AIMC Topic: Models, Biological

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Using a multi-strain infectious disease model with physical information neural networks to study the time dependence of SARS-CoV-2 variants of concern.

PLoS computational biology
With the ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its increasing adaptation to humans, several variants of concern (VOCs) and variants of interest (VOIs) have been identified since late 2020. These include...

Resilience of hierarchical actuators highlighted by a myosin-to-muscle mock-up.

Bioinspiration & biomimetics
Skeletal muscle is the main actuator of various families of vertebrates (mammals, fish, reptiles). It displays remarkable robustness to micro-damage, that supposedly originates both from its redundant hierarchical structure and its nervous command. A...

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...

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...

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 ...

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...

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...