AIMC Topic: Models, Biological

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Machine Learning Models for Human Pharmacokinetic Parameters with In-House Validation.

Molecular pharmaceutics
Prior to clinical development, a comprehensive pharmacokinetic characterization of a novel drug is required to understand its exposure at the site of action and elimination. Accordingly, assays and animal pharmacokinetic studies are regularly employ...

A transfer learning approach for predictive modeling of bioprocesses using small data.

Biotechnology and bioengineering
Predictive modeling of new biochemical systems with small data is a great challenge. To fill this gap, transfer learning, a subdomain of machine learning that serves to transfer knowledge from a generalized model to a more domain-specific model, prov...

Sensing small interaction forces through proprioception.

Scientific reports
Understanding the human motor control strategy during physical interaction tasks is crucial for developing future robots for physical human-robot interaction (pHRI). In physical human-human interaction (pHHI), small interaction forces are known to co...

Robotic end-to-end fusion of microtubules powered by kinesin.

Science robotics
The active assembly of molecules by nanorobots has advanced greatly since “molecular manufacturing”—that is, the use of nanoscale tools to build molecular structures—was proposed. In contrast to a catalyst, which accelerates a reaction by smoothing t...

Machine Learning Prediction of the Three Main Input Parameters of a Simplified Physiologically Based Pharmacokinetic Model Subsequently Used to Generate Time-Dependent Plasma Concentration Data in Humans after Oral Doses of 212 Disparate Chemicals.

Biological & pharmaceutical bulletin
Physiologically based pharmacokinetic (PBPK) modeling has the potential to play significant roles in estimating internal chemical exposures. The three major PBPK model input parameters (i.e., absorption rate constants, volumes of the systemic circula...

Predicting physiological aging rates from a range of quantitative traits using machine learning.

Aging
It is widely thought that individuals age at different rates. A method that measures "physiological age" or physiological aging rate independent of chronological age could therefore help elucidate mechanisms of aging and inform an individual's risk o...

Flow visualization and force measurement of the clapping effect in bio-inspired flying robots.

Bioinspiration & biomimetics
In this paper, we perform experimental investigations of the aerodynamic characteristics due to wing clapping in bio-inspired flying robots; i.e., micro-air-vehicles (MAVs) that fly by flapping their wings. For this purpose, four flapping MAV models ...

OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany.

PLoS computational biology
Mathematical models in epidemiology are an indispensable tool to determine the dynamics and important characteristics of infectious diseases. Apart from their scientific merit, these models are often used to inform political decisions and interventio...

Prediction of Micronucleus Assay Outcome Using In Vivo Activity Data and Molecular Structure Features.

Applied biochemistry and biotechnology
In vivo micronucleus assay is the widely used genotoxic test to determine the extent of chromosomal aberrations caused by the chemicals in human beings, which plays a significant role in the drug discovery paradigm. To reduce the uncertainties of the...