Artificial Intelligence in Business Analytics: Predictive Modeling for Nanoparticle Applications in Drug Delivery Systems

EasyChair Preprint 14979

Abstract

This study explores the integration of artificial intelligence (AI) in business analytics to develop predictive models for optimizing nanoparticle applications in drug delivery systems. By leveraging machine learning algorithms and data analytics, this research aims to enhance the efficacy and precision of nanoparticle-based drug delivery. A comprehensive dataset of nanoparticle properties, drug characteristics, and delivery outcomes is utilized to train AI models, enabling predictive insights into optimal nanoparticle design, targeting strategies, and release mechanisms.

The results demonstrate significant improvements in drug delivery efficiency, reduced toxicity, and enhanced patient outcomes. Moreover, the AI-driven predictive framework provides actionable business intelligence for pharmaceutical companies, facilitating informed decision-making, streamlined research and development, and optimized resource allocation. This interdisciplinary approach at the nexus of AI, business analytics, and nanomedicine paves the way for innovative drug delivery solutions, improved healthcare outcomes, and sustainable business growth.

Keyphrases: Artificial Intelligence, Business Analytics, drug delivery systems, machine learning, nanoparticle applications, predictive modeling

@booklet{EasyChair:14979,
  author    = {Abill Robert},
  title     = {Artificial Intelligence in Business Analytics: Predictive Modeling for Nanoparticle Applications in Drug Delivery Systems},
  howpublished = {EasyChair Preprint 14979},
  year      = {EasyChair, 2024}}