ibm-research/biomed.omics.bl.sm.ma-ted-458m.moleculenet_clintox_tox
Drugs must satisfy stringent criteria for both efficacy and safety. This model predicts the likelihood of failure in clinical toxicity trials for small-molecule drugs, represented using SMILES (Simplified Molecular Input Line Entry System) strings.
README
tags: drug-discovery ibm mammal pytorch small molecules drugs smiles MoleculeNet toxicity safetensors biomed-multi-alignment license: apache-2.0 libraryname: biomed-multi-alignment basemodel: ibm/biomed.omics.bl.sm.ma-ted-458m Drugs must satisfy stringent criteria for both efficacy and safety. This model predicts the likelihood of failure in clinical toxicity trials for small-molecule drugs, represented using SMILES (Simplified Molecular Input Line Entry System) strings. It is a fine-tuned…
Source attribution
- HuggingFace — ibm-research/biomed.omics.bl.sm.ma-ted-458m.moleculenet_clintox_tox
Related resources
Drugs targeting the central nervous system must meet stringent criteria for both efficacy and safety, including their ability to penetrate the blood-brain barrier (BBB). This model predicts the likelihood of small-molecule drugs crossing the BBB, a critical factor in CNS drug development.
Drugs must satisfy stringent criteria for both efficacy and safety. This model predicts the likelihood of FDA approval for small-molecule drugs, represented using SMILES (Simplified Molecular Input Line Entry System) strings.
T-cell receptor (TCR) binding to immunogenic peptides (epitopes) presented by major histocompatibility complex (MHC) molecules is a critical mechanism in the adaptive immune system, essential for antigen recognition and triggering immune responses.
ibm-research/biomed.omics.bl.sm.ma-ted-458m
by ibm-researchThe ibm/biomed.omics.bl.sm.ma-ted-458m model is a biomedical foundation model trained on over 2 billion biological samples across multiple modalities, including proteins, small molecules, and single-cell gene data. Designed for robust performance, it achieves state-of-the-art results over a variety…
Accurate prediction of drug-target binding affinity is essential in the early stages of drug discovery. This is an example of finetuning ibm/biomed.omics.bl.sm-ted-400 the task. Prediction of binding affinities using pKd, the negative logarithm of the dissociation constant, which reflects the…
Protein solubility is a critical factor in both pharmaceutical research and production processes, as it can significantly impact the quality and function of a protein. This is an example for finetuning ibm/biomed.omics.bl.sm-ted-458m for protein solubility prediction (binary classification) based…