ReviewFrontiers in artificial intelligence2025
AI alignment is all your need for future drug discovery.
Review in Frontiers in artificial intelligence, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- The Design-Driven Innovation Path of Human-Centered Artificial Intelligence in the Field of Healthcare: Theory, Practice, and Future Prospects.Healthcare (Basel, Switzerland) · 2026Review
- The Pharmaceutical Industry in 2025: An Analysis of FDA Drug Approvals from the Perspective of Molecules.Molecules (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, the integration of artificial intelligence (AI) with drug discovery has become a promising frontier in biomedical research. However, as artificial intelligence systems become increasingly complex, ensuring their alignment with human values and goals becomes essential. Specifically, combining artificial intelligence systems with human values is crucial for reducing potential risks in the field of drug discovery and maximizing social benefits. This article explores the concepts and challenges related to alignment with artificial intelligence in the context of drug discovery, emphasizing on human-centered approaches to AI development and deployment. We further investigated popular technology frameworks designed for human-centered AI alignment, aimed at improving the robustness and interpretability of AI models. We provide some insights into the challenges of human-centered AI alignment, which represents a significant advancement in addressing robustness and interpretability, thus taking a step forward in the field of AI alignment research. Finally, we discuss strategies for systematically integrating human values into AI-driven drug discovery systems. This article aims to emphasize the importance of AI alignment as a foundational principle in the field of drug discovery and advocate the perspective that "AI alignment is all your need for future drug discovery".
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.