Machine Learning Attempts for Predicting Human Subcutaneous Bioavailability of Monoclonal Antibodies.
Hao LouMichael J HagemanPublished in: Pharmaceutical research (2021)
Machine learning could be a potential tool to predict mAb's bioavailability. Since all input features were acquired using theoretical calculations and predictions rather than experiments, the models may be particularly applicable to some early-stage research activities such as mAb molecule triage, design/optimization, mutant screening, molecule selection, and formulation design.
Keyphrases
- machine learning
- early stage
- endothelial cells
- artificial intelligence
- emergency department
- monoclonal antibody
- big data
- drug delivery
- density functional theory
- induced pluripotent stem cells
- molecular dynamics
- pluripotent stem cells
- sentinel lymph node
- radiation therapy
- squamous cell carcinoma
- risk assessment
- lymph node
- monte carlo