
## Dataset description

As a membrane separating circulating blood and brain extracellular fluid, the blood-brain barrier (BBB) is the protection layer that blocks most foreign drugs. Thus the ability of a drug to penetrate the barrier to deliver to the site of action forms a crucial challenge in development of drugs for central nervous system.

## Task description
Binary classification. Given a drug SMILES string, predict the activity of BBB.

## Dataset statistics
Total: 1,975; Train_val: 1,580; Test: 395

## Dataset split
Random split on 70% training, 10% validation, and 20% testing

To load the dataset in TDC, type

```python
from tdc.single_pred import ADME
data = ADME(name = 'BBB_Martins')
```

## Model description
AttentiveFP is a Graph Attention Network-based molecular representation learning method. The model is tuned with 100 runs using the Ax platform.
To load the pre-trained model, type

```python
from tdc import tdc_hf_interface
tdc_hf = tdc_hf_interface("BBB_Martins-AttentiveFP")
# load deeppurpose model from this repo
dp_model = tdc_hf_herg.load_deeppurpose('./data')
tdc_hf.predict_deeppurpose(dp_model, ['YOUR SMILES STRING'])
```

## References
* Dataset entry in Therapeutics Data Commons, https://tdcommons.ai/single_pred_tasks/adme/#bbb-blood-brain-barrier-martins-et-al
* Martins, Ines Filipa, et al. “A Bayesian approach to in silico blood-brain barrier penetration modeling.” Journal of chemical information and modeling 52.6 (2012): 1686-1697.
{"language": ["en"], "license": "bsd-2-clause", "library_name": "tdc", "tags": ["biology", "chemistry", "therapeutic science", "drug design", "drug development", "therapeutics"], "metrics": ["accuracy", "AUC ROC", "precision", "recall"]}
tdc biology chemistry therapeutic science drug design drug development therapeutics en license:bsd-2-clause region:us
TAGS
#tdc #biology #chemistry #therapeutic science #drug design #drug development #therapeutics #en #license-bsd-2-clause #region-us 


## Dataset description

As a membrane separating circulating blood and brain extracellular fluid, the blood-brain barrier (BBB) is the protection layer that blocks most foreign drugs. Thus the ability of a drug to penetrate the barrier to deliver to the site of action forms a crucial challenge in development of drugs for central nervous system.

## Task description
Binary classification. Given a drug SMILES string, predict the activity of BBB.

## Dataset statistics
Total: 1,975; Train_val: 1,580; Test: 395

## Dataset split
Random split on 70% training, 10% validation, and 20% testing

To load the dataset in TDC, type



## Model description
AttentiveFP is a Graph Attention Network-based molecular representation learning method. The model is tuned with 100 runs using the Ax platform.
To load the pre-trained model, type



## References
* Dataset entry in Therapeutics Data Commons, URL
* Martins, Ines Filipa, et al. “A Bayesian approach to in silico blood-brain barrier penetration modeling.” Journal of chemical information and modeling 52.6 (2012): 1686-1697.
## Dataset description

As a membrane separating circulating blood and brain extracellular fluid, the blood-brain barrier (BBB) is the protection layer that blocks most foreign drugs. Thus the ability of a drug to penetrate the barrier to deliver to the site of action forms a crucial challenge in development of drugs for central nervous system. ## Task description
Binary classification. Given a drug SMILES string, predict the activity of BBB. ## Dataset statistics
Total: 1,975; Train_val: 1,580; Test: 395 ## Dataset split
Random split on 70% training, 10% validation, and 20% testing

To load the dataset in TDC, type ## Model description
AttentiveFP is a Graph Attention Network-based molecular representation learning method. The model is tuned with 100 runs using the Ax platform.
To load the pre-trained model, type ## References
* Dataset entry in Therapeutics Data Commons, URL
* Martins, Ines Filipa, et al. “A Bayesian approach to in silico blood-brain barrier penetration modeling.” Journal of chemical information and modeling 52.6 (2012): 1686-1697.
TAGS
#tdc #biology #chemistry #therapeutic science #drug design #drug development #therapeutics #en #license-bsd-2-clause #region-us 
 ## Dataset description

As a membrane separating circulating blood and brain extracellular fluid, the blood-brain barrier (BBB) is the protection layer that blocks most foreign drugs. Thus the ability of a drug to penetrate the barrier to deliver to the site of action forms a crucial challenge in development of drugs for central nervous system. ## Task description
Binary classification. Given a drug SMILES string, predict the activity of BBB. ## Dataset statistics
Total: 1,975; Train_val: 1,580; Test: 395 ## Dataset split
Random split on 70% training, 10% validation, and 20% testing

To load the dataset in TDC, type ## Model description
AttentiveFP is a Graph Attention Network-based molecular representation learning method. The model is tuned with 100 runs using the Ax platform.
To load the pre-trained model, type ## References
* Dataset entry in Therapeutics Data Commons, URL
* Martins, Ines Filipa, et al. “A Bayesian approach to in silico blood-brain barrier penetration modeling.” Journal of chemical information and modeling 52.6 (2012): 1686-1697.
TAGS
#tdc #biology #chemistry #therapeutic science #drug design #drug development #therapeutics #en #license-bsd-2-clause #region-us 
## Dataset description

As a membrane separating circulating blood and brain extracellular fluid, the blood-brain barrier (BBB) is the protection layer that blocks most foreign drugs. Thus the ability of a drug to penetrate the barrier to deliver to the site of action forms a crucial challenge in development of drugs for central nervous system.## Task description
Binary classification. Given a drug SMILES string, predict the activity of BBB.## Dataset statistics
Total: 1,975; Train_val: 1,580; Test: 395## Dataset split
Random split on 70% training, 10% validation, and 20% testing

To load the dataset in TDC, type## Model description
AttentiveFP is a Graph Attention Network-based molecular representation learning method. The model is tuned with 100 runs using the Ax platform.
To load the pre-trained model, type## References
* Dataset entry in Therapeutics Data Commons, URL
* Martins, Ines Filipa, et al. “A Bayesian approach to in silico blood-brain barrier penetration modeling.” Journal of chemical information and modeling 52.6 (2012): 1686-1697.