At any given time, most cancer patients receive treatment that does not significantly benefit them while enduring bodily and financial toxicity. Aiming to guide each patient to the most appropriate treatment, precision medicine is expanding from genetic mutations to other factors of clinical outcome. A concerted effort has been made to create “avatars” of patient tumors to test and select treatments before administering them to patients.
recently published cancer cell Representing several National Cancer Institute consortia and featuring key opinion leaders from the research and clinical sectors in the United States and Europe, the paper outlined the vision for next-generation, functional precision medicine by proposing measures to enable 3D patient tumor avatars (3D-PTAs) in the clinic. guides treatment decisions. The corresponding author of this article and chief scientific officer of the Terasaki Institute for Biomedical Innovation, Dr. According to Xiling Shen, the power of 3D-PTAs containing patient-derived organoids, 3D bioprinting and microscale models, the microenvironment and their speed and scalability to test and predict the efficacy of prospective therapeutic drugs, and accurate real-life depiction of a tumor. However, to fully realize this goal and maximize clinical accuracy, many steps are required to standardize methods and criteria, design clinical trials, and incorporate complete patient data for the best possible outcome in personalized care.
The use of such tools and resources may involve a wide variety of materials, methods, and processing of data, but great efforts are required to pool, standardize, and validate uses to ensure accuracy and integrity in any clinical decision-making. 3D-PTAs. Initiatives from the National Cancer Institute’s Patient Induced Cancer Models Consortium and other groups have initiated formal protocol standardizations, and much work remains to be done.
The authors emphasize that in addition to consolidating and standardizing protocols across multiple research facilities, measurements should be made using validated software pipelines and information should be coded and shared among all research groups involved. They also recommend compiling a more comprehensive and comprehensive clinical patient profile that covers every aspect of a patient’s history, including not only medical but also demographic information; these are important factors in patient outcomes. To achieve standardization in this regard, the regulatory infrastructure provided by the National Institutes of Health and other institutes and journals must be incorporated to allow reliable global data sharing and access.
Clinical trials are also an important part of the 3D-PTA effort, and to date, studies have been conducted to examine clinical trial workflows and turnaround times using 3D-PTA. The authors propose innovative clinical trial designs that can help select patients for particular trials or specific treatments, especially when combined with the patient’s clinical and demographic information.
Combining these patient omic profiles with information from 3D-PTA functional data libraries can be facilitated by well-defined computational lines, and the authors advocate the use of relevant consortia such as the NCI Patient-Derived Cancer Model Program, PDXnet, Tissue Engineering Collaborative. and Cancer Systems Biology Centers and European research infrastructure such as INFRAFRONTIER, EuroPDX)
Integrating data from existing 3D-PTA initiatives, consortia, and biobanks with ohmic profiles can take precision medicine to a new level and provide advanced tools for making optimal choices between approved therapeutic drugs and investigational, alternative, non-chemotherapeutic drugs. It can also provide solutions for patients experiencing drug resistance and expand opportunities for drug reuse.
“The integration of the 3D-PTA platform is a game-changing tool for oncological drug development,” said Ali Khademhosseini, Director and CEO of Terasaki Institute for Biomedical Innovation. “We must combine it robustly with existing cancer genomics to produce the most powerful paradigm for precision oncology.”