MOViDA: multiomics visible drug activity prediction with a biologically informed neural network model.

ABSTRACT:

Motivation

The process of drug development is inherently complex, marked by extended intervals from the inception of a pharmaceutical agent to its eventual launch in the market. Additionally, each phase in this process is associated with a significant failure rate, amplifying the inherent challenges of this task. Computational virtual screening powered by machine learning algorithms has emerged as a promising approach for predicting therapeutic efficacy. However, the complex relationships between the features learned by these algorithms can be challenging to decipher.

Results

We have engineered an artificial neural network model designed specifically for predicting drug sensitivity. This model utilizes a biologically informed visible neural network, thereby enhancing its int

SUBMITTER: Ferraro L 

PROVIDER: S-EPMC10375315 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature