AI Scientific Assistants Rise: Google’s Co‑Scientist and FutureHouse’s Robin

Two groundbreaking Nature papers introduce Google DeepMind’s multi‑agent Co‑Scientist and FutureHouse’s Robin, AI systems that combine literature search, hypothesis generation, experimental design and data analysis to accelerate drug repurposing for leukemia and age‑related macular degeneration, demonstrating how AI is evolving from a tool into a collaborative scientific partner.

AIDeepMindFutureHouse

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AI Scientific Assistants Rise: Google’s Co‑Scientist and FutureHouse’s Robin

DataFunTalk

Dec 25, 2022 · Artificial Intelligence

GraphSynergy: A Network‑Inspired Deep Learning Model for Predicting Anti‑Cancer Drug Combinations

GraphSynergy integrates network science and graph convolutional networks to predict synergistic anti‑cancer drug combinations by modeling protein‑protein interaction networks, computing therapy and toxicity scores, and outperforming baseline methods on DrugCombDB and Oncology‑Screen datasets, while offering interpretable mechanisms for drug repurposing.

AI drug discoverycancer therapydrug repurposing

0 likes · 19 min read

GraphSynergy: A Network‑Inspired Deep Learning Model for Predicting Anti‑Cancer Drug Combinations

DataFunSummit

Jun 7, 2022 · Artificial Intelligence

Thematic Role Semantic Recognition and Fine-Grained Biomedical Knowledge Mining for Drug Repurposing

This presentation explores how deep semantic role labeling and multimodal data fusion of biomedical literature can build fine‑grained knowledge graphs that enable drug repurposing, describing the AGAC corpus, modeling approaches, evaluation results, and future research directions.

AIBiomedical NLPdrug repurposing

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Thematic Role Semantic Recognition and Fine-Grained Biomedical Knowledge Mining for Drug Repurposing