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Suggested Citation:"Appendix A: Statement of Task." National Academies of Sciences, Engineering, and Medicine. 2019. Improving Cancer Diagnosis and Care: Clinical Application of Computational Methods in Precision Oncology: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25404.
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Appendix A

Statement of Task

An ad hoc committee will plan and host a 1.5-day public workshop to examine the clinical use of high-dimensional omics data and computational methods in precision oncology research and clinical care. The workshop will feature invited presentations and panel discussions on topics that may include

  • Challenges and opportunities to use omics data to develop precision medicine approaches and technologies in cancer care.
  • Potential standards and best practices for computational software and methodological approaches for the use of big data to inform clinical care of patients with cancer, especially in regard to multiparameter/multitreatment testing and interpretation.
  • Potential opportunities to improve the translation of omics technologies into oncology practice, such as harmonization of standards for omics-based discovery, development, and evaluation; data sharing and reproducibility; oversight and regulation; education, training, and workforce needs; and use of dissemination and implementation science strategies.

The committee will develop the agenda for the workshop sessions, select and invite speakers and discussants, and moderate the discussions. A proceedings of the presentations and discussions at the workshop will be prepared by a designated rapporteur in accordance with institutional guidelines.

Suggested Citation:"Appendix A: Statement of Task." National Academies of Sciences, Engineering, and Medicine. 2019. Improving Cancer Diagnosis and Care: Clinical Application of Computational Methods in Precision Oncology: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25404.
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Suggested Citation:"Appendix A: Statement of Task." National Academies of Sciences, Engineering, and Medicine. 2019. Improving Cancer Diagnosis and Care: Clinical Application of Computational Methods in Precision Oncology: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25404.
×
Page 65
Suggested Citation:"Appendix A: Statement of Task." National Academies of Sciences, Engineering, and Medicine. 2019. Improving Cancer Diagnosis and Care: Clinical Application of Computational Methods in Precision Oncology: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/25404.
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Page 66
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A hallmark of high-quality cancer care is the delivery of the right treatment to the right patient at the right time. Precision oncology therapies, which target specific genetic changes in a patient’s cancer, are changing the nature of cancer treatment by allowing clinicians to select therapies that are most likely to benefit individual patients. In current clinical practice, oncologists are increasingly formulating cancer treatment plans using results from complex laboratory and imaging tests that characterize the molecular underpinnings of an individual patient’s cancer. These molecular fingerprints can be quite complex and heterogeneous, even within a single patient. To enable these molecular tumor characterizations to effectively and safely inform cancer care, the cancer community is working to develop and validate multiparameter omics tests and imaging tests as well as software and computational methods for interpretation of the resulting datasets.

To examine opportunities to improve cancer diagnosis and care in the new precision oncology era, the National Cancer Policy Forum developed a two-workshop series. The first workshop focused on patient access to expertise and technologies in oncologic imaging and pathology and was held in February 2018. The second workshop, conducted in collaboration with the Board on Mathematical Sciences and Analytics, was held in October 2018 to examine the use of multidimensional data derived from patients with cancer, and the computational methods that analyze these data to inform cancer treatment decisions. This publication summarizes the presentations and discussions from the second workshop.

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