There are still huge challenges from clinical real-world data to accurate targets and critical quality attributes (CQAs) for effective treatment of allergic rhinitis (AR). Here, we present a novel integrated strategy that biosensors and intelligent algorithms were used to angle AR targets and CQAs from clinical real-world. Firstly, bagging and boosting partial least squares discrimination analysis (PLS-DA) and Monte-Carlo sampling were proposed to screen accurate AR targets. Macrophage migration inhibitory factor (MIF) and Interleukin-1beta (IL-1β) targets were obtained based on large-scale analysis of one thousand proteins and in-depth precise screening of seventy proteins. Furthermore, high electron mobility transistor (HEMT) biosensors were fabricated and were successfully modified by MIF and IL-1β targets with a low detection concentration as 1 pM and quantitative range from 1 pM to 10 nM. Surprisingly, through MIF/IL-1β biosensors, we angled 5-O-methylvisammioside, amygdalin, and cimicifugoside three CQAs. The strong interaction was discovered among three CQAs and MIF/IL-1β biosensors with all K_D up to 10^-11 M. Finally, interaction of three CQAs and MIF/IL-1β biosensors were evaluated by in vitro and vivo experiments. In this paper, two critical targets and three effective CQAs for AR treatment were discovered and validated by biosensor and advanced algorithms. It provides a superior integrated idea for angling critical targets and CQAs from clinical real-world data by biosensors and informatics.

从临床真实世界数据到有效治疗过敏性鼻炎 (AR) 的准确目标和关键质量属性 (CQA)，仍然存在巨大挑战。在这里，我们提出了一种新的集成策略，即使用生物传感器和智能算法从临床现实世界中分析 AR 目标和 CQA。首先，提出了 bagging 和 boosting 偏最小二乘判别分析 (PLS-DA) 和 Monte-Carlo 采样来筛选准确的 AR 目标。巨噬细胞迁移抑制因子（MIF）和白细胞介素-1β（IL-1β）靶点是基于对1000种蛋白质的大规模分析和对70种蛋白质的深度精准筛选获得的。此外，制造了高电子迁移率晶体管（HEMT）生物传感器，并成功地被 MIF 和 IL-1β 靶标修饰，检测浓度低至 1 pM，定量范围从 1 pM 到 10 nM。令人惊讶的是，通过 MIF/IL-1β 生物传感器，我们将 5-O-甲基维桑苷、苦杏仁苷和升麻苷三种 CQA 成角度。在三个 CQAs 和 MIF/IL-1β 生物传感器之间发现了强相互作用，所有 K_D高达 10 ^-11 M。最后，通过体外和体内实验评估了三种 CQAs 和 MIF/IL-1β 生物传感器的相互作用。在本文中，通过生物传感器和先进算法发现并验证了用于 AR 治疗的两个关键目标和三个有效 CQA。它为通过生物传感器和信息学从临床真实世界数据中确定关键目标和 CQA 提供了一种卓越的综合理念。