Researchers are using 3D printing to gain insights that contribute to advances in basic biomedical research and the development of precision medical therapies by creating 3D models of pathogens, tumors, normal tissues, cells, and biomolecules. Dr. Sriram Subramaniam, principal investigator in the Laboratory of Cell Biology at the NCI Center for Cancer Research (CCR), uses 3D printing as both an educational and a research tool. Referring to the work of his own research team, he asserts that “You always learn more when you look at things in 3D.”
The value of printing as an aid for learning and discovery in structural biology can scarcely be overstated. The technology makes the relationship between molecular shape and biological function immediate and tangible, allowing 2D representations of protein, virus or cell structure to “jump” off the page. Researchers are able to appreciate the shapes of objects of biological interest because they can hold them in their hands. Furthermore, with 3D printing getting cheaper, it’s being used for a whole spectrum of applications that scientists can easily share with other researchers. It has also rapidly become an essential communication tool serving as a bridge for nonscientists by allowing them to see and touch biological structures that used to be accessible only through the use of complex scientific instrumentation. As a result, 3D printing has begun taking on the role of an open-science gateway that allows important discoveries to be shared by a wider audience.
We’ve shaped our policies and practices in the NCI Center of Biomedical Informatics and Information Technology (CBIIT) to support the principles of open science. An essential part of our mission is to facilitate open resource sharing and collaboration. After learning about the establishment of an NIH 3D Print Exchange, we invited Dr. Darrell Hurt, who led development of the Exchange, to introduce the resource to NCI via the CBIIT Speaker Series. Dr. Hurt heads the Computational Biology Section of the Bioinformatics and Computational Biosciences Branch (BCBB) in the Office of Cyber Infrastructure and Computational Biology at the National Institute of Allergy and Infectious Diseases (NIAID), and has collaborated with Dr. Subramaniam to print various protein structures. One of the Exchange’s main goals is to facilitate the dissemination of open data by making 3D-model files free and easily accessible to the scientific community as well as encourage the use of open-source software.
The 3D Print Exchange is also a centralized portal allowing scientists to find accurate, high-quality 3D models that encourages its users to participate in open science, open data sharing, and collaborative communication. It maintains a repository of downloadable 3D-model files that can be printed, as well as tutorials with instructions for 3D-modeling software, forums, and public outreach events. The Exchange achieves one of Dr. Subramaniam’s goals by giving researchers something tangible and solid to study, which results in a more comprehensive understanding of the connection between structure and function.
Beyond the laboratory, 3D printing has started to enter the clinic as an aid to developing personalized medical interventions that contribute to more precise diagnoses and treatments in oncology. Marcelino L. Bernardo, a staff scientist in the CCR Molecular Imaging Program, uses it to make individually designed prostate molds using patient MRIs. He started using 3D printing because it was the best method for making functioning prototypes and it was so widely accessible. He notes that the technology makes it easier to “take something in a computer into the physical world.” In order to make these customized molds, Bernardo uses open-source software to generate a 3D model of the patient’s prostate. From there, he creates a pre-design shape of a cubic mold and subtracts the prostate model from it in order to generate a file for the mold itself. After that, the mold can be printed on a low-cost 3D printer, such as an open-source RepRap printer.
These molds have made possible an important advance in treatment since the primary treatment for prostate cancer usually involves removing the entire gland even when only a few areas are contaminated by cancer or the tumor is very low grade. Although precision treatments for prostate and other types of cancer are still largely on the horizon, 3D printing is already making it easier to improve diagnosis and medical therapies because it helps identify the areas that should be treated so that the whole gland doesn’t have to be removed. It has helped the researchers in the Molecular Imaging Program and their collaborators in other CCR branches to pioneer a new treatment that involves using a laser to selectively oblate cancer cells.
The need for highly precise treatments tailored to individual patients is particularly acute in oncology because the diseases that we classify as “cancers” are genetic disorders and can manifest themselves in many different ways depending on the patient’s genetic background and mutational profile. Because of this, it is essential that cancer treatments be both precise and diverse so that the cancer can be treated most effectively. The ease with which 3D printing can now be done provides yet another tool that promises to leverage technological advances in the quest for customized cancer treatments.
To learn more about how 3D-printing is being used in the biomedical community, please consult these sources:
Articles and references to Dr. Subramaniam’s work:
Dr. Bernardo’s papers:
Shah V, Pohida T, Turkbey B, Mani H, Merino M, Pinto PA, Choyke P, Marcelino B, A method for correlating in vivo prostate magnetic resonance imaging and histopathology using individualized magnetic resonance-based molds. Review of Scientific Instruments, 2009; 80, 104301.
Mena E, Turkbey B, Mani H, Adler S, Valera VA, Bernardo M, Shah V, Pohida T, McKinney Y, Kwarteng G, Daar D, Lindenberg ML, Eclarinal P, Wade R, Linehan WM, Merino MJ, Pinto PA, Choyke PL, Kurdziel KA, 11C-Acetate PET/CT in localized prostate cancer: a study with MRI and histopathologic correlation. J Nucl Med, 2012 Apr; 53(4):538-45.
Shah V, Turkbey B, Mani H, Pang Y, Pohida T, Merino MJ, Merino, Pinto PA, Choyke PL, Bernardo M, Decision support system for localizing prostate cancer based on multiparametric magnetic resonance imaging. Med Phys, Jul 2012; 39(7): 4093–4103.
Other NCIP Blog Posts dealing with open data and open science:
- Open development
- Cancer Genomics Cloud
- NCIP Hub development
Cristina Galvez was a CBIIT summer intern in 2014 and is a student at Santa Fe University of Art and Design.