2023 in Evaluation
Wellness Research Study + Modern Technology: A Turning Point
Palantir Factory has actually long contributed in speeding up the research findings of our health and life scientific research partners, helping achieve extraordinary insights, enhance data access, enhance information usability, and assist in advanced visualization and evaluation of data sources– all while shielding the privacy and protection of the support information
In 2023, Factory supported over 50 peer-reviewed magazines in esteemed journals, covering a varied variety of subjects– from hospital operations, to oncological medicines, to learning modalities. The year prior, our software program sustained a document number of peer-reviewed publications, which we highlighted in a previous blog post
Our partners’ foundational financial investments in technological infrastructure throughout the peak of the COVID- 19 pandemic has actually made the outstanding amount of magazines feasible.
Public and business health care companions have proactively scaled their financial investments in information sharing and research software application beyond COVID response to construct a more thorough data foundation for biomedical research. As an example, the N 3 C Enclave — which houses the information of 21 5 M people from across almost 100 establishments– is being used daily by thousands of researchers across agencies and organizations. Provided the intricacy of accessing, organizing, and taking advantage of ever-expanding biomedical data, the demand for similar study sources remains to increase.
In this post, we take a closer look at some significant publications from 2023 and analyze what exists ahead for software-backed research study.
Arising Modern Technology and the Velocity of Scientific Research
The impact of new technologies on the scientific venture is accelerating research-based outputs at a formerly impossible range. Emerging modern technologies and progressed software application are aiding develop a lot more precise, arranged, and available information properties, which subsequently are permitting researchers to tackle increasingly complicated scientific difficulties. Particularly, as a modular, interoperable, and flexible platform, Shop has been used to support a varied variety of scientific researches with special study features, including AI-assisted therapies recognition, real-world evidence generation, and a lot more.
In 2023, the industry has likewise seen an exponential growth in interest around making use of Expert system (AI)– and in particular, generative AI and huge language designs (LLM)– in the health and wellness and life scientific research domains. Along with various other core technical advancements (e.g., around data quality and usability), the potential for AI-enabled software to speed up clinical research study is a lot more appealing than ever before. As an industrial leader in AI-enabled software application, Palantir has actually gone to the center of finding liable, safe, and reliable methods to use AI-enabled capabilities to sustain our partners throughout industries in attaining their crucial goals.
Over the past year, Palantir software program aided drive essential components of our partners’ research and we stand prepared to continue working together with our partners in government, sector, and civil society to take on one of the most important difficulties in wellness and science ahead. In the following area, we give concrete examples of exactly how the power of software program can aid advance clinical research study, highlighting some essential biomedical magazines powered by Shop in 2023
2023 Publications Powered by Palantir Shop
In addition to a number of essential cancer and COVID treatment researches, Palantir Factory also enabled brand-new findings in the more comprehensive field of research study method. Listed below, we highlight an example of some of the most impactful peer-reviewed articles published in 2023 that used Palantir Foundry to assist drive their research study.
Identifying brand-new reliable medication combinations for several myeloma
- Publication : Cancer Letters
- Writers : Peat, T.J., Gaikwad, S.M., Dubois, W., Gyabaah-Kessie, N., Zhang, S., Gorjifard, S., Phyo, Z., Andres, M., Hughitt, V.K., Simpson, R.M., Miller, M.A., Girvin, A.T., Taylor, A., Williams, D., D’Antonio, N., Zhang, Y., Rajagopalan, A., Flietner, E., Wilson, K., Zhang, X., Shinn, P., Klumpp-Thomas, C., McKnight, C., Itkin, Z., Chen, L., Kazandijian, D., Zhang, J., Michalowski, A.M., Simmons, J.K., Keats, J., Thomas, C.J., Mock, B.A.
