2023 in Evaluation
Health Research Study + Technology: A Transition
Palantir Factory has long been instrumental in accelerating the study searchings for of our wellness and life scientific research companions, assisting accomplish unprecedented understandings, streamline data accessibility, boost data usability, and help with sophisticated visualization and evaluation of information sources– all while safeguarding the privacy and security of the support information
In 2023, Factory supported over 50 peer-reviewed publications in prestigious journals, covering a diverse number of topics– from hospital procedures, to oncological medicines, to discovering techniques. The year prior, our software program sustained a document number of peer-reviewed magazines, which we highlighted in a previous article
Our companions’ foundational investments in technical facilities throughout the top of the COVID- 19 pandemic has actually made the excellent quantity of magazines possible.
Public and industrial healthcare companions have actually proactively scaled their investments in information sharing and study software application past COVID response to develop a more comprehensive data foundation for biomedical research. As an example, the N 3 C Enclave — which houses the data of 21 5 M clients from throughout virtually 100 institutions– is being utilized everyday by thousands of researchers across firms and organizations. Offered the complexity of accessing, arranging, and utilizing ever-expanding biomedical information, the demand for similar study resources remains to rise.
In this article, we take a closer take a look at some notable publications from 2023 and examine what exists ahead for software-backed research.
Emerging Modern Technology and the Acceleration of Scientific Research Study
The influence of brand-new modern technologies on the clinical venture is increasing research-based results at a previously difficult scale. Emerging innovations and advanced software are helping create extra precise, organized, and obtainable data properties, which in turn are allowing scientists to tackle significantly intricate scientific challenges. Specifically, as a modular, interoperable, and adaptable platform, Factory has actually been made use of to support a diverse series of scientific studies with special study functions, including AI-assisted therapeutics recognition, real-world evidence generation, and much more.
In 2023, the industry has actually likewise seen an exponential development in passion around utilizing Expert system (AI)– and in particular, generative AI and big language models (LLM)– in the wellness and life scientific research domains. Together with various other core technical advancements (e.g., around data high quality and functionality), the possibility for AI-enabled software program to increase clinical research study is more encouraging than ever before. As an industrial leader in AI-enabled software program, Palantir has been at the leading edge of finding responsible, safe and secure, and effective ways to apply AI-enabled capacities to sustain our companions throughout industries in accomplishing their most important missions.
Over the previous year, Palantir software assisted drive crucial elements of our partners’ research study and we stand all set to proceed working together with our companions in government, industry, and civil culture to take on the most pressing challenges in wellness and scientific research in advance. In the next area, we offer concrete examples of just how the power of software can assist development clinical research study, highlighting some key biomedical publications powered by Foundry in 2023
2023 Publications Powered by Palantir Foundry
Along with a number of important cancer cells and COVID treatment researches, Palantir Foundry likewise allowed new searchings for in the wider area of study approach. Below, we highlight a sample of a few of the most impactful peer-reviewed posts released in 2023 that used Palantir Shop to assist drive their research study.
Identifying brand-new reliable medication mixes for numerous myeloma
- Publication : Cancer 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.
- Summary : Numerous myeloma (MM) is frequently immune to medicine therapy, needing ongoing exploration to determine new, effective therapeutic combinations. In this research, researchers utilized high-throughput medicine screening to recognize over 1900 compounds with task versus a minimum of 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 across the 47 cell lines and different devices of activity were picked for more evaluation. Particularly, six (6 medication combinations were effective at 1 reducing over-expression of a crucial healthy protein (MYC) that is usually connected to the manufacturing of malignant cells and 2 boosted expression of the p 16 protein, which can help the body subdue tumor development. Furthermore, three (3 recognized medication mixes increased possibilities of survival and decreased the growth of cancer cells, partially by decreasing activity of pathways associated with TGFβ/ SMAD signaling, which regulate the cell life cycle. These preclinical findings identify possibly beneficial unique medication mixes for challenging to deal with multiple myeloma.
New rank-based protein category technique to improve glioblastoma therapy
- Magazine : Cancers cells
- Authors : Tasci, E., Jagasia, S., Zhuge, Y., Sproull, M., Cooley Zgela, T., Mackey, M., Camphausen, K., Krauze, A.V.
- Recap : Glioblastomas, the most common type of cancerous brain lumps, differ substantially, restricting the capacity to evaluate the organic aspects that drive whether glioblastomas will respond to treatment. Nonetheless, information evaluation of the proteome– the entire collection of healthy proteins that can be shared by the growth– can 1 deal non-invasive techniques of identifying glioblastomas to help notify therapy and 2 identify healthy protein biomarkers related to treatments to assess action to treatment. In this research, scientists established and examined a novel rank-based weighting approach (“RadWise”) for protein includes to assist ML formulas concentrate on the the most appropriate factors that suggest post-therapy end results. RadWise uses a more reliable pathway to identify the proteins and functions that can be essential targets for treatment of these aggressive, deadly tumors.
