2023 in Review
Health And Wellness Research + Innovation: A Juncture
Palantir Factory has actually long been instrumental in increasing the research study findings of our health and life scientific research partners, aiding accomplish extraordinary insights, simplify information gain access to, boost information functionality, and assist in sophisticated visualization and evaluation of information resources– all while securing the privacy and safety and security of the backing data
In 2023, Foundry supported over 50 peer-reviewed magazines in esteemed journals, covering a varied number of topics– from health center procedures, to oncological medicines, to finding out techniques. The year prior, our software program supported a record variety of peer-reviewed publications, which we highlighted in a previous post
Our partners’ foundational financial investments in technological infrastructure throughout the height of the COVID- 19 pandemic has made the remarkable quantity of publications possible.
Public and commercial health care partners have actually proactively scaled their financial investments in data sharing and research study software application past COVID feedback to develop an extra comprehensive data structure for biomedical study. For example, the N 3 C Enclave — which houses the data of 21 5 M patients from throughout virtually 100 organizations– is being made use of everyday by countless scientists throughout firms and organizations. Provided the intricacy of accessing, arranging, and taking advantage of ever-expanding biomedical data, the need for comparable research study resources continues to increase.
In this article, we take a closer take a look at some notable magazines from 2023 and analyze what exists ahead for software-backed research study.
Arising Technology and the Velocity of Scientific Research Study
The impact of new modern technologies on the clinical venture is speeding up research-based outputs at a formerly impossible range. Emerging technologies and progressed software application are helping create much more precise, arranged, and easily accessible data assets, which subsequently are allowing scientists to take on progressively intricate scientific obstacles. In particular, as a modular, interoperable, and versatile platform, Factory has been used to sustain a diverse range of clinical research studies with one-of-a-kind research study features, including AI-assisted therapies recognition, real-world evidence generation, and much more.
In 2023, the industry has likewise seen a rapid development in rate of interest around using Artificial Intelligence (AI)– and specifically, generative AI and big language models (LLM)– in the health and life scientific research domains. Along with various other core technological developments (e.g., around information top quality and functionality), the possibility for AI-enabled software to increase clinical study is extra encouraging than ever. As a commercial leader in AI-enabled software program, Palantir has been at the leading edge of finding accountable, safe and secure, and reliable means to use AI-enabled capabilities to support our partners across markets in attaining their essential missions.
Over the previous year, Palantir software helped drive vital components of our partners’ research and we stand all set to proceed interacting with our partners in federal government, market, and civil society to tackle the most pressing obstacles in health and wellness and science in advance. In the following section, we give concrete instances of how the power of software can help development scientific research study, highlighting some essential biomedical magazines powered by Shop in 2023
2023 Publications Powered by Palantir Foundry
In addition to a variety of crucial cancer and COVID treatment studies, Palantir Shop additionally enabled new searchings for in the broader field of research technique. Below, we highlight a sample of several of the most impactful peer-reviewed articles published in 2023 that utilized Palantir Factory to help drive their research study.
Recognizing brand-new effective drug combinations for numerous myeloma
- Magazine : Cancer cells Letters
- Authors : 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 : Multiple myeloma (MM) is frequently resistant to medicine therapy, requiring ongoing expedition to determine brand-new, reliable healing mixes. In this research, researchers made use of high-throughput drug screening to identify over 1900 compounds with activity versus a minimum of 25 of the 47 MM cell lines tested. From these 1900 compounds, 3 61 million mixes were examined in silico, and sets of substances with very associated activity throughout the 47 cell lines and various systems of activity were chosen for further evaluation. Specifically, 6 (6 drug combinations worked at 1 decreasing over-expression of a vital healthy protein (MYC) that is typically linked to the manufacturing of deadly cells and 2 increased expression of the p 16 protein, which can help the body subdue lump development. Furthermore, 3 (3 recognized medicine mixes raised opportunities of survival and lowered the development of cancer cells, partly by reducing task of paths associated with TGFβ/ SMAD signaling, which regulate the cell life cycle. These preclinical searchings for recognize potentially useful novel drug combinations for challenging to treat several myeloma.
New rank-based healthy protein classification method to boost glioblastoma therapy
- Magazine : Cancers
- Authors : Tasci, E., Jagasia, S., Zhuge, Y., Sproull, M., Cooley Zgela, T., Mackey, M., Camphausen, K., Krauze, A.V.
- Recap : Glioblastomas, one of the most usual sort of cancerous brain growths, vary greatly, restricting the capacity to assess the biological factors that drive whether glioblastomas will react to therapy. Nonetheless, information evaluation of the proteome– the whole set of healthy proteins that can be expressed by the tumor– can 1 offer non-invasive techniques of identifying glioblastomas to assist inform therapy and 2 recognize protein biomarkers connected with interventions to review action to treatment. In this research, researchers established and checked an unique rank-based weighting technique (“RadWise”) for protein features to help ML algorithms concentrate on the one of the most appropriate factors that show post-therapy outcomes. RadWise uses an extra effective path to recognize the healthy proteins and features that can be crucial targets for therapy of these aggressive, fatal growths.
