Over 60 % of people over the age of 65 will suffer from multiple diseases concomitantly but the common approach is to treat each disease separately. As age-associated diseases have common underlying mechanisms there is potential to tackle many diseases with the same pharmacological intervention. These are known as geroprotectors and could overcome the problems related to polypharmacy seen with the use of the single disease model. With some geroprotectors now reaching the end stage of preclinical studies and early clinical trials, there is a need to review the evidence and assess how they can be translated practically and effectively into routine practice. Despite promising evidence, there are many gaps and challenges in our understanding that must be addressed to make geroprotective medicine effective in the treatment of age-associated multimorbidity. Here we highlight the key barriers to clinical translation and discuss whether geroprotectors such as metformin, rapamycin and senolytics can tackle all age-associated diseases at the same dose, or whether a more nuanced approach is required. The evidence suggests that geroprotectors’ mode of action may differ in different tissues or in response to different inducers of accelerating ageing, suggesting that a blunt ‘one drug for many diseases’ approach may not work. We make the case for the use of artificial intelligence to better understand multimorbidity, allowing identification of clusters and networks of diseases that are significantly associated beyond chance and the underpinning molecular pathway of ageing causal to each cluster. This will allow us to better understand the development of multimorbidity, select a more homogenous group of patients for intervention, match them with the appropriate geroprotector and identify biomarkers specific to the cluster.

65岁以上的人中，60%以上会同时患有多种疾病，但常见的方法是分别治疗每种疾病。由于与年龄相关的疾病具有共同的潜在机制，因此有可能通过相同的药物干预来解决许多疾病。这些被称为老年保护剂，可以克服使用单一疾病模型所看到的与多药治疗相关的问题。随着一些老年保护剂现已进入临床前研究和早期临床试验的最后阶段，有必要审查证据并评估如何将它们切实有效地转化为常规实践。尽管有令人鼓舞的证据，我们的理解存在许多差距和挑战，必须解决这些差距和挑战，才能使老年保护药物有效治疗与年龄相关的多种疾病。在这里，我们强调了临床转化的主要障碍，并讨论了二甲双胍、雷帕霉素和 Senolytics 等老年保护剂是否可以以相同的剂量治疗所有与年龄相关的疾病，或者是否需要更细致的方法。证据表明，老年保护剂的作用模式可能在不同组织中不同，或对加速衰老的不同诱导剂做出反应，这表明“一种药物治疗多种疾病”的方法可能行不通。我们为使用人工智能更好地理解多重疾病提供了理由，允许识别与偶然性显着相关的疾病集群和网络，以及每个集群的衰老原因的基础分子途径。这将使我们能够更好地了解多发病的发展，选择更同质的患者组进行干预，将他们与适当的老年保护剂相匹配，并确定特定于集群的生物标志物。