ReviewPatterns (New York, N.Y.)2023
Computer-aided multi-objective optimization in small molecule discovery.
Review in Patterns (New York, N.Y.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
What it found
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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
58 citing papers in PubMed.
- Multi-objective-conditioned-return-blocks decision transformer: a novel approach for multi-objective de novo drug design.Bioinformatics (Oxford, England) · 2026Article
- MoDeMol: A Decomposition-Based Evolutionary Framework for Multi-Objective Molecular Optimization.International journal of molecular sciences · 2026Article
- Multi-Endpoint Prediction of Bioactivity and ADMET Properties Coupled with Multi-Objective Optimization in Molecular Descriptor Space for Candidate ERα Antagonists.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Multi-objective optimization in the context of generative chemistry.Nature communications · 2026Review
- Mixture-Quantitative Structure-Property Relationship Approaches for Jet Fuel-Component Blends: A Review.Molecular informatics · 2026Review
- A Problem-Setup-Centric Framework for Mixed-Variable Chemical Formulation Optimization with Customized Constraints.Materials (Basel, Switzerland) · 2026Article
- Artificial Intelligence for Discovery in Life Sciences.Bioconjugate chemistry · 2026Review
- Multi-Property De Novo Drug Design Using Deep Learning-Based Knowledge Distillation and Reinforcement Learning.International journal of molecular sciences · 2026Article
- In Silico Drug Design and Discovery: Big Data for Small Molecule Design-2nd Edition.Biomolecules · 2026Article
- Precision oncology in the age of AI: lessons from AI-driven drug discovery and clinical translation.BJC reports · 2026Review
- A simple compound prioritization method for drug discovery considering multi-target binding.Digital discovery · 2026Article
- Molecular Design with Artificial Intelligence: Progress and Perspectives for Small Molecules.Chemical reviews · 2026Review
- Inverse Molecular Design for the Discovery of Organic Energy Transfer Photocatalysts: Bridging Global and Local Chemical Space Exploration.Journal of the American Chemical Society · 2026Article
- Developments and challenges in hit progression within fragment-based drug discovery.Nature communications · 2026Review
- Generative Multiobjective Bayesian Optimization with Scalable Batch Evaluations for Sample-Efficient De Novo Molecular Design.Industrial & engineering chemistry research · 2026Article
- MMPCS: multi-view molecular pretraining based on consistency information and specific information.Bioinformatics (Oxford, England) · 2026Article
- Application and Prospects of Large Language Models in Small-Molecule Drug Discovery.Analytical chemistry · 2025Review
- Explore antibody repertoire in the era of AI.Acta biochimica et biophysica Sinica · 2025Article
- Molecule generation for target protein binding with hierarchical consistency diffusion model.Chemical science · 2025Article
- Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular discovery is a multi-objective optimization problem that requires identifying a molecule or set of molecules that balance multiple, often competing, properties. Multi-objective molecular design is commonly addressed by combining properties of interest into a single objective function using scalarization, which imposes assumptions about relative importance and uncovers little about the trade-offs between objectives. In contrast to scalarization, Pareto optimization does not require knowledge of relative importance and reveals the trade-offs between objectives. However, it introduces additional considerations in algorithm design. In this review, we describe pool-based and
Identifiers
What OpenQuestion 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 OpenQuestion graph.