- Recap : Several myeloma (MM) is frequently immune to medication treatment, calling for ongoing expedition to determine brand-new, efficient therapeutic mixes. In this research study, researchers utilized high-throughput medication testing to identify over 1900 substances with activity against at the very least 25 of the 47 MM cell lines checked. From these 1900 substances, 3 61 million mixes were evaluated in silico, and pairs of substances with very associated activity throughout the 47 cell lines and various mechanisms of activity were picked for more analysis. Particularly, 6 (6 medication combinations worked at 1 minimizing over-expression of a key healthy protein (MYC) that is commonly connected to the manufacturing of malignant cells and 2 boosted expression of the p 16 healthy protein, which can aid the body suppress lump development. Additionally, 3 (3 recognized drug mixes boosted chances of survival and lowered the growth of cancer cells, partly by minimizing task of pathways associated with TGFβ/ SMAD signaling, which regulate the cell life process. These preclinical searchings for identify possibly beneficial unique medication mixes for tough to deal with several myeloma.
New rank-based healthy protein category method to improve glioblastoma treatment
- Publication : Cancers cells
- Writers : Tasci, E., Jagasia, S., Zhuge, Y., Sproull, M., Cooley Zgela, T., Mackey, M., Camphausen, K., Krauze, A.V.
- Recap : Glioblastomas, the most common sort of cancerous brain growths, vary greatly, limiting the capability to assess the organic factors that drive whether glioblastomas will certainly react to therapy. Nonetheless, data evaluation of the proteome– the entire collection of proteins that can be shared by the lump– can 1 deal non-invasive approaches of categorizing glioblastomas to help notify treatment and 2 recognize healthy protein biomarkers associated with interventions to assess reaction to treatment. In this research study, scientists created and checked an unique rank-based weighting technique (“RadWise”) for healthy protein includes to help ML algorithms concentrate on the the most pertinent elements that indicate post-therapy results. RadWise offers an extra reliable pathway to recognize the proteins and features that can be crucial targets for therapy of these hostile, deadly tumors.
Recognizing liver cancer cells subtypes most likely to reply to immunotherapy
- Magazine : Cell Records Medication
- Writers : Budhu, A., Pehrsson, E.C., He, A., Goyal, L., Kelley, R.K., Dang, H., Xie, C., Monge, C., Tandon, M., Ma, L., Revsine, M., Kuhlman, L., Zhang, K., Baiev, I., Lamm, R., Patel, K., Kleiner, D.E., Hewitt, S.M., Tran, B., Shetty, J., Wu, X., Zhao, Y., Shen, T.W., Choudhari, S., Kriga, Y., Ylaya, K., Warner, A.C., Edmondson, E.F., Forgues, M., Greten, T.F., Wang, X.W.
- Recap : Liver cancer cells is a climbing source of cancer deaths in the United States. This study explored variant in individual end results for a kind of immunotherapy making use of immune checkpoint preventions. Researchers noted that specific molecular subtypes of cancer cells, specified by 1 the aggressiveness of cancer and 2 the microenvironment of the cancer cells, were linked to greater survival rates with immune checkpoint inhibitor therapy. Determining these molecular subtypes can assist medical professionals determine whether a person’s unique cancer is likely to react to this kind of intervention, suggesting they can use extra targeted use of immunotherapy and enhance likelihood of success.
Applying algorithms to EHR information to presume maternity timing for more exact mother’s health and wellness study
- Publication : JAMIA, Women’s Wellness Scandal sheet
- Writers : Jones, S., Bradwell, K.R. *, Chan, L.E., McMurry, J.A., Olson-Chen, C., Tarleton, J., Wilkins, K.J., Qin, Q., Faherty, E.G., Lau, Y.K., Xie, C., Kao, Y.H., Liebman, M.N., Ljazouli, S. *, Mariona, F., Challa, A., Li, L., Ratcliffe, S.J., Haendel, M.A., Patel, R.C., Hillside, E.L.
- Recap : There are indicators that COVID- 19 can cause maternity problems, and expecting individuals seem at greater threat for more severe COVID- 19 infection. Analysis of health record (EHR) information can assist provide more insight, however due to data disparities, it is commonly hard to identify 1 maternity begin and end dates and 2 gestational age of the baby at birth. To assist, researchers adapted an existing formula for establishing gestational age and pregnancy size that relies on diagnostic codes and delivery days. To raise the accuracy of this formula, the scientists layered on their own data-driven algorithms to specifically presume maternity begin, pregnancy end, and spots timespan throughout a maternity’s development while additionally attending to EHR information variance. This method can be reliably made use of to make the fundamental inference of maternity timing and can be applied to future maternity and maternity research on topics such as adverse maternity outcomes and mother’s mortality.
