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Nanotechnology Data Tools

Data sharing is essential to scientific progress. NCI has engaged in developing effective data sharing practices and built the caNanoLab database.

caNanoLab is a data sharing portal designed to facilitate information sharing across the biomedical nanotechnology research community to expedite and validate the use of nanotechnology in biomedicine. caNanoLab provides support for the annotation of nanomaterials with characterizations resulting from physico-chemical, in vitro and in vivo assays, and the sharing of these characterizations and associated nanotechnology protocols in a secure fashion.

Please refer to the new Data Management and Sharing (DMS) policy that the NIH has issued, effective January 25, 2023, to promote the sharing of scientific data.

Data Sharing Tools

  • Cancer Nanotechnology Laboratory (caNanoLab) Data Portal: The caNanoLab is a web portal designed to facilitate sharing of well–characterized biomedical nanomaterial data in the research community.
  • Nanomaterial Registry: The Nanomaterial Registry is a free, web-based resource launched by Research Triangle Institute International. It organizes and evaluates the biological and environmental implications of well-characterized nanomaterials from publicly available resources.
  • National Cancer Informatics Program Nanotechnology Working Group (NCIP Nano WG): The NCIP Nano WG was established to work closely with the nanotechnology research community to develop and encourage adoption of a shared informatics infrastructure that describes the physicochemical properties, biological interactions, and environmental interactions of nanomaterials. The NCIP Nano WG is comprised of over 20 active participants from academia, government and industry.

caNanoLab and Data Sharing Publications

Trends and patterns in cancer nanotechnology research: A survey of NCI's caNanoLab and nanotechnology characterization laboratory. Ke W, Crist RM, Clogston JD, Stern ST, Dobrovolskaia MA, Grodzinski P, Jensen MA. Adv Drug Deliv Rev. 2022 Dec;191:114591

Merging data curation and machine learning to improve nanomedicines. Chen C, Yaari Z, Apfelbaum E, Grodzinski P, Shamay Y, Heller DA. Adv Drug Deliv Rev. 2022 Apr;183:114172

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