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Prediction of the Extent of Blood-Brain Barrier Transport Using Machine Learning and Integration into the LeiCNS-PK3.0 Model.

Pharmaceutical research
INTRODUCTION: The unbound brain-to-plasma partition coefficient (K) is an essential parameter for predicting central nervous system (CNS) drug disposition using physiologically-based pharmacokinetic (PBPK) modeling. K values for specific compounds ar...

A numerical treatment through Bayesian regularization neural network for the chickenpox disease model.

Computers in biology and medicine
OBJECTIVES: The current research investigations designates the numerical solutions of the chickenpox disease model by applying a proficient optimization framework based on the artificial neural network. The mathematical form of the chickenpox disease...

Comparing Scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations.

CPT: pharmacometrics & systems pharmacology
A variety of classical machine learning (ML) approaches has been developed over the past decade aiming to individualize drug dosages based on measured plasma concentrations. However, the interpretability of these models is challenging as they do not ...

Autoregressive exogenous neural structures for synthetic datasets of olive disease control model with fractional Grünwald-Letnikov solver.

Computers in biology and medicine
A fundamental element of the Mediterranean diet, olive oil is abundant in heart-healthy monounsaturated fats and antioxidants, lowering the risk of cardiovascular diseases. However, the olive oil industry confronts hurdles arising from olive tree dis...

Leveraging public AI tools to explore systems biology resources in mathematical modeling.

NPJ systems biology and applications
Predictive mathematical modeling is an essential part of systems biology and is interconnected with information management. Systems biology information is often stored in specialized formats to facilitate data storage and analysis. These formats are ...

A wing-flapping robot with a bio-inspired folding mechanism derived from the beetle's hind wing.

Bioinspiration & biomimetics
When the beetle lands on the target, the hind wings fold regularly to form smaller wing packages and are hidden on the ventral side of the elytra due to the interaction between the elytra and abdomen. Its complex folding pattern is attributed to the ...

Development of an mPBPK machine learning framework for early target pharmacology assessment of biotherapeutics.

Scientific reports
Development of antibodies often begins with the assessment and optimization of their physicochemical properties, and their efficient engagement with the target of interest. Decisions at the early optimization stage are critical for the success of the...

Jointed tails enhance control of three-dimensional body rotation.

Journal of the Royal Society, Interface
Tails used as inertial appendages induce body rotations of animals and robots-a phenomenon that is governed largely by the ratio of the body and tail moments of inertia. However, vertebrate tails have more degrees of freedom (e.g. number of joints an...

Machine Learning for Prediction of Drug Concentrations: Application and Challenges.

Clinical pharmacology and therapeutics
With the advancements in algorithms and increased accessibility of multi-source data, machine learning in pharmacokinetics is gaining interest. This review summarizes studies on machine learning-based pharmacokinetics analysis up to September 2024, i...

Exploring the Influence of Feature Selection Methods on a Random Forest Model for Gait Time Series Prediction Using Inertial Measurement Units.

Journal of biomechanical engineering
Despite the increasing use of inertial measurement units (IMUs) and machine learning techniques for gait analysis, there remains a gap in which feature selection methods are best tailored for gait time series prediction. This study explores the impac...