What are the Recent Advances in QSAR for Nanotechnology?
Recent advances are addressing some of these challenges, including:
Machine Learning: Integrating machine learning techniques to improve the accuracy and reliability of QSAR models. High-Throughput Screening: Using high-throughput screening methods to generate large datasets for model training. Multiscale Modeling: Developing multiscale models that consider different levels of biological organization and environmental conditions. Collaborative Platforms: Creating collaborative platforms for data sharing and model validation among researchers and regulatory bodies.
