Machine Learning and Chemometrics in Drug Delivery: Focusing on Molecular Research
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".
Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 1485
Special Issue Editors
Interests: computational chemistry; molecular dynamics; modelling; machine learning; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: computational chemistry; bio-inspired systems; molecular dynamics; Monte Carlo simulations; modelling
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Machine learning (ML) and Chemometrics have emerged as crucial tools in the synergy between pharmaceutical sciences and data-based technology. In the context of drug delivery, these tools hold the potential to transform the way we approach the design, refinement, and understanding of drug delivery systems. From advancing drug formulation to tailoring drug release profiles and projecting therapeutic outcomes, the use of ML and Chemometrics presents an exciting pathway for innovation and efficacy.
Our understanding of drug delivery has traditionally been supported by empirical observations, but now we have the opportunity to dive deeper into the molecular foundations of this intricate process. This Special Issue is dedicated to exploring the vast landscape of molecular-level studies and validation results that are at the forefront of innovation in drug delivery. From elucidating the molecular interactions between drugs and carriers to deciphering the mechanistic pathways governing drug release, we invite contributions that cover the molecular dimension. The studies should attempt to explore the core of drug delivery systems at the molecular level and should focus on the thorough validation of the computational results.
We welcome contributions in the form of original research papers, as well as topical reviews and/or short communications.
Dr. Tânia Cova
Dr. Sandra Nunes
Guest Editors
Manuscript Submission Information
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Keywords
- machine learning
- chemometrics
- analytical chemistry
- drug delivery
- drug-drug interaction
- drug-carrier interaction
- drug release
- drug formulations
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