Precision Medicine Defined
Precision medicine, also known as personalized medicine, is an innovative omics-based approach to identify, prevent and treat disease using DNA, RNA, and protein analyses. To allow the data-demanding analyses needed to achieve this, high-throughput omics technologies enable the retrieval of comprehensive and holistic biological information, while advanced data processing capabilities enable the data modeling required . Omics disease studies include genomics, transcriptomics, epigenomics, proteomics, and metabolomics .
Precision medicine helps physicians identify unique disease risks for different groups of people, and helps match treatment and prevention strategies that will be more effective and have fewer adverse effects in specific groups of individuals. Precision medicine already plays a role in treating conditions with a strong genetic link, like epilepsy and cystic fibrosis, and is beginning to play a more prominent role in cancer therapeutics. For example, targeted therapies for breast cancer and tumor marker tests for cancer diagnosis .
Precision Medicine and Clinical Trials
The application of precision medicine in clinical research has changed the way trials are conducted and created opportunities for matching the right treatment to the right patient at the right time.
- Precision medicine allows for better matching of patients with novel treatments for their specific cancer mutations. One-person trials, or “n of 1 trials” are already being conducted. The National Cancer Institute’s MATCH project is an example of a precision trial. By checking tumor DNA from patients whose tumors were unresponsive to standard treatment, researchers can match patients with mutations to the appropriate targeted treatment. These innovative trial designs can be conducted in a shorter timeframe and potentially reduce time to market for sponsors.
- Sequencing (ex. DNA or RNA) allows for the identification and analysis of disease subtypes and their response to different treatment strategies.
- Real-world data and access to advanced data processing capabilities has grown and can be leveraged to identify novel mutations to support better drug development.
Oncology Clinical Trials
The shift towards precision medicine in oncology has necessitated innovations in clinical trial design. In response, contract research organizations (CROs) like Vial can consider improving operational efficiency through genetics-driven and adaptive design . For sponsors, adaptive trials can offer a seamless transition to confirmatory trials if early results are positive . Further, researchers need to be aware of the potential changes in the drug approval process by regulatory authorities, who are also working to overcome technological, ethical, and legal barriers in providing precision medicine to their citizens .
Oncology clinical trials have changed from tumor type-centered trials to genetics-directed trials where the core principle is to tailor treatment or prevention strategies to match specific treatments with specific genetic mutations. Novel study designs for precision oncology include biomarker-guided trials  such as basket trials, umbrella trials, or platform trials (collectively known as master protocols). This type of trial design tests multiple therapies, and/or multiple diseases under a single overarching protocol. Benefits of this design:
- A single overarching protocol does not require individual protocols for each sub-study
- Operational efficiency increased as the same infrastructure is used across sub-studies
- Recruitment is from a broader patient population (versus traditional trials)
- Each participant has a greater probability of being on an experimental arm
- Information sharing across sub-studies is possible through innovative statistical methods 
Cancer treatment is moving towards biomarker-driven therapies personalized to patient characteristics . Next-generation sequencing (NGS) is key to the development of precision oncology treatment including targeted therapy which uses cancer genome profiling to identify the mutation and select the best therapeutic, which could be an immunotherapy that helps the immune system attack cancer. Genomic data is used to develop and deploy immunotherapy options.
To improve immunotherapy patient outcomes, genomic-based cancer screening is used to help identify patients most likely to respond to the immunotherapy and in turn, allows customized treatment for each patient. We have already seen this approach taken in treatment decisions for cancer types including colorectal cancer, breast cancer, lung cancer, certain types of leukemia and lymphoma, melanoma, esophageal cancer, stomach cancer, ovarian cancer, and thyroid cancer. For example in breast cancer treatment, targeted therapies treat specific types of cells, namely HER2-positive breast cancer cells; while late-stage cancer patients matched with targeted therapy and immunotherapy have benefited from a significant improvement in survival .
Cancer Moonshot and Immunotherapy
In early 2022, President Joe Biden reignited the Cancer Moonshot initiative which was originally launched in 2016 to accelerate scientific discovery . As part of the Cancer Moonshot initiative, the Immuno-Oncology Translational Network (IOTN) was established to accelerate the translation of basic discoveries to improve outcomes . The Cancer Immune Monitoring and Analysis Centers – Cancer Immunologic Data Commons (CIMAC-CIDC) network was also supported by the Cancer Moonshot initiative and provides correlative analyses for clinical trials in cancer immunotherapy .
Precision medicine has and will continue to change the way trials are conducted, creating opportunities for matching the right treatment to the right patient at the right time. The shift toward precision medicine in oncology has necessitated innovations in clinical trial design where the core principle is to tailor treatment or prevention strategies to match the predictive risk factors of individuals.
