DLM-DTI: a dual language model for the prediction of drug-target interaction with hint-based learning

Abstract The drug discovery process is demanding and time-consuming, and machine learning-based research is increasingly proposed to enhance efficiency. A significant challenge in this field is predicting whether a drug molecule’s structure will interact with a target protein. A recent study attempted to address this challenge by utilizing an encoder that leverages prior knowledge of molecular and protein structures, resulting in notable improvements in the prediction performance of the drug-target interactions task. Nonetheless, the target encoders employed in previous studies exhibit computational complexity that increases quadratically with the input length, thereby limiting their practical utility. To overcome this challenge, we adopt a hint-based learning strategy to develop a compact and efficient target encoder. With the adaptation parameter, our model can blend general knowledge and target-oriented knowledge to build features of the protein sequences. This approach yielded considerable performance enhancements and improved learning efficiency on three benchmark datasets: BIOSNAP, DAVIS, and Binding DB. Furthermore, our methodology boasts the merit of necessitating only a minimal Video RAM (VRAM) allocation, specifically 7.7GB, during the training phase (16.24% of the previous state-of-the-art model). This ensures the feasibility of training and inference even with constrained computational resources

Considerations for clinical evaluation of the effects of bariatric surgery on the pharmacokinetics of orally administered drugs

Obesity has been a growing worldwide concern, and surgical intervention including bariatric surgery is considered as one of the options for treatment. However, there still is controversy over the change in pharmacokinetics (PKs) of drugs after the surgery. To investigate the potential covariates that can influence the area under the curve (AUC) and maximum plasma concentration (Cmax), the design of previous studies was reviewed based on pre-determined eligibility criteria. Each study calculated the ratios of the AUC and Cmax before and after bariatric surgery. These studies investigated whether the PK parameters were affected by the time after the surgery or by the type of control group. The ratio of the AUC calculated in the early and late follow-up period was similar across Roux-en Y gastric bypass patients. No significant difference in the PK parameters was found between the pre-surgical patients and matched healthy subjects. However, certain control groups could be preferable depending on the purpose of the clinical trial. Although Cmax was inconsistent compared to the AUC, insufficient sampling of the time points may have caused such an inconsistency. This is the first article exploring the appropriate methodology in designing clinical studies for changes in the PK characteristics of orally administered drugs in patients with bariatric surgery.Y