Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches

Article Chemistry, Medicinal

Development of a Web-Based Toolbox to Support Quantitative In-Vitro-to-In-Vivo Extrapolations (QIVIVE) within Nonanimal Testing Strategies

Ans Punt et al.

Summary: The study developed an online PBK model toolbox for predicting chemical concentrations in vivo and prioritizing chemicals based on comparing oral equivalent doses.

CHEMICAL RESEARCH IN TOXICOLOGY (2021)

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Article Pharmacology & Pharmacy

An integrated computational methodology with data-driven machine learning, molecular modeling and PBPK modeling to accelerate solid dispersion formulation design

Hanlu Gao et al.

Summary: Computational tools, including machine learning, molecular dynamic simulation and physiologically based pharmacokinetic modeling, have been integrated to accelerate the development of solid dispersion (SD) formulations. Prediction models for dissolution behavior and human pharmacokinetic profile have been constructed and validated, showing good performance in predicting the important information for formulation development. The use of integrated computational methodology is expected to significantly facilitate pharmaceutical formulation development compared to traditional trial-and-error approaches in the laboratory.

EUROPEAN JOURNAL OF PHARMACEUTICS AND BIOPHARMACEUTICS (2021)

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Review Biotechnology & Applied Microbiology

Engineering precision nanoparticles for drug delivery

Michael J. Mitchell et al.

Summary: The development of nanoparticles has shown promising clinical applications, overcoming the limitations of therapeutic interventions and biological barriers. Precision therapies have enhanced treatment efficacy through personalized interventions. Advancements in nanoparticle design aim to optimize drug delivery, improving efficacy in general applications and enabling tailored designs for precision applications.

NATURE REVIEWS DRUG DISCOVERY (2021)

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Article Oncology

Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

Hyuna Sung et al.

Summary: The global cancer burden in 2020 saw an estimated 19.3 million new cancer cases and almost 10.0 million cancer deaths. Female breast cancer surpassed lung cancer as the most commonly diagnosed cancer, while lung cancer remained the leading cause of cancer death. These trends are expected to rise in 2040, with transitioning countries experiencing a larger increase compared to transitioned countries due to demographic changes and risk factors associated with globalization and a growing economy. Efforts to improve cancer prevention measures and provision of cancer care in transitioning countries will be crucial for global cancer control.

CA-A CANCER JOURNAL FOR CLINICIANS (2021)

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Article Multidisciplinary Sciences

Prioritizing non-coding regions based on human genomic constraint and sequence context with deep learning

Dimitrios Vitsios et al.

Summary: The study integrates intolerance to variation, functional genomic annotations, and primary genomic sequences to build a comprehensive deep learning model JARVIS and genome-wide residual variation intolerance score (gwRVIS) for prioritizing non-coding regions. Both JARVIS and gwRVIS capture previously inaccessible human-lineage constraint information and enhance understanding of the non-coding genome.

NATURE COMMUNICATIONS (2021)

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Review Pharmacology & Pharmacy

Influencing factors and strategies of enhancing nanoparticles into tumors in vivo

Mingming Zhang et al.

Summary: This review discusses the challenges and mechanisms of nanoparticle infiltration in tumor microenvironment, as well as the strategies for enhancing therapeutic efficacy through adjusting the characteristics and structure of nanoparticles. The comprehensive summary provided in this review aims to guide future research in improving cancer treatment outcomes.

ACTA PHARMACEUTICA SINICA B (2021)

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Article Toxicology

Development and Application of an Interactive Physiologically Based Pharmacokinetic (iPBPK) Model to Predict Oxytetracycline Tissue Distribution and Withdrawal Intervals in Market-Age Sheep and Goats

Mahbubul H. Riad et al.

Summary: A physiologically based pharmacokinetic (PBPK) model for oxytetracycline in sheep and goats was developed, calibrated, and evaluated using serum and tissue concentration data, demonstrating accurate simulation and providing a tool to predict the time needed for drug concentrations in edible tissues to fall below tolerances. The model, converted to a web-based interactive PBPK (iPBPK) interface, serves as a useful tool for estimating withdrawal intervals and ensuring food safety in small ruminants.

TOXICOLOGICAL SCIENCES (2021)

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Article Multidisciplinary Sciences

Toward the use of neural networks for influenza prediction at multiple spatial resolutions

Emily L. Aiken et al.

Summary: The study compares the use of a gated recurrent unit neural network approach with baseline machine learning methods in estimating influenza activity in the United States at state and city levels, and explores the inclusion of real-time Internet search data. It is found that the neural network approach outperforms baseline models for long-term prediction horizons, but is not enhanced by real-time internet search data. A thorough analysis of feature importances in all models is conducted for interpretability purposes.

