2023 in Testimonial
Wellness Research Study + Modern Technology: A Pivotal Moment
Palantir Factory has long contributed in accelerating the research study searchings for of our health and wellness and life scientific research partners, assisting achieve extraordinary understandings, enhance information gain access to, enhance information use, and promote advanced visualization and evaluation of information resources– all while shielding the privacy and safety and security of the support information
In 2023, Factory sustained over 50 peer-reviewed publications in prestigious journals, covering a diverse number of topics– from healthcare facility operations, to oncological medications, to learning techniques. The year prior, our software program supported a record variety of peer-reviewed publications, which we highlighted in a previous post
Our companions’ foundational investments in technical infrastructure during the height of the COVID- 19 pandemic has made the outstanding quantity of publications possible.
Public and business healthcare companions have actually proactively scaled their financial investments in data sharing and study software application past COVID action to construct an extra comprehensive information foundation for biomedical study. As an example, the N 3 C Enclave — which houses the information of 21 5 M patients from throughout virtually 100 institutions– is being made use of day-to-day by countless researchers across firms and companies. Offered the complexity of accessing, organizing, and taking advantage of ever-expanding biomedical information, the need for similar research resources continues to rise.
In this article, we take a closer consider some notable magazines from 2023 and examine what exists ahead for software-backed study.
Emerging Modern Technology and the Acceleration of Scientific Research Study
The influence of new innovations on the scientific enterprise is increasing research-based results at a previously impossible range. Emerging innovations and advanced software are aiding create extra exact, organized, and available information assets, which in turn are enabling scientists to tackle significantly intricate scientific difficulties. Particularly, as a modular, interoperable, and flexible system, Foundry has actually been made use of to sustain a varied series of clinical studies with one-of-a-kind research features, consisting of AI-assisted therapeutics identification, real-world evidence generation, and more.
In 2023, the sector has actually additionally seen a rapid development in interest around making use of Artificial Intelligence (AI)– and in particular, generative AI and huge language models (LLM)– in the health and life scientific research domain names. Together with various other core technical improvements (e.g., around data high quality and usability), the capacity for AI-enabled software program to increase scientific research study is more promising than ever. As a commercial leader in AI-enabled software program, Palantir has gone to the forefront of searching for liable, protected, and efficient ways to apply AI-enabled abilities to support our partners across industries in attaining their crucial goals.
Over the previous year, Palantir software application helped drive key parts of our companions’ study and we stand prepared to continue collaborating with our partners in federal government, market, and civil culture to take on one of the most pressing challenges in health and wellness and scientific research ahead. In the following area, we offer concrete examples of just how the power of software program can assist development clinical research, highlighting some vital biomedical publications powered by Foundry in 2023
2023 Publications Powered by Palantir Factory
Along with a number of vital cancer cells and COVID therapy researches, Palantir Factory likewise allowed new findings in the wider field of study methodology. Below, we highlight an example of a few of the most impactful peer-reviewed short articles published in 2023 that used Palantir Factory to aid drive their research study.
Identifying brand-new effective medicine mixes for multiple myeloma
- Publication : 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.
- Summary : Multiple myeloma (MM) is frequently immune to medicine treatment, requiring continued expedition to identify new, effective restorative mixes. In this study, scientists made use of high-throughput drug testing to recognize over 1900 substances with task against a minimum of 25 of the 47 MM cell lines evaluated. From these 1900 compounds, 3 61 million combinations were evaluated in silico, and sets of compounds with very correlated task throughout the 47 cell lines and various systems of activity were selected for more evaluation. Especially, six (6 medication mixes worked at 1 minimizing over-expression of a vital healthy protein (MYC) that is often linked to the manufacturing of deadly cells and 2 boosted expression of the p 16 protein, which can assist the body suppress tumor development. In addition, 3 (3 determined medicine combinations increased possibilities of survival and reduced the growth of cancer cells, partially by minimizing task of pathways associated with TGFβ/ SMAD signaling, which manage the cell life process. These preclinical searchings for identify potentially valuable unique medicine mixes for challenging to deal with numerous myeloma.
New rank-based healthy protein classification approach to improve glioblastoma therapy
- Publication : Cancers
- Writers : Tasci, E., Jagasia, S., Zhuge, Y., Sproull, M., Cooley Zgela, T., Mackey, M., Camphausen, K., Krauze, A.V.
- Summary : Glioblastomas, the most usual kind of malignant brain lumps, differ considerably, limiting the capacity to evaluate the biological aspects that drive whether glioblastomas will reply to treatment. Nonetheless, data evaluation of the proteome– the entire collection of proteins that can be expressed by the growth– can 1 offer non-invasive methods of classifying glioblastomas to aid inform treatment and 2 determine protein biomarkers related to treatments to examine feedback to therapy. In this research study, scientists developed and evaluated an unique rank-based weighting approach (“RadWise”) for healthy protein includes to help ML formulas concentrate on the the most appropriate elements that show post-therapy results. RadWise uses an extra efficient pathway to determine the healthy proteins and features that can be key targets for treatment of these hostile, deadly lumps.
Determining liver cancer subtypes most likely to react 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 an increasing root cause of cancer cells fatalities in the US. This study checked out variant in client results for a kind of immunotherapy making use of immune checkpoint preventions. Scientist kept in mind that certain molecular subtypes of cancer cells, defined by 1 the aggressiveness of cancer and 2 the microenvironment of the cancer cells, were connected to greater survival prices with immune checkpoint prevention treatment. Recognizing these molecular subtypes can assist medical professionals recognize whether a patient’s special cancer cells is likely to respond to this sort of treatment, suggesting they can use much more targeted use of immunotherapy and boost probability of success.
Applying algorithms to EHR information to infer pregnancy timing for even more precise mother’s health research
- Publication : JAMIA, Women’s 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., Hill, E.L.
- Recap : There are indicators that COVID- 19 can cause pregnancy difficulties, and pregnant persons seem at greater threat for much more serious COVID- 19 infection. Analysis of health and wellness document (EHR) information can assist provide even more understanding, but due to data incongruities, it is commonly tough to ascertain 1 maternity begin and end days and 2 gestational age of the infant at birth. To assist, scientists adjusted an existing formula for figuring out gestational age and pregnancy size that depends on diagnostic codes and delivery days. To increase the accuracy of this algorithm, the scientists layered on their own data-driven algorithms to specifically infer maternity beginning, maternity end, and spots amount of time throughout a maternity’s development while additionally addressing EHR data incongruity. This technique can be reliably used to make the foundational inference of maternity timing and can be applied to future pregnancy and maternity