The development of rapid and sensitive devices for the simultaneous detection of neurotransmitters has critical implications for the clinical field and for the management of several diseases. Parkinson’s, Alzheimer’s disease, autism, schizophrenia, depression and anxiety are major healthcare challenges for which early diagnostics and personalized therapy are of great concern.

Carbon-based nanomaterials and especially graphene-based nanomaterials associated with different architectures have been extensively studied and continue to represent the first line of approach in the development of nanoplatforms for electrochemical sensors. The simultaneous detection of analytes represents a critical point that could be addressed by designing new materials with the capacity to resolve their electrochemical signals. The results can be presented as a matrix that offers a broader viewpoint toward the balance of the neurotransmitter levels that are correlated with clinical symptoms for personalized diagnosis.

The goal is to describe and evaluate, in a critical manner, the elaboration of graphene-based sensors that can be included in clinical applications. A major check point discussed throughout the paper is represented by the interference between different neurotransmitters that appear due to their overlapping signals and the strategies to address them to achieve simultaneous detection of as many molecules as possible and to be similar to in vivo experiments.

用于同时检测神经递质的快速灵敏设备的开发对临床领域和几种疾病的管理具有至关重要的意义。帕金森氏症，阿尔茨海默氏病，自闭症，精神分裂症，抑郁症和焦虑症是主要的医疗挑战，因此，早期诊断和个性化治疗备受关注。

碳基纳米材料，尤其是与不同结构相关的石墨烯基纳米材料已经得到了广泛的研究，并继续代表着开发用于电化学传感器的纳米平台的第一线方法。同时检测分析物代表了一个关键点，可以通过设计具有解析其电化学信号能力的新材料来解决这一问题。可以将结果表示为矩阵，从而为与个性化诊断的临床症状相关的神经递质水平的平衡提供更广阔的视野。

目的是以关键的方式描述和评估可用于临床应用中的基于石墨烯的传感器。贯穿本文讨论的一个主要检查要点是由于不同的神经递质之间的干扰，这些递质由于它们的重叠信号而出现，以及解决它们以同时检测尽可能多的分子并与体内实验相似的策略。