41,346 research outputs found
Visual Artist Talk with Jen Liu
No full textJen Liu is a visual artist based in New York and Vermont, working in video/animation, choreography, biomaterial, and painting to explore national identity, gendered economies, neoliberal industrial labor, and the re-motivating of archival artifacts. She is a 2019 recipient of the Creative Capital Award, 2018 LACMA Art + Technology Lab grant, and 2017 Guggenheim Fellowship in Film/Video. She has presented work at The Whitney Museum, MoMA, and The New Museum, New York; Smithsonian American Art Museum, DC; Royal Academy and ICA, London; Kunsthaus Zurich; Kunsthalle Wien; the Aspen Museum of Art; Henry Art Gallery, Seattle; MUSAC, Leon; UCCA and A07 @ 798, Beijing; and the 2014 Shanghai Biennale and 2019 Singapore Biennale
Statistical Designs of Clinical Trials
No full textClinical Trials
FDA (21 CFR 312.3, April 1994)
A clinical trial is the clinical investigation of a
drug which is administrated or dispensed or
used involving one or more human subjects.
Chow and Liu (July 1998)
A clinical trial is a clinical investigation in
which treatments are administrated,
dispensed or used involving one or more
human subjects for evaluation of the
treatment
Lithobius (Monotarsobius) subspinipes Ma, Pei, Zhu, Zhang & Liu 2009
No full textLithobius (Monotarsobius) subspinipes Ma, Pei, Zhu, Zhang & Liu, 2009 Lithobius (Monotarsobius) subspinipes Ma, Pei, Zhu, Zhang & Liu, 2009 b: 314, Figs, 1 – 6 Previous records. Hebei Province (Baoding and Hengshui Cities) (Ma et al., 2009 b). Remarks. Only known from China.Published as part of Ma, Huiqin, Pei, Sujian, Hou, Xiaojie, Zhu, Tiegang, Wu, Dayong & Gai, Yonghua, 2014, An annotated checklist of Lithobiomorpha of China, pp. 333-358 in Zootaxa 3847 (3) on page 346, DOI: 10.11646/zootaxa.3847.3.2, http://zenodo.org/record/23128
Commentary on "accounting for the interim safety monitoring of an adverse event upon termination of a clinical trial"
No full textRethinking statistical approaches to evaluating drug safety
No full text[[abstract]]The current methods used to evaluate the efficacy of drug products are inadequate. We propose a non-inferiority approach to prove the safety of drugs. Materials and Methods: Traditional hypotheses for the evaluation of the safety of drugs are based on proof of hazard, which have proven to be inadequate. Therefore, based on the concept of proof of safety, the non-inferiority hypothesis is employed to prove that the risk of new drugs does not exceed a pre-specified allowable safety margin, hence proving that a drug has no excessive risk. The results from papers published on Vioxx (R) and Avandia (R) are used to illustrate the difference between the traditional approach for proof of hazard and the non-inferiority approach for proof of safety. Results: The p-values from traditional hypotheses were greater than 0.05, and failed to demonstrate that Vioxx (R) and Avandia (R) are of cardiovascular hazard. However, these results cannot prove that both Vioxx (R) and Avandia (R) are of no cardiovascular risk. On the other hand, the non-inferiority approach can prove that they are of excessive cardiovascular risk. Conclusion: The non-inferiority approach is appropriate to prove the safety of drugs
Clinical Data Management and Case Report Form
No full textClinical Data Management
To provide consistency, accuracy and validity of clinical data in timeliness and cost-effective manner to support of conclusion on efficacy, safety, quality of life and pharmacoeconomic assessment of a pharmaceutical product
Statistical Methods for Clinical Evaluation of Biochip Products
No full textPost HGP (Human Genome Project) Era
Pharmacogentics
Pharmacogenomics
Biochip Products
Target Clinical Trials
Personalized Medicine
Diagnosis and Treatmen
An Introduction to Statistical Evaluation of Drug Products
No full textEvidence from clinical trials must prove that the drug is efficacious –drug is better than no drug
Inference from the sample (patients in trials) to the targeted population (patients in clinical practice)
A decision process for clinical hypotheses based on the trial objectives through statistical testing procedure
Statistical Methods for Biotechnology Products II－Sample Size Estimation in Clinical Trials
No full textIntroduction
E = experimental treatment group
C = control treatment group
We consider
Mean difference
Difference in proportions
Relative risk
Equivalence trial
Time to even
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