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Developmental Clinical Studies - Curing Obesity with the 'Medical Bypass'

Developmental Clinical Studies - Curing Obesity with the 'Medical Bypass'
发育临床研究 - 通过“医疗旁路”治愈肥胖
批准号:
MR/J010731/1
负责人:
Stephen Bloom
金额:
$378.22万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2013
资助国家:
英国
项目状态:
已结题
起止时间:
2013 至 --

项目摘要

项目成果

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中文摘要
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英文摘要
A quarter of the UK population is obese and unfortunately this number is still rising. Obesity is strongly associated with maturity onset diabetes. Obesity is also a major cause of cancer, heart attacks, strokes and other illnesses. There is no effective drug therapy for obesity. The only effective treatment is gastric bypass surgery which causes a large weight loss, cure of diabetes and a reduction of rates of cancer and heart attacks. Unfortunately surgery is a major undertaking, is expensive, is irreversible, is associated with complications, and is risky. The benefits of this surgery are due to the much increased secretion of chemicals by the gut, called gut hormones. These are glucagon-like peptide-1, oxyntomodulin and peptide YY. We have developed two new drugs based on these gut hormones, made with natural amino acids, and combined them together to mimic the effect of bypass surgery in a single weekly injection through a fine needle. We call this the 'medical bypass' as it works by the same mechanism as the surgical bypass. This treatment will be as effective as bypass surgery but it will be less expensive and will be much less risky. One of the components of the medical bypass, which we call Y242, is already being tested in trials this year. In the project here, we are going to develop the other component, which we call G3215. We will first test G3215 to make sure it is safe before testing it in human volunteers to check that it is well-tolerated. We will then mix the Y242 and G3215 together and test this in human volunteers, as well as in patients with diabetes, to prove that the medical bypass is effective in helping patients lose weight and control their blood sugar levels. If our medical bypass is effective, this would be a great advance in the treatment of obesity and diabetes, and would help to save the many lives lost each year to the complications of these serious conditions.
期刊论文(10)
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会议论文
DOI: 10.1210/en.2016-1827
发表时间: 2017-06-01
期刊: Endocrinology
影响因子: 4.8
作者: [Cuenco J, Minnion J, Tan T, Scott R, Germain N, Ling Y, Chen R, Ghatei M, Bloom S]
通讯作者: Bloom S
DOI: 10.1016/s0140-6736(15)60343-9
发表时间: 2015-02-26
期刊: Lancet (London, England)
影响因子: --
作者: [Cegla, Jaimini, Cuenco, Joyceline, Bloom, Stephen]
通讯作者: Bloom, Stephen
DOI: 10.1016/j.xcrm.2022.100810
发表时间: 2022-11-15
期刊: CELL REPORTS MEDICINE
影响因子: 14.3
作者: [Hope, David C. D., Hinds, Charlotte E., Lopes, Tatiana, Vincent, Matthew L., V. Shrewsbury, Jed, Yu, Arthur T. C., Davies, Iona, Scott, Rebecca, Jones, Ben, Murphy, Kevin G., Minnion, James S., Sardini, Alessandro, Carling, David, Lutz, Thomas A., Bloom, Stephen R., Tan, Tricia M. M., Owen, Bryn M.]
通讯作者: Owen, Bryn M.
DOI: 10.1210/en.2016-1755
发表时间: 2017-08-01
期刊: Endocrinology
影响因子: 4.8
作者: [Cegla J, Jones BJ, Gardiner JV, Hodson DJ, Marjot T, McGlone ER, Tan TM, Bloom SR]
通讯作者: Bloom SR
Next generation Y analogue for treatment of obesity
  • 批准号:
    MR/L013088/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $519.47万
  • 财政年份:
    2014
  • 负责人:
    Stephen Bloom
  • 依托单位:
Do gut hormones mediate the beneficial effects of Roux-en-Y bypass surgery?
  • 批准号:
    MR/K02115X/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $327.22万
  • 财政年份:
    2013
  • 负责人:
    Stephen Bloom
  • 依托单位:
Developmental Clinical Studies - Phase 1 studies on an analogue of peptide YY as a treatment for obesity
  • 批准号:
    G1000474/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $350.04万
  • 财政年份:
    2011
  • 负责人:
    Stephen Bloom
  • 依托单位:
Treatment of obesity by long acting analogues of peptide YY (PYY)
  • 批准号:
    G0802390/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $93.76万
  • 财政年份:
    2009
  • 负责人:
    Stephen Bloom
  • 依托单位:
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海外基金
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data