Identifying liver cancer cells subtypes likely to reply to immunotherapy
- Publication : 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., Detector, A.C., Edmondson, E.F., Forgues, M., Greten, T.F., Wang, X.W.
- Summary : Liver cancer is an increasing cause of cancer cells fatalities in the United States. This research explored variation in person outcomes for a type of immunotherapy utilizing immune checkpoint preventions. Researchers kept in mind that certain molecular subtypes of cancer, defined by 1 the aggressiveness of cancer cells and 2 the microenvironment of the cancer cells, were connected to higher survival rates with immune checkpoint inhibitor therapy. Determining these molecular subtypes can assist medical professionals recognize whether a person’s one-of-a-kind cancer is most likely to react to this type of treatment, indicating they can apply more targeted use of immunotherapy and improve possibility of success.
Applying algorithms to EHR data to infer maternity timing for more exact mother’s wellness research study
- Magazine : JAMIA, Female’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., Hill, E.L.
- Summary : There are signs that COVID- 19 can trigger maternity complications, and expecting persons appear to be at higher risk for more severe COVID- 19 infection. Evaluation of wellness record (EHR) data can help give even more insight, but because of information inconsistencies, it is often challenging to determine 1 maternity begin and end dates and 2 gestational age of the child at birth. To aid, researchers adapted an existing formula for determining gestational age and pregnancy size that relies upon analysis codes and shipment days. To boost the accuracy of this formula, the researchers layered by themselves data-driven algorithms to specifically presume pregnancy start, pregnancy end, and site period throughout a maternity’s progression while additionally addressing EHR data inconsistency. This technique can be dependably made use of to make the fundamental reasoning of maternity timing and can be put on future pregnancy and maternity research on topics such as damaging maternity results and maternal mortality.
An unique technique for dealing with EHR data top quality concerns for scientific 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 : Medical encounter information can be an abundant resource for study, but it frequently varies substantially throughout companies, centers, and organizations, making it hard to evenly assess. This inconsistency is multiplied when multisite digital health and wellness record (EHR) data is networked with each other in a main database. In this research, researchers established a novel, generalizable approach for settling clinical encounter information for evaluation by integrating associated experiences right into composite “macrovisits.” This method helps adjust and settle EHR experience information problems in a generalizable, repeatable way, allowing researchers to much more easily unlock the possibility of this abundant information for large-scale studies.
Improving transparency in phenotyping for Long COVID research study and past
- Magazine : Journal of the American Medical Informatics Organization
- Writers : 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
- Recap : Phenotyping, the process of reviewing and categorizing a microorganism’s features, can aid scientists better understand the distinctions between individuals and groups of individuals, and to recognize certain traits that might be connected to specific conditions or problems. Artificial intelligence (ML) can help obtain phenotypes from information, however these are testing to share and duplicate due to their complexity. Scientists in this research study created and trained an ML-based phenotype to identify patients highly likely to have Lengthy COVID, an increasingly immediate public wellness factor to consider, and showed applicability of this technique for various other environments. This is a success story of just how clear technology and collaboration can make phenotyping algorithms much more obtainable to a wide target market of researchers in informatics, decreasing duplicated job and offering them with a tool to reach insights faster, including for various other conditions.
Navigating difficulties for multisite real life data (RWD) data sources
- Publication : BMC Medical Study Technique
- Authors : Sidky, H., Youthful, 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
- Summary : Working with large range systematized EHR data sources such as N 3 C for study needs specialized understanding and cautious evaluation of data high quality and efficiency. This research takes a look at the procedure of examining information high quality in preparation for study, focusing on medicine effectiveness studies. Scientist identified numerous techniques and ideal methods to much better identify important study components including exposure to treatment, baseline wellness comorbidities, and key results of rate of interest. As big range, centralized real life databases come to be a lot more common, this is a practical step forward in helping scientists more effectively navigate their distinct information challenges while unlocking essential applications for medication growth.
What’s Next for Health And Wellness Research at Palantir
While 2023 saw crucial progress, the brand-new year brings with it brand-new opportunities, in addition to an urgency to use the latest technical improvements to one of the most important health and wellness issues dealing with individuals, areas, and the general public at large. For instance, in 2023, the U.S. Federal government reaffirmed its dedication to combating systemic illness such as cancer cells, and even released a brand-new health agency, the Advanced Research Projects Firm for Health And Wellness ( ARPA-H
Moreover, in 2024, Palantir is honored to be an industry partner in the cutting-edge National AI Study Source (NAIRR) pilot program , created under the auspices of the National Scientific Research Structure (NSF) and with funding from the NIH. As component of the NAIRR pilot– whose launch was directed by the Biden Administration’s Exec Order on Expert System — Palantir will certainly be dealing with its veteran partners at the National Institutes of Health (NIH) and N 3 C to support research ahead of time secure, secure, and reliable AI, as well as the application of AI to challenges in healthcare.
In 2024, we’re delighted to work with partners, brand-new and old, on issues of important value, applying our understandings on data, tools, and research study to assist enable significant enhancements in wellness results for all.
To read more concerning our proceeding job throughout health and life scientific researches, go to https://www.palantir.com/offerings/federal-health/
* Authors associated with Palantir Technologies