- Tebani, A., Afonso, C., Marret, S., & Bekri, S. (2016). Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations. International journal of molecular sciences, 17(9), 1555. https://doi.org/10.3390/ijms17091555
- Rania Ibrahim, Maria Pasic & George M Yousef (2016) Omics for personalized medicine: defining the current we swim in, Expert Review of Molecular Diagnostics, 16:7, 719-722, DOI: 10.1586/14737159.2016.1164601
- National Cancer Institute. NCI Dictionary of Cancer Terms. Precision Medicine. https://www.cancer.gov/publications/dictionaries/cancer-terms/def/precision-medicine
- WebMD. (2019, June 9). How Precision Medicine is Changing Clinical Trials. https://www.webmd.com/cancer/precision-medicine-clinical-trials
- Verweij, J., Hendriks, H. R., Zwierzina, H., & Cancer Drug Development Forum (2019). Innovation in oncology clinical trial design. Cancer treatment reviews, 74, 15–20. https://doi.org/10.1016/j.ctrv.2019.01.001
- Krendyukov A, Singhvi S and Zabransky M (2021) Value of Adaptive Trials and Surrogate Endpoints for Clinical Decision-Making in Rare Cancers. Front. Oncol. 11:636561. doi: 10.3389/fonc.2021.636561
- Doxzen KW, Signé L and Bowman DM. (2022, Jan 4). Advancing precision medicine through agile governance. https://www.brookings.edu/research/advancing-precision-medicine-through-agile-governance/
- Antoniou, M., Kolamunnage-Dona, R., Wason, J., Bathia, R., Billingham, C., Bliss, J. M., Brown, L. C., Gillman, A., Paul, J., & Jorgensen, A. L. (2019). Biomarker-guided trials: Challenges in practice. Contemporary clinical trials communications, 16, 100493. https://doi.org/10.1016/j.conctc.2019.100493
- Lu, C. C., Li, X. N., Broglio, K., Bycott, P., Jiang, Q., Li, X., McGlothlin, A., Tian, H., & Ye, J. (2021). Practical Considerations and Recommendations for Master Protocol Framework: Basket, Umbrella and Platform Trials. Therapeutic innovation & regulatory science, 55(6), 1145–1154. https://doi.org/10.1007/s43441-021-00315-7
- Janiaud, P., Serghiou, S., & Ioannidis, J. (2019). New clinical trial designs in the era of precision medicine: An overview of definitions, strengths, weaknesses, and current use in oncology. Cancer treatment reviews, 73, 20–30. https://doi.org/10.1016/j.ctrv.2018.12.003.
- Shokoohi, A., Al-Hashami, Z., Moore, S., Pender, A., Wong, S. K., Wang, Y., Leung, B., Wu, J., & Ho, C. (2022). Effect of targeted therapy and immunotherapy on advanced nonsmall-cell lung cancer outcomes in the real world. Cancer medicine, 11(1), 86–93. https://doi.org/10.1002/cam4.4427
- The White House. (2022, February 2). Fact Sheet: President Biden Reignites Cancer Moonshot to End Cancer as We Know It. https://www.whitehouse.gov/briefing-room/statements-releases/2022/02/02/fact-sheet-president-biden-reignites-cancer-moonshot-to-end-cancer-as-we-know-it
- Annapragada, A., Sikora, A., Bollard, C., Conejo-Garcia, J., Cruz, C. R., Demehri, S., Demetriou, M., Demirdjian, L., Fong, L., Horowitz, M., Hutson, A., Kadash-Edmondson, K., Kufe, D., Lipkin, S., Liu, S., McCarthy, C., Morgan, M., Morris, Z., Pan, Y., Pasquini, M., … Odunsi, A. (2020). Cancer Moonshot Immuno-Oncology Translational Network (IOTN): accelerating the clinical translation of basic discoveries for improving immunotherapy and immunoprevention of cancer. Journal for immunotherapy of cancer, 8(1), e000796. https://doi.org/10.1136/jitc-2020-000796
- Akturk, G., Parra, E. R., Gjini, E., Lako, A., Lee, J. J., Neuberg, D., Zhang, J., Yao, S., Laface, I., Rogic, A., Chen, P. H., Sanchez-Espiridion, B., Valle, D., Moravec, R., Kinders, R., Hudgens, C., Wu, C., Wistuba, I. I., Thurin, M., Hewitt, S. M., … Tetzlaff, M. T. (2021). Multiplex Tissue Imaging Harmonization: A Multicenter Experience from CIMAC-CIDC Immuno-Oncology Biomarkers Network. Clinical cancer research: an official journal of the American Association for Cancer Research, 27(18), 5072–5083. https://doi.org/10.1158/1078-0432.CCR-21-2051