms, such as transporters, has been recognized more recently, and should also be addressed. This article was prepared by the Pharmaceutical Research and Manufacturers of America (PhRMA) Drug Metabolism and Clinical Pharmacology Technical Working Groups and represents the current industry position. The intent is to define a minimal best practice for in vitro and in vivo pharmacokinetic drug-drug interaction studies targeted to development (not discovery support) and to define a data package that can be expected by regulatory agencies in compound registration dossiers.
753 citations
Authors
Showing all 17866 results
Name | H-index | Papers | Citations |
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Mark J. Daly | 204 | 763 | 304452 |
Irving L. Weissman | 201 | 1141 | 172504 |
Eric J. Topol | 193 | 1373 | 151025 |
Tony Hunter | 175 | 593 | 124726 |
Xiang Zhang | 154 | 1733 | 117576 |
Jerrold M. Olefsky | 143 | 595 | 77356 |
Stephen F. Badylak | 133 | 530 | 57083 |
George A. Bray | 131 | 896 | 100975 |
Lloyd Paul Aiello | 131 | 506 | 85550 |
Levi A. Garraway | 129 | 366 | 99989 |
Mark Sullivan | 126 | 802 | 63916 |
James A. Russell | 124 | 1024 | 87929 |
Tony L. Yaksh | 123 | 806 | 60898 |
Elisabetta Dejana | 122 | 430 | 48254 |
Hagop S. Akiskal | 118 | 565 | 50869 |