ADCdb

ADCdb provides a curated database of antibody-drug conjugates (ADCs), including detailed pharma-information and literature-reported biological activities to support ADC design and evaluation.


Key Features:

  • Extensive Data Collection: Contains 6,572 ADC entries categorized by development stage: 359 ADCs approved by the FDA or in clinical trial pipelines, 501 in preclinical testing, 819 with in-vivo testing data, 1,868 with cell line/target testing data, and 3,025 lacking in-vivo/cell line/target testing data.
  • Comprehensive Pharma-Information: Each entry includes explicit pharma-information describing the chemical and biological properties of ADCs, including antibody components and cytotoxic payloads.
  • Literature-Reported Activities: Compiles 9,171 literature-reported activities derived from sources such as clinical trial pipelines, model organisms, and patient/cell-derived xenograft models.
  • Multi-Perspective Integration: Integrates data across development stages and testing types to provide a holistic view of each ADC's potential efficacy and safety profile.

Scientific Applications:

  • Drug Design and Development: Enables comparison and analysis of existing ADCs to inform the design of new ADC candidates.
  • Clinical Research: Provides biological activity and development-stage data to support evaluation of ADCs in clinical trial pipelines.
  • Preclinical Studies: Supplies preclinical and in-vivo/cell line testing data to aid optimization of ADC candidates prior to human studies.

Methodology:

Manual curation, compilation of literature-reported activities, and categorization of ADC entries by development stage.

Topics

Details

License:
CC-BY-NC-4.0
Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Added:
3/21/2024
Last Updated:
11/24/2024

Operations

Publications

Shen L, Sun X, Chen Z, Guo Y, Shen Z, Song Y, Xin W, Ding H, Ma X, Xu W, Zhou W, Che J, Tan L, Chen L, Chen S, Dong X, Fang L, Zhu F. ADCdb: the database of antibody–drug conjugates. Nucleic Acids Research. 2023;52(D1):D1097-D1109. doi:10.1093/nar/gkad831. PMID:37831118. PMCID:PMC10768060.

PMID: 37831118
Funding: - Natural Science Foundation of China: 22220102001, 81973172, 81973396, 82173660, 82274020, 82373790, U1909208 - Natural Science Fund for Distinguished Young Scholars of Zhejiang: LR21H300001, LR21H300003 - Key R&D Program of Zhejiang Province: 2023C03111