Dense data enables 21st century clinical trials.
Dense data enables 21st century clinical trials.
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DOI：
10.1002/trc2.12297
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发表时间：
2022
影响因子：
4.8
通讯作者：
Bramen, Jennifer
中科院分区：
文献类型：
--
作者：
Roach, Jared C;Hodes, John F;Funk, Cory C;Shankle, William R;Merrill, David A;Hood, Leroy;Bramen, Jennifer
阿尔茨海默病(AD)是我们这个时代最重大的挑战之一。我们需要一个多样化的研究组合。我们承担不起关闭研究途径的代价。淀粉样蛋白假说主导了一个世纪，扼杀了AD的研究。我们不能再承受上个世纪的机会成本了。医保延误就是医保被否定。审判需要数年时间。在可能的情况下，试验应并行进行。如果我们先测试所有可能的单一模式干预，然后再测试任何其他假设，这将需要数十年--如果不是数百年的话。鉴于AD研究投资的高预期回报，我们不主张在AD试验之间重新分配资金作为零和游戏；相反，我们应该增加对所有AD研究的资助。如果需要重新分配全球AD资金，我们注意到制药公司可能会花费数十亿美元将验证和有效性低于多模式疗法或其组件的产品推向市场。为比药物试验便宜几个数量级的多模式试验重新分配资金的建议似乎是错误的。在系统生物学研究所(ISB)，我们的目标是改变临床研究的认识论性质。1大多数20世纪的临床试验主要建立在两个认识论支柱上：意义和效果大小。仅仅站在这两根柱子上，所能达到的知识是有限的。有些知识--通常是最令人满意的--只能从机械论或因果洞察力中获得。利用多个不同的大型数据集进行集成学习对包括商业在内的许多领域越来越重要，并正在成为生物医学知识和突破的主要驱动力。现在是大多数临床研究产生推动这种学习所需的密集数据的时候了。对全球知识的贡献现在应该成为临床试验设计的一个因素。承诺产生全球有用的数据集应该是更新的试验设计指南的一部分。我们的建议并不局限于AD研究--它们可以应用于所有复杂的疾病。有了足够深的数据，通过跨多个域集成数据可以学到很多东西。多模式AD疗法被广泛使用；美国人正在花费金钱和机会成本来追求这些疗法。我们民主国家的成员要求为多模式疗法的研究提供资金。当务之急是为这些公民和他们的医疗保健提供者提供科学。前瞻性随机对照试验(RCT)提供了最好的证据。我们有义务将研究价值返还给支持我们的人。
Alzheimer’s disease (AD) is one of the most significant challenges of our time. We need a diverse research portfolio. We cannot afford to shut down avenues of research. A century of domination by the amyloid hypothesis stifled AD research. We cannot again afford last century’s opportunity cost. Health care delayed is health care denied. Trials take years. Trials should be done in parallel where possible. If we were to test all possible single-mode interventions before testing any other hypotheses, it would take decades—if not centuries. Given the high expected return on AD research investment, we do not advocate redistributing money among AD trials as a zero-sum game; rather, we should increase funding for all AD research. If there were a need to redistribute global AD funding, we note that pharmaceutical companies may spend billions of dollars bringing to market products that are less validated and less effective than multimodal therapy or its components. A recommendation to reallocate funding for multimodal trials that are several orders of magnitude less expensive than pharmaceutical trials seems mistargeted.At the Institute for Systems Biology (ISB), we aim to change the epistemological nature of clinical studies. 1 Most 20th-century clinical trials were primarily built on two epistemological pillars: significance and effect size. There are limits to the knowledge that is reachable from standing only on these two pillars. Some knowledge—typically the most satisfying—can only be gained from mechanistic or causal insights. Integrated learning leveraging multiple diverse large datasets is increasingly important to many fields, including commerce, and is becoming a major driver of biomedical knowledge and breakthroughs. It is time for most clinical studies to generate the dense data necessary to power such learning. Contributing to global knowledge should now be a factor in clinical trial design. Commitment to generating globally useful datasets should be part of updated trial-design guidelines. Our recommendations are not restricted to AD research—they can be applied to all complex diseases. With sufficiently deep data, much can be learned by integrating data across multiple domains. Multimodal AD therapies are in wide use; Americans are spending money and opportunity cost to pursue them. There is a demand from the members of our democracy to fund research for multimodal therapies. It is urgent to provide these citizens and their healthcare providers with science. Prospective randomized controlled trials (RCTs) provide the best form of evidence. We have an obligation to return research value to the people that support us.