A novel approach for settling EHR information top quality concerns for professional experiences
- Publication : JAMIA
- Authors : Leese, P., Anand, A., Girvin, A. *, Manna, A. *, Patel, S., Yoo, Y.J., Wong, R., Haendel, M., Chute, C.G., Bennett, T., Hajagos, J., Pfaff, E., Moffitt, R.
- Summary : Professional experience data can be a rich resource for research, yet it typically varies significantly across suppliers, facilities, and organizations, making it difficult to evenly examine. This incongruity is magnified when multisite electronic health and wellness record (EHR) data is networked with each other in a main data source. In this research study, researchers created an unique, generalizable technique for solving medical experience data for evaluation by integrating relevant experiences into composite “macrovisits.” This approach assists adjust and settle EHR encounter data concerns in a generalizable, repeatable means, enabling researchers to more easily unlock the possibility of this rich data for large-scale studies.
Improving openness in phenotyping for Long COVID research and beyond
- Publication : Journal of the American Medical Informatics Association
- Authors : Pfaff, E.R., Girvin, A.T. *, Crosskey, M., Gangireddy, S., Master, H., Wei, W.Q., Kerchberger, V.E., Weiner, M., Harris, P.A., Basford, M., Lunt, C., Chute, C.G., Moffitt, R.A., Haendel, M.; N 3 C and Recoup Consortia
- Summary : Phenotyping, the procedure of reviewing and classifying a microorganism’s features, can help researchers better recognize the distinctions between individuals and groups of people, and to recognize specific attributes that might be linked to particular conditions or problems. Machine learning (ML) can help obtain phenotypes from information, yet these are testing to share and replicate as a result of their complexity. Researchers in this study created and educated an ML-based phenotype to recognize patients highly probable to have Long COVID, a progressively urgent public health factor to consider, and showed applicability of this approach for various other settings. This is a success story of just how clear modern technology and cooperation can make phenotyping formulas more obtainable to a broad audience of researchers in informatics, decreasing copied work and supplying them with a tool to get to understandings quicker, including for other conditions.
Navigating obstacles for multisite real world information (RWD) databases
- Magazine : BMC Medical Research Study Approach
- Authors : Sidky, H., Young, J.C., Girvin, A.T. *, Lee, E., Shao, Y.R., Hotaling, N., Michael, S., Wilkins, K.J., Setoguchi, S., Funk, M.J.; N 3 C Consortium
- Recap : Working with large scale streamlined EHR data sources such as N 3 C for research calls for specialized understanding and mindful evaluation of information high quality and completeness. This research study examines the process of analyzing data high quality in preparation for research, concentrating on medicine effectiveness researches. Scientist determined numerous methods and best practices to much better identify crucial research study elements consisting of exposure to treatment, baseline health comorbidities, and key results of interest. As large scale, systematized real world databases end up being extra prevalent, this is a valuable step forward in helping scientists better browse their special information obstacles while opening vital applications for medication development.
What’s Following for Health Research Study at Palantir
While 2023 saw essential progress, the new year brings with it new opportunities, along with a seriousness to apply the most up to date technological advancements to one of the most essential health and wellness issues dealing with people, neighborhoods, and the general public at large. As an example, in 2023, the united state Government declared its commitment to combating systemic illness such as cancer cells, and even released a brand-new health agency, the Advanced Study Projects Firm for Health And Wellness ( ARPA-H
In addition, in 2024, Palantir is honored to be an industry partner in the ingenious National AI Research Study Source (NAIRR) pilot program , developed under the auspices of the National Science Structure (NSF) and with funding from the NIH. As part of the NAIRR pilot– whose launch was routed by the Biden Management’s Exec Order on Expert System — Palantir will be dealing with its veteran partners at the National Institutes of Wellness (NIH) and N 3 C to support research study ahead of time safe, protected, and trustworthy AI, as well as the application of AI to challenges in health care.
In 2024, we’re thrilled to work with partners, brand-new and old, on issues of important importance, applying our understandings on data, tools, and study to assist enable significant improvements in health results for all.
To learn more about our proceeding work throughout health and life sciences, check out https://www.palantir.com/offerings/federal-health/
* Authors associated with Palantir Technologies