SCIENCE ADVANCES (2021)

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Article Nanoscience & Nanotechnology

Promoting Nanoparticle Delivery Efficiency to Tumors by Locally Increasing Blood Flow There

Feng Fan et al.

Summary: Enhancing tumor-targeted delivery efficiency of nanoparticles is vital for their therapeutic efficacy, with blood flow playing a crucial role in facilitating this process.

ACS APPLIED BIO MATERIALS (2021)

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Article Multidisciplinary Sciences

Deep exploration of random forest model boosts the interpretability of machine learning studies of complicated immune responses and lung burden of nanoparticles

Fubo Yu et al.

Summary: This study successfully predicts the pulmonary immune responses and lung burden of nanoparticles using a tree-based random forest feature importance and feature interaction network analysis framework (TBRFA), overcoming feature importance bias brought by small datasets.

SCIENCE ADVANCES (2021)

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Article Computer Science, Information Systems

The Effect of Preprocessing Techniques, Applied to Numeric Features, on Classification Algorithms' Performance

Esra'a Alshdaifat et al.

Summary: The performance of classification algorithms is significantly impacted by the choice of preprocessing techniques, with varying effects depending on the algorithm used. Different data preprocessing techniques result in statistically significant differences in classification outcomes.

DATA (2021)

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Article Chemistry, Multidisciplinary

Meta-Analysis of Nanoparticle Delivery to Tumors Using a Physiologically Based Pharmacokinetic Modeling and Simulation Approach

Yi-Hsien Cheng et al.

ACS NANO (2020)

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Article Multidisciplinary Sciences

Animal simulations facilitate smart drug design through prediction of nanomaterial transport to individual tissue cells

Edward Price et al.

SCIENCE ADVANCES (2020)

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Review Cell Biology

Tumor microenvironment complexity and therapeutic implications at a glance

Roghayyeh Baghba et al.

CELL COMMUNICATION AND SIGNALING (2020)

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Article Multidisciplinary Sciences

Construction of a web-based nanomaterial database by big data curation and modeling friendly nanostructure annotations

Xiliang Yan et al.

NATURE COMMUNICATIONS (2020)

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Article Multidisciplinary Sciences

A reanalysis of nanoparticle tumor delivery using classical pharmacokinetic metrics

Lauren S. L. Price et al.

SCIENCE ADVANCES (2020)

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Review Engineering, Biomedical

Artificial Intelligence and Machine Learning in Computational Nanotoxicology: Unlocking and Empowering Nanomedicine

Ajay Vikram Singh et al.

ADVANCED HEALTHCARE MATERIALS (2020)

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Article Computer Science, Theory & Methods

Survey on categorical data for neural networks

John T. Hancock et al.

JOURNAL OF BIG DATA (2020)

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Article Energy & Fuels

Prediction Model Based on an Artificial Neural Network for User-Based Building Energy Consumption in South Korea

Seunghui Lee et al.

ENERGIES (2019)

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Article Toxicology

Integration of Food Animal Residue Avoidance Databank (FARAD) empirical methods for drug withdrawal interval determination with a mechanistic population-based interactive physiologically based pharmacokinetic (iPBPK) modeling platform: example for flunixin meglumine administration

Miao Li et al.

ARCHIVES OF TOXICOLOGY (2019)

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Editorial Material Chemistry, Physical

Opportunities and challenges using artificial intelligence in ADME/Tox

Barun Bhhatarai et al.

NATURE MATERIALS (2019)

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Article Chemistry, Multidisciplinary

Supervised Learning and Mass Spectrometry Predicts the in Vivo Fate of Nanomaterials

James Lazarovits et al.

ACS NANO (2019)

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Review Pharmacology & Pharmacy

Artificial Intelligence for Drug Toxicity and Safety

Anna O. Basile et al.

TRENDS IN PHARMACOLOGICAL SCIENCES (2019)

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Article Chemistry, Medicinal

Prediction of Oral Bioavailability in Rats: Transferring Insights from in Vitro Correlations to (Deep) Machine Learning Models Using in Silico Model Outputs and Chemical Structure Parameters

Sebastian Schneckener et al.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2019)

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Review Chemistry, Medicinal

Physiologically Based Pharmacokinetic Modeling of Nanoparticles

Dongfen Yuan et al.

JOURNAL OF PHARMACEUTICAL SCIENCES (2019)

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Review Medicine, Research & Experimental

Research tools for extrapolating the disposition and pharmacokinetics of nanomaterials from preclinical animals to humans

Michael S. Valic et al.

THERANOSTICS (2019)

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Review Biotechnology & Applied Microbiology

Nanoparticles in the clinic: An update

Aaron C. Anselmo et al.

