Eli Lilly and Company

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.

The Discovery of Fluoxetine Hydrochloride (Prozac)

Abstract: In the early 1970s, evidence of the role of serotonin (5-hydroxytryptamine or 5-HT) in depression began to emerge and the hypothesis that enhancing 5-HT neurotransmission would be a viable mechanism to mediate antidepressant response was put forward. On the basis of this hypothesis, efforts to develop agents that inhibit the uptake of 5-HT from the synaptic cleft were initiated. These studies led to the discovery and development of the selective serotonin-reuptake inhibitor fluoxetine hydrochloride (Prozac; Eli Lilly), which was approved for the treatment of depression by the US FDA in 1987. Here, we summarize this research and discuss the many challenges that we encountered during the development of fluoxetine hydrochloride, which has now been widely acknowledged as a breakthrough drug for depression.

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

Abstract: Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

Evaluation of the Characteristics of Safety Withdrawal of Prescription Drugs from Worldwide Pharmaceutical Markets-1960 to 1999*

Abstract: A descriptive analysis was conducted to evaluate prescription drugs withdrawn from worldwide pharmaceutical markets over the past four decades due to safety reasons. The list of drugs, including indication, the duration of marketing, and reasons for withdrawal were examined. Among the 121 products identified, 42.1% were withdrawn from European markets alone, 5.0% from North America, 3.3% from Asia Pacific, and 49.6% from markets in multiple continents. Distributions of these withdrawals in each decade were: 12.4% from the 1960s, 16.5% from the 1970s, 39.7% from the 1980s, and 31.4% from the 1990s. Unfortunately, since the denominators (number of drug approvals) were not readily available, an accurate rate of withdrawal could not be reliably calculated. The most common categories of drugs withdrawn were: Non-Steroidal Anti-Inflammatory Drugs (13.2%), nonnarcotic analgesics (8.3%), antidepressants (7.4%), and vasodilators (5.8%). The top five safety reasons for withdrawals were: hepatic (26.2%), hematologic (10.5%), cardiovascular (8.7%), dermatologic (6.3%), and carcinogenic (6.3%) issues. Among the 87 products for which the timing of marketing was available, the median time on the market was 5.4 years with about one-third withdrawn within the first two years. It is hoped that the current review will stimulate other future research into this important topic. However, due to the intrinsic limitations of the descriptive analysis design, our observations are subject to the availability of data in the public domain. Readers are cautioned to be objective and careful when approaching data of this nature in order not to misinterpret the results due to potential data gaps.

New models of collaboration in genome-wide association studies: the Genetic Association Information Network

Abstract: The Genetic Association Information Network (GAIN) is a public-private partnership established to investigate the genetic basis of common diseases through a series of collaborative genome-wide association studies. GAIN has used new approaches for project selection, data deposition and distribution, collaborative analysis, publication and protection from premature intellectual property claims. These demonstrate a new commitment to shared scientific knowledge that should facilitate rapid advances in understanding the genetics of complex diseases.

2-Phenyl-3-aroylbenzothiophenes useful as antifertility agents

Abstract: Derivatives of 2-phenyl-3-aroylbenzothiophenes and 2-phenyl-3-aroylbenzothiophene-1-oxides are useful as antifertility agents. Certain of these compounds also are useful in suppressing the growth of mammary tumors.