Develop an algorithmic analytics-enabled end-to-end high-throughput platform for solubility, LogD, and ASD formulation screening

Many high‑throughput (HT) experimental workflows have been reported for the determination of two key compound physicochemical properties—solubility and LogD. However, data processing for these assays has received far less attention, and the lack of efficient and scalable solutions has become a major bottleneck that constrains the overall throughput and practical utility of HT screening platforms. In this work, we designed an HT algorithm named FLASH (Functional LC Analysis & Sequencing Hub) containing two integrated modules. The first module streamlines HT liquid chromatography (LC) data acquisition by enabling one-click analytical sequence generation. The second module addresses the data processing bottleneck through integrated result calculation, anomaly flagging, and data visualization/correction, which enables a highly efficient workflow for solubility and LogD, thereby enabling throughput matching across the workflow. On this basis, we established a closed‑loop platform that encompasses the entire workflow from sample preparation to data reporting. This end-to-end platform has increased efficiency by more than tenfold and reduced material consumption by 20-fold. Building on this experience, we further developed an ASD formulation screening workflow. Overall, the multifunctional, algorithm-assisted end-to-end HT platform has laid down a practical and expandable framework to support a broad array of drug discovery/development activities.

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Publication Details

Journal
AAPS Open
Published
2026-08-27
DOI
https://doi.org/10.1186/s41120-026-00192-0
Primary Topic
Computational Drug Discovery Methods
Type
article
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article

Develop an algorithmic analytics-enabled end-to-end high-throughput platform for solubility, LogD, and ASD formulation screening

Yiran Su, Deliang Zhou, Xiaoning Shan, Yuxin Yue et al.
AAPS Open
Computational Drug Discovery Methods
article

Develop an algorithmic analytics-enabled end-to-end high-throughput platform for solubility, LogD, and ASD formulation screening

Yiran Su, Deliang Zhou, Xiaoning Shan, Yuxin Yue, Qian Li, Mingxin Hu, Shijun Wang, Yang Zhou, Zhen Chen
article en

Abstract

Many high‑throughput (HT) experimental workflows have been reported for the determination of two key compound physicochemical properties—solubility and LogD. However, data processing for these assays has received far less attention, and the lack of efficient and scalable solutions has become a major bottleneck that constrains the overall throughput and practical utility of HT screening platforms. In this work, we designed an HT algorithm named FLASH (Functional LC Analysis & Sequencing Hub) containing two integrated modules. The first module streamlines HT liquid chromatography (LC) data acquisition by enabling one-click analytical sequence generation. The second module addresses the data processing bottleneck through integrated result calculation, anomaly flagging, and data visualization/correction, which enables a highly efficient workflow for solubility and LogD, thereby enabling throughput matching across the workflow. On this basis, we established a closed‑loop platform that encompasses the entire workflow from sample preparation to data reporting. This end-to-end platform has increased efficiency by more than tenfold and reduced material consumption by 20-fold. Building on this experience, we further developed an ASD formulation screening workflow. Overall, the multifunctional, algorithm-assisted end-to-end HT platform has laid down a practical and expandable framework to support a broad array of drug discovery/development activities.

AAPS OpenVol. 12(1)
Science & Technology Park (Czechia) (CZ)
Openalex Percentile: Top 8%
Computational Drug Discovery Methods
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