Lei Liu,1,2 Qinghua Zhang,1,2 Yichuan Ma,3 Ling Lin,2 Wenli Liu,2 Aizhong Ding,2 Chunjian Wang,2 Shuiping Zhou,1 Jinyong Cai,1 Hai Tang1,2 

1Tasly Academy, Tasly Pharma Co., Ltd., Tianjin, People’s Republic of China; 2Tasly Academy Jiangsu Branch, Jiangsu Tasly Diyi Pharmaceutical Co., Ltd., Huaian, Jiangsu, People’s Republic of China; 3China Medical University (CMU)-The Queen’s University of Belfast (QUB) Joint College, Shenyang, Liaoning, People’s Republic of China

Correspondence: Hai Tang, Tasly Academy, Tasly Pharma Co., Ltd., No. 1 Tingjiang Road, Beichen District, Tianjin, 300410, People’s Republic of China, Email tsl-tanghai2020@tasly.com

Abstract: Over the past two decades, synthetic FFAR1 agonists such as TAK-875 and TSL1806 have undergone meticulous design and extensive clinical trials. However, due to issues primarily related to hepatotoxicity, no FFAR1 agonist has yet received regulatory approval. Research into the sources of hepatotoxicity suggests that one potential cause lies in the molecular structure itself. These structures typically feature lipid-like carboxylic acid head groups, which tend to generate toxic metabolites. Strategies to mitigate these risks focus on optimizing chemical groups to reduce lipophilicity and prevent the formation of reactive metabolites. Recent studies have concentrated on developing low-molecular-weight compounds that more closely resemble natural products, with CPL207280 showing promising potential and liver safety, currently in Phase II clinical trials. Moreover, ongoing research continues to explore the potential applications of FFAR1 agonists in diabetes management, as well as in conditions such as non-alcoholic fatty liver disease (NAFLD) and cerebrovascular diseases. Utilizing advanced technologies such as artificial intelligence and computer-aided design, the development of compact molecules that mimic natural structures represents a hopeful direction for future research and development.

Keywords: antidiabetics, oral FFAR1 development, natural-inspired structure modification, hepatotoxicity, fatty acid-based lipotoxicity, artificial intelligence aided