Preclinical Drug Screening

Preclinical drug screening aims to rapidly identify promising drug candidates by computationally predicting their effectiveness against target proteins or cells. Current research emphasizes improving the accuracy and efficiency of these predictions, focusing on machine learning approaches such as graph neural networks, gradient boosting decision trees, and zero-shot learning methods to handle novel compounds. These advancements address challenges like mitigating false positives from molecular aggregation and improving the reliability of performance evaluations, ultimately accelerating drug discovery and reducing development costs. The improved predictive power of these models promises to significantly streamline the drug development pipeline.

Papers

October 5, 2023

Zero-shot Learning of Drug Response Prediction for Preclinical Drug Screening
Kun Li, Yong Luo, Xiantao Cai, Wenbin Hu, Bo Du
Zero Shot Learning Drug Response Prediction Drug Response Preclinical Drug Screening

June 3, 2023

Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI
Hunter Sturm, Jonas Teufel, Kaitlin A. Isfeld, Pascal Friederich, Rebecca L. Davis
Explainable AI Drug Discovery High Throughput Molecular Functionality Preclinical Drug Screening

May 4, 2022

Compound virtual screening by learning-to-rank with gradient boosting decision tree and enrichment-based cumulative gain
Kairi Furui, Masahito Ohue
Decision Tree Virtual Screening Learning to Rank Ranking Task Based Virtual Screening Compound Property Enrichment Based Cumulative Gain Preclinical Drug Screening

January 28, 2022

Insights into performance evaluation of com-pound-protein interaction prediction methods
Adiba Yaseen, Imran Amin, Naeem Akhter, Asa Ben-Hur, Fayyaz Minhas
DCU Insight AQ Performance Evaluation Protein Protein Interaction Drug Design Compound Library Compound Protein Interaction Preclinical Drug Screening

Preclinical Drug Screening

Papers

Zero-shot Learning of Drug Response Prediction for Preclinical Drug Screening

Mitigating Molecular Aggregation in Drug Discovery with Predictive Insights from Explainable AI

Compound virtual screening by learning-to-rank with gradient boosting decision tree and enrichment-based cumulative gain

Insights into performance evaluation of com-pound-protein interaction prediction methods