BIOENGINEERING & TRANSLATIONAL MEDICINE (2019)

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Review Toxicology

Challenges Associated With Applying Physiologically Based Pharmacokinetic Modeling for Public Health Decision-Making

Yu-Mei Tan et al.

TOXICOLOGICAL SCIENCES (2018)

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Review Multidisciplinary Sciences

Progress and challenges towards targeted delivery of cancer therapeutics

Daniel Rosenblum et al.

NATURE COMMUNICATIONS (2018)

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Review Biochemistry & Molecular Biology

Controlled drug delivery vehicles for cancer treatment and their performance

Sudipta Senapati et al.

SIGNAL TRANSDUCTION AND TARGETED THERAPY (2018)

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Article Nanoscience & Nanotechnology

A physiologically based pharmacokinetic model for polyethylene glycol-coated gold nanoparticles of different sizes in adult mice

Zhoumeng Lin et al.

NANOTOXICOLOGY (2016)

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Article Toxicology

In vivo biodistribution and physiologically based pharmacokinetic modeling of inhaled fresh and aged cerium oxide nanoparticles in rats

Dingsheng Li et al.

PARTICLE AND FIBRE TOXICOLOGY (2016)

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Article Nanoscience & Nanotechnology

Toward a general physiologically-based pharmacokinetic model for intravenously injected nanoparticles

Ulrika Carlander et al.

INTERNATIONAL JOURNAL OF NANOMEDICINE (2016)

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Review Pharmacology & Pharmacy

Mathematical modeling and simulation in animal health - Part II: principles, methods, applications, and value of physiologically based pharmacokinetic modeling in veterinary medicine and food safety assessment

Z. Lin et al.

JOURNAL OF VETERINARY PHARMACOLOGY AND THERAPEUTICS (2016)

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Article Biotechnology & Applied Microbiology

A computational framework for interspecies pharmacokinetics, exposure and toxicity assessment of gold nanoparticles

Zhoumeng Lin et al.

NANOMEDICINE (2016)

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Article Nanoscience & Nanotechnology

Analysis of nanoparticle delivery to tumours

Stefan Wilhelm et al.

NATURE REVIEWS MATERIALS (2016)

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Article Nanoscience & Nanotechnology

Physiologically based pharmacokinetic modeling of zinc oxide nanoparticles and zinc nitrate in mice

Wei-Yu Chen et al.

INTERNATIONAL JOURNAL OF NANOMEDICINE (2015)

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Review Computer Science, Artificial Intelligence

Deep learning in neural networks: An overview

Juergen Schmidhuber

NEURAL NETWORKS (2015)

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Review Nanoscience & Nanotechnology

Pharmacokinetics of metallic nanoparticles

Zhoumeng Lin et al.

WILEY INTERDISCIPLINARY REVIEWS-NANOMEDICINE AND NANOBIOTECHNOLOGY (2015)

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Article Chemistry, Multidisciplinary

Nanoparticle Surface Characterization and Clustering through Concentration-Dependent Surface Adsorption Modeling

Ran Chen et al.

ACS NANO (2014)

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Article Nanoscience & Nanotechnology

A physiologically based pharmacokinetic model for ionic silver and silver nanoparticles

Gerald Bachler et al.

INTERNATIONAL JOURNAL OF NANOMEDICINE (2013)

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Editorial Material Biotechnology & Applied Microbiology

Of mice, men and nanoparticle biocoronas: are in vitro to in vivo correlations and interspecies extrapolations realistic?

Jim E. Riviere

NANOMEDICINE (2013)

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Article Pharmacology & Pharmacy

Basic Concepts in Physiologically Based Pharmacokinetic Modeling in Drug Discovery and Development

H. M. Jones et al.

CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY (2013)

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Article Chemistry, Multidisciplinary

Physiologically Based Pharmacokinetic Model for Composite Nanodevices: Effect of Charge and Size on In Vivo Disposition

Donald E. Mager et al.

PHARMACEUTICAL RESEARCH (2012)

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Article Computer Science, Interdisciplinary Applications

Kernel-based machine learning for fast text mining in R

Alexandros Karatzoglou et al.

COMPUTATIONAL STATISTICS & DATA ANALYSIS (2010)

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Article Chemistry, Multidisciplinary

Comparison of Quantum Dot Biodistribution with a Blood-Flow-Limited Physiologically Based Pharmacokinetic Model

Hyun A. Lee et al.

NANO LETTERS (2009)

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Article Computer Science, Interdisciplinary Applications

Building Predictive Models in R Using the caret Package

Max Kuhn

JOURNAL OF STATISTICAL SOFTWARE (2008)

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Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches

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