ReviewPharmaceuticals (Basel, Switzerland)2025
Exploring Experimental and In Silico Approaches for Antibody-Drug Conjugates in Oncology Therapies.
Review in Pharmaceuticals (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Advances in improving cancer immunotherapy with nanotechnology: from smart nanoparticles to synergistic combination strategies.Molecular cancer · 2026Review
- Advances and Future Directions in Antibody-Drug Conjugates: From Paradigm Shifts to Data-Driven Design.Cancers · 2026Review
- Toxicities of Antibody-Drug Conjugates in Breast Cancer: From Mechanistic Insights to Clinical Management.Pharmaceutics · 2026Review
- Article
- Antibody-Drug Conjugates Drug Product Formulation and Process Development, Scalability and Stability Considerations.AAPS PharmSciTech · 2026Review
- Antibody-Drug Conjugates and Beyond: Next-Generation Targeted Therapies for Breast Cancer.Cancers · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
BACKGROUND/
objectivesAntibody-drug conjugates are a rapidly evolving class of cancer therapeutics that combine the specificity of monoclonal antibodies with the potency of cytotoxic drugs. This review explores experimental and computational advances in ADC design, focusing on structural elements and optimization strategies.
methodsWe examined recent developments in the mechanisms of action, antibody engineering, linker chemistries, and payload selection. Emphasis was placed on experimental strategies and computational tools, including molecular modeling and AI-driven structure prediction.
resultsADCs function through both internalization-dependent and -independent mechanisms, enabling targeted drug delivery and bystander effects. The therapeutic efficacy of ADCs depends on key factors: antigen specificity, linker stability, and payload potency. Linkers are categorized as cleavable or non-cleavable, each with distinct advantages. Payloads-mainly tubulin inhibitors and DNA-damaging agents-require extreme potency to be effective. Computational methods have become essential for antibody modeling, developability assessment, and in silico optimization of ADC components, accelerating candidate selection and reducing experimental labor.
conclusionsThe integration of experimental and in silico approaches enhances ADC design by improving selectivity, stability, and efficacy. These strategies are critical for advancing next-generation ADCs with broader applicability and improved therapeutic indices.
Indexed as
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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.