传统药物筛选的缺点
治疗药物的常规选择包括检查病毒或细菌对不同潜在候选人的反应。这些药物以越来越大的剂量给予细菌或病毒,直到观察到对它们生长的最大抑制。然后将其他药物加在一起以增强效果。然而,当同时研究几种候选药物时,这些方法就无效了。此外,这些方法通常在体外研究中产生积极的结果,但在人体研究中没有观察到。
“如果10或更多的药物检查,这几乎是不可能的研究的影响所需的所有可能的药物组合和剂量使用传统方法确定最好的组合,”何教授解释说,N.1研究所主任健康和数字医学研究所(WisDM)在新加坡国立大学。
此外,在传统的筛选中,如果从一组候选疗法中选出的一种药物被证明对病原体没有明显的效果,这种药物通常将不再被考虑。“然而,如果这种药物系统地与更多的药物结合,每一种都有正确的剂量,这很可能会产生最好的组合。不幸的是,这种需要的非凡水平的精度不能任意推导出来,”何教授补充说,他同时也是新加坡国立大学生物医学工程系主任。
使用人工智能优化药物治疗
为了避免传统药物联合治疗开发的弊端,何教授和他的团队与上海交通大学的合作者一起利用了人工智能的处理能力。
研究小组仔细挑选了12种治疗由水泡性口炎病毒(VSV)引起的肺部细胞感染的可行候选药物。然后他们使用了IDentif。人工智能to markedly reduce the number of experiments needed to interrogate the full range of combinations and optimal dosages of these 12 drugs. "Using IDentif.AI, we took three days to identify multiple optimal drug regimens out of billions of possible combinations that reduced the VSV infection to 1.5 percent with no apparent adverse impact. This speed and accuracy in discovering new drug combination therapies is completely unprecedented," said Prof Ho.
重要的是,该团队发现,当排名靠前的药物组合采用最佳剂量时,其效果比次最佳剂量高出7倍。这表明了理想药物和剂量识别的关键重要性。
同样地,当从排名靠前的药物组合中替代一种药物,并且以次优剂量给药时,该组合的效果要低14倍。“在药物发现中有这样一种观念,如果你发现了正确的分子,工作就完成了。我们的结果与IDentif。人工智能prove that it is critically important to think about how the drug is developed into a combination and subsequently administered. How do you combine it with the right drugs? How do you dose this drug properly? Answering these questions can dramatically increase efficacy at the clinical stage of drug development," shared Prof Ho.
除了验证IDentif。人工智能, this study also included insights by a team of experts in operations research and healthcare economics from NUS Business School and KPMG Global Health and Life Sciences Centre of Excellence, as well as global health security and surveillance experts from EpiPointe LLC and MRIGlobal. They concluded that strategies such as IDentif.AI, which can rapidly optimise drug repurposing under austere economic conditions amidst pandemics, could play a key role in improving patient outcomes compared to standard approaches.
使用IDentif。人工智能against COVID-19 and more
证明了识别的有效性。人工智能to rapidly provide treatments for infectious diseases, the team is currently setting their sights on COVID-19.
何教授说:“随着COVID-19疫苗和抗体疗法的开发正在进行中,我们将需要一种快速治疗策略,以应对可能随着时间演变的病毒。我们的优势在于,我们可以进行一次实验,并在几天内拿出一份治疗药物组合清单。及时地,如果患者对第一批药物组合反应不好,我们可以在几天内推出新的组合来重新优化他们的治疗。我们的平台有助于解决这样一种可能性,即患者将根据开始治疗的时间需要不同的药物组合,以及如果下游发生不同菌株的感染。”
此外,IDentif。人工智能could be immediately deployed to address any other infectious diseases in the future. Prof Ho concluded, "When an aggressive pathogen hits, a rapid response is needed, and this response may need to evolve quickly as the pathogen evolves. Now, with IDentif.AI, we will be ready."
来源:新加坡国立大学