Prediction of Multi-Pharmacokinetics Property in Multi-Species: Bayesian Neural Network Stacking Model with Uncertainty
文献类型：期刊论文
| 作者 | Zhang, Yuanyuan2,3; Xie, Zhiyin2,3; Xiao, Fu2,4; Yu, Jie1,2,5; Fan, Zhehuan2,3; Sun, Shihui2,4; Shi, Jiangshan2,3; Fu, Zunyun2; Li, Xutong2,3; Wang, Dingyan1 |
| 刊名 | MOLECULAR PHARMACEUTICS
 |
| 出版日期 | 2024-11-07 |
| 页码 | 16 |
| 关键词 | pharmacokinetic parameters machine learning uncertainty stacking multitask learning ADME |
| ISSN号 | 1543-8384 |
| DOI | 10.1021/acs.molpharmaceut.4c00406 |
| 英文摘要 | Pharmacokinetic (PK) properties of a drug are vital attributes influencing its therapeutic effectiveness, playing an important role in the drug development process. Focusing on the difficult task of predicting PK parameters, we compiled an extensive data set comprising parameters across multiple species. Building upon this groundwork, we introduced the PKStack ensemble model to predict PK parameters across diverse species. PKStack integrates a variety of base models and includes uncertainty in its predictions. We also manually collected PK data from animals as an external test set. We predicted a total of 45 tasks for nine PK parameters in five species, and in general, the prediction accuracy was better for intravenous injections, including parameters such as human V d (R2 = 0.72, RMSE = 0.31), human CL (R2 = 0.52, RMSE = 0.32), and others. In addition to predictive accuracy, we also considered the interpretability of the results and the definition of the model's application domain. Based on the findings, our model has great potential for practical applications in drug discovery. |
| WOS关键词 | MOLECULAR-PROPERTIES ; DRUG DISCOVERY ; IN-VITRO ; PARAMETERS ; PHARMACODYNAMICS ; VOLUME |
| 资助项目 | National Natural Science Foundation of China[82130108] ; National Natural Science Foundation of China[T2225002] ; National Natural Science Foundation of China[82204278] ; National Natural Science Foundation of China[SIMM0120232001] ; Fund of State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences[22YF1460800] ; Shanghai Sailing Program[2023YFC2305904] ; National Key Research and Development Program of China[2023B1111030004] ; Key Technologies R&D Program of Guangdong Province[2023693] ; Shanghai Postdoctoral Excellence Program |
| WOS研究方向 | Research & Experimental Medicine ; Pharmacology & Pharmacy |
| WOS记录号 | WOS:001350025900001 |
| 出版者 | AMER CHEMICAL SOC |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/314370]  |
| 专题 | 新药研究国家重点实验室 |
| 通讯作者 | Wang, Dingyan; Zheng, Mingyue; Luo, Xiaomin |
| 作者单位 | 1.Lingang Lab, Shanghai 200031, Peoples R China 2.Chinese Acad Sci, Shanghai Inst Mat Med, Drug Discovery & Design Ctr, State Key Lab Drug Res, Shanghai 201203, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Nanjing Univ Chinese Med, Sch Chinese Mat Med, Nanjing 210023, Peoples R China 5.Shanghai Tech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Yuanyuan,Xie, Zhiyin,Xiao, Fu,et al. Prediction of Multi-Pharmacokinetics Property in Multi-Species: Bayesian Neural Network Stacking Model with Uncertainty[J]. MOLECULAR PHARMACEUTICS,2024:16. |
| APA | Zhang, Yuanyuan.,Xie, Zhiyin.,Xiao, Fu.,Yu, Jie.,Fan, Zhehuan.,...&Luo, Xiaomin.(2024).Prediction of Multi-Pharmacokinetics Property in Multi-Species: Bayesian Neural Network Stacking Model with Uncertainty.MOLECULAR PHARMACEUTICS,16. |
| MLA | Zhang, Yuanyuan,et al."Prediction of Multi-Pharmacokinetics Property in Multi-Species: Bayesian Neural Network Stacking Model with Uncertainty".MOLECULAR PHARMACEUTICS (2024):16. |
入库方式： OAI收割
来源：上海药物研究所
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