Determining liver cancer cells subtypes most likely to respond 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., Warner, A.C., Edmondson, E.F., Forgues, M., Greten, T.F., Wang, X.W.
- Recap : Liver cancer cells is a climbing cause of cancer cells fatalities in the United States. This research checked out variation in individual end results for a type of immunotherapy making use of immune checkpoint preventions. Scientist noted that particular molecular subtypes of cancer cells, specified by 1 the aggressiveness of cancer and 2 the microenvironment of the cancer cells, were connected to greater survival rates with immune checkpoint inhibitor therapy. Identifying these molecular subtypes can assist physicians identify whether a patient’s unique cancer is likely to react to this type of treatment, indicating they can use extra targeted use of immunotherapy and enhance likelihood of success.
Applying algorithms to EHR information to infer maternity timing for more accurate mother’s wellness study
- Publication : JAMIA, Female’s Health and 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 create pregnancy problems, and expecting individuals seem at higher threat for more serious COVID- 19 infection. Analysis of wellness document (EHR) data can help provide even more insight, yet because of data disparities, it is usually hard to determine 1 maternity start and end dates and 2 gestational age of the baby at birth. To help, researchers adjusted an existing formula for establishing gestational age and pregnancy size that counts on analysis codes and distribution days. To increase the accuracy of this formula, the scientists layered by themselves data-driven algorithms to exactly infer pregnancy start, maternity end, and landmark period throughout a pregnancy’s progression while additionally addressing EHR data inconsistency. This technique can be accurately made use of to make the fundamental inference of maternity timing and can be put on future maternity and maternity research study on subjects such as negative pregnancy end results and mother’s mortality.
An unique approach for fixing EHR information quality concerns for clinical experiences
- 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.
- Recap : Professional experience data can be an abundant source for research study, but it often differs substantially across providers, facilities, and organizations, making it challenging to evenly evaluate. This incongruity is multiplied when multisite electronic health record (EHR) information is networked with each other in a main database. In this research, researchers established an unique, generalizable technique for settling medical experience information for evaluation by integrating associated experiences right into composite “macrovisits.” This method helps adjust and settle EHR encounter information concerns in a generalizable, repeatable means, permitting researchers to a lot more quickly open the possibility of this abundant data for large-scale studies.
Improving transparency in phenotyping for Long COVID research study and beyond
- Magazine : Journal of the American Medical Informatics Association
- 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 RECOVER Consortia
- Recap : Phenotyping, the procedure of assessing and classifying a microorganism’s qualities, can aid scientists much better recognize the distinctions between people and teams of individuals, and to recognize particular characteristics that might be linked to certain conditions or problems. Machine learning (ML) can help acquire phenotypes from data, however these are testing to share and replicate due to their complexity. Scientists in this study created and educated an ML-based phenotype to determine people highly potential to have Lengthy COVID, a significantly immediate public wellness factor to consider, and showed applicability of this technique for various other settings. This is a success tale of exactly how clear innovation and partnership can make phenotyping formulas a lot more available to a broad target market of scientists in informatics, decreasing duplicated job and offering them with a tool to reach insights much faster, consisting of for various other conditions.
Browsing obstacles for multisite real world data (RWD) data sources
- Publication : BMC Medical Research 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 : Collaborating with big range streamlined EHR data sources such as N 3 C for research study calls for specialized understanding and careful analysis of information high quality and efficiency. This study analyzes the process of evaluating data quality in preparation for research, concentrating on medication efficacy research studies. Scientist recognized numerous techniques and finest methods to much better identify important study components including direct exposure to therapy, standard health comorbidities, and crucial outcomes of rate of interest. As huge scale, centralized real world data sources become more prevalent, this is a practical step forward in assisting researchers better navigate their one-of-a-kind data obstacles while unlocking important applications for drug development.
What’s Next for Health Research at Palantir
While 2023 saw crucial progress, the new year brings with it brand-new possibilities, as well as an urgency to use the current technical advancements to the most important health problems encountering people, neighborhoods, and the general public at big. As an example, in 2023, the united state Government reaffirmed its commitment to combating systemic diseases such as cancer cells, and even launched a new health and wellness company, the Advanced Research Study Projects Firm for Health And Wellness ( ARPA-H
Additionally, in 2024, Palantir is honored to be a sector companion in the cutting-edge National AI Research Study Resource (NAIRR) pilot program , developed under the auspices of the National Science Structure (NSF) and with financing from the NIH. As component of the NAIRR pilot– whose launch was guided by the Biden Management’s Executive Order on Expert System — Palantir will certainly be working with its veteran partners at the National Institutes of Wellness (NIH) and N 3 C to sustain research in advancing secure, safe, and credible AI, in addition to the application of AI to challenges in health care.
In 2024, we’re excited to work with companions, new and old, on problems of essential value, using our knowings on information, tools, and research study to aid make it possible for meaningful enhancements in health and wellness end results for all.
To find out more concerning our proceeding job throughout wellness and life scientific researches, visit https://www.palantir.com/offerings/federal-health/
* Authors connected with Palantir Technologies