Lu Lu

This paper develops a computational platform to evaluate anti-sickling agents by integrating PK/PD models with RBC sickling kinetics, demonstrating its utility in predicting therapeutic efficacy and noncompliance outcomes for existing and potential drugs.

The paper uses imaging and simulations to estimate hindered diffusion rates in platelet masses, finding rates range from 2% to 40% of unhindered rates.

The paper develops a deep learning algorithm that integrates ordinary differential equations into neural networks to infer hidden dynamics and parameters from sparse experimental data.