2023 in Testimonial
Wellness Research + Modern Technology: A Transition
Palantir Foundry has actually long been instrumental in increasing the research study searchings for of our health and life science companions, assisting attain extraordinary insights, streamline information access, improve data usability, and facilitate sophisticated visualization and evaluation of information sources– all while protecting the personal privacy and safety of the backing information
In 2023, Foundry supported over 50 peer-reviewed publications in renowned journals, covering a varied variety of subjects– from health center operations, to oncological drugs, to finding out techniques. The year prior, our software program supported a document variety of peer-reviewed magazines, which we highlighted in a previous blog post
Our companions’ foundational financial investments in technological facilities during the optimal of the COVID- 19 pandemic has made the impressive quantity of magazines possible.
Public and industrial health care companions have proactively scaled their financial investments in information sharing and research study software application past COVID response to build a much more comprehensive information structure for biomedical research study. For example, the N 3 C Enclave — which houses the information of 21 5 M clients from throughout virtually 100 establishments– is being made use of daily by countless researchers across agencies and companies. Provided the intricacy of accessing, organizing, and using ever-expanding biomedical information, the need for comparable study sources continues to increase.
In this blog post, we take a closer take a look at some notable publications from 2023 and examine what exists in advance for software-backed research.
Arising Technology and the Velocity of Scientific Research
The impact of brand-new technologies on the scientific enterprise is increasing research-based outputs at a previously difficult range. Emerging innovations and progressed software are aiding produce a lot more accurate, arranged, and accessible information possessions, which consequently are enabling scientists to take on progressively complex clinical obstacles. Particularly, as a modular, interoperable, and versatile system, Factory has actually been utilized to sustain a varied series of scientific researches with one-of-a-kind research study features, consisting of AI-assisted therapeutics recognition, real-world proof generation, and more.
In 2023, the sector has also seen an exponential development in interest around using Expert system (AI)– and particularly, generative AI and huge language models (LLM)– in the health and life science domain names. Along with various other core technical innovations (e.g., around data top quality and functionality), the potential for AI-enabled software to accelerate scientific research is a lot more promising than ever. As a business leader in AI-enabled software, Palantir has actually gone to the leading edge of finding liable, safe, and efficient methods to use AI-enabled abilities to sustain our companions across sectors in attaining their essential objectives.
Over the previous year, Palantir software program helped drive key components of our partners’ study and we stand all set to proceed working together with our companions in federal government, industry, and civil society to deal with one of the most pressing difficulties in health and wellness and scientific research in advance. In the next section, we give concrete instances of exactly how the power of software program can aid breakthrough clinical research study, highlighting some crucial biomedical publications powered by Factory in 2023
2023 Publications Powered by Palantir Foundry
Along with a number of crucial cancer cells and COVID treatment researches, Palantir Foundry additionally allowed new searchings for in the more comprehensive area of study approach. Listed below, we highlight a sample of a few of the most impactful peer-reviewed posts released in 2023 that used Palantir Foundry to help drive their study.
Identifying brand-new efficient medication combinations for numerous myeloma
- Publication : Cancer cells 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 : Numerous myeloma (MM) is regularly resistant to medicine treatment, requiring ongoing exploration to identify brand-new, reliable therapeutic mixes. In this research study, scientists used high-throughput medication screening to recognize over 1900 compounds with activity versus at least 25 of the 47 MM cell lines evaluated. From these 1900 compounds, 3 61 million combinations were evaluated in silico, and pairs of substances with highly correlated task throughout the 47 cell lines and different mechanisms of action were picked for further analysis. Particularly, six (6 medicine mixes worked at 1 reducing over-expression of a key protein (MYC) that is usually connected to the manufacturing of malignant cells and 2 increased expression of the p 16 protein, which can help the body suppress tumor development. Moreover, 3 (3 recognized drug combinations boosted chances of survival and decreased the development of cancer cells, partly by minimizing task of pathways associated with TGFβ/ SMAD signaling, which regulate the cell life cycle. These preclinical findings determine potentially useful unique medicine combinations for challenging to deal with several myeloma.
New rank-based healthy protein category method to improve glioblastoma therapy
- 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 typical kind of cancerous brain lumps, vary substantially, limiting the ability to examine the organic elements that drive whether glioblastomas will certainly react to therapy. However, information analysis of the proteome– the whole collection of proteins that can be expressed by the tumor– can 1 deal non-invasive methods of classifying glioblastomas to aid inform therapy and 2 recognize protein biomarkers connected with interventions to assess feedback to treatment. In this research study, scientists created and evaluated a novel rank-based weighting method (“RadWise”) for protein features to assist ML formulas concentrate on the one of the most appropriate factors that show post-therapy end results. RadWise uses a much more reliable path to recognize the healthy proteins and features that can be key targets for therapy of these aggressive, deadly lumps.
Identifying liver cancer cells subtypes most likely to respond to immunotherapy
- Publication : Cell Reports Medicine
- 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 a rising reason for cancer cells fatalities in the US. This research explored variant in client outcomes for a kind of immunotherapy using immune checkpoint inhibitors. Scientist noted that certain molecular subtypes of cancer, defined by 1 the aggression of cancer cells and 2 the microenvironment of the cancer cells, were linked to higher survival rates with immune checkpoint inhibitor therapy. Recognizing these molecular subtypes can help physicians recognize whether a person’s special cancer is likely to react to this type of treatment, suggesting they can use extra targeted use of immunotherapy and improve possibility of success.
Applying algorithms to EHR information to infer pregnancy timing for even more accurate mother’s health and wellness study
- Magazine : JAMIA, Women’s Health and wellness Special Edition
- Authors : 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 signs that COVID- 19 can create maternity issues, and expectant individuals appear to be at greater risk for extra extreme COVID- 19 infection. Analysis of health record (EHR) information can aid provide more insight, yet due to data variances, it is frequently difficult to identify 1 pregnancy beginning and end days and 2 gestational age of the child at birth. To assist, scientists adjusted an existing algorithm for determining gestational age and pregnancy length that relies upon diagnostic codes and delivery days. To enhance the accuracy of this formula, the scientists layered on their own data-driven algorithms to specifically infer pregnancy beginning, maternity end, and spots timespan throughout a maternity’s development while also addressing EHR information variance. This method can be dependably used to make the fundamental inference of maternity timing and can be put on future maternity and maternity study on topics such as adverse maternity end results and maternal mortality.
An unique approach for settling EHR information high quality concerns for medical encounters
- Magazine : 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 : Scientific experience data can be an abundant resource for research study, but it frequently varies substantially throughout carriers, facilities, and institutions, making it challenging to consistently assess. This inconsistency is amplified when multisite digital health record (EHR) information is networked with each other in a central data source. In this research, researchers developed a novel, generalizable method for resolving scientific encounter information for evaluation by integrating related experiences into composite “macrovisits.” This method aids adjust and deal with EHR encounter information concerns in a generalizable, repeatable way, allowing scientists to a lot more conveniently open the capacity of this rich information for large research 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 RECOVER Consortia
- Summary : Phenotyping, the process of evaluating and classifying an organism’s features, can help researchers better understand the differences in between individuals and groups of individuals, and to recognize specific attributes that may be connected to particular conditions or conditions. Artificial intelligence (ML) can help acquire phenotypes from information, but these are challenging to share and reproduce as a result of their intricacy. Scientists in this study created and educated an ML-based phenotype to determine individuals highly likely to have Long COVID, a significantly immediate public wellness factor to consider, and showed applicability of this method for various other atmospheres. This is a success tale of exactly how transparent modern technology and cooperation can make phenotyping formulas a lot more available to a broad audience of researchers in informatics, decreasing duplicated job and providing them with a device to get to understandings much faster, including for various other diseases.
Navigating difficulties for multisite real world information (RWD) data sources
- Publication : BMC Medical Study Methodology
- 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
- Summary : Working with big scale streamlined EHR data sources such as N 3 C for research needs specialized knowledge and careful examination of data quality and efficiency. This research checks out the process of examining information top quality to prepare for research, focusing on medication effectiveness researches. Researchers determined several approaches and finest practices to much better characterize crucial study elements including exposure to treatment, baseline health and wellness comorbidities, and essential outcomes of interest. As big scale, streamlined real life data sources become much more widespread, this is a practical step forward in aiding researchers better browse their special data difficulties while opening essential applications for medication advancement.
What’s Following for Wellness Study at Palantir
While 2023 saw crucial progression, the new year brings with it brand-new possibilities, in addition to a necessity to apply the most recent technological advancements to one of the most crucial health and wellness issues encountering people, areas, and the public at large. For instance, in 2023, the U.S. Government reaffirmed its dedication to combating systemic conditions such as cancer cells, and even introduced a new health and wellness agency, the Advanced Research Study Projects Agency for Health And Wellness ( ARPA-H
Moreover, in 2024, Palantir is honored to be an industry partner in the ingenious National AI Study Resource (NAIRR) pilot program , developed under the auspices of the National Scientific Research Foundation (NSF) and with financing from the NIH. As component of the NAIRR pilot– whose launch was routed by the Biden Management’s Exec Order on Expert System — Palantir will be collaborating with its long-time companions at the National Institutes of Wellness (NIH) and N 3 C to sustain research beforehand risk-free, safe and secure, and credible AI, along with the application of AI to challenges in healthcare.
In 2024, we’re excited to collaborate with companions, brand-new and old, on problems of essential importance, applying our discoverings on data, devices, and research to help allow purposeful enhancements in health end results for all.
To get more information regarding our continuing job across health and life sciences, visit https://www.palantir.com/offerings/federal-health/
* Authors affiliated with Palantir Technologies