Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Comput Biol ChemAug 3, 2026 (epub)
Clinical ResearchOncology (Medical)

Wahyu Rahmaniar, Anggit Listyacahyani Sunarwidhi, Ari Hernawan

✦ AI-curated · Sources linked

In 30 seconds

This systematic review examines the role of artificial intelligence (AI) in the discovery of anticancer drugs from marine natural products (MNPs) derived from macroalgae and sponges. It highlights the shift in challenges from algorithmic capabilities to data infrastructure and validation. The review emphasizes the need for improved bioactivity records to enhance the reliability of AI-driven drug candidates.

Key findings

  • AI methods are increasingly used in MNP anticancer drug discovery, including bioactivity prediction and target identification.
  • The review identifies a shift in bottlenecks from algorithmic capability to data infrastructure and experimental validation.
  • Sparse and heterogeneous bioactivity records limit the learning of current AI models, affecting candidate reliability.
  • A proposed roadmap includes prioritizing open MNP-specific benchmarks and active learning loops.

Why it matters

Understanding the integration of AI in drug discovery can enhance the efficiency of developing new anticancer therapies from marine sources. Improved methodologies may lead to more effective treatments and better patient outcomes in oncology.

Source

PubMed · PMID 42556018

Published in Comput Biol Chem. This summary was written by xxcode from the publication's abstract and metadata. It is not peer reviewed and is not a substitute for the original article. For clinical decisions, review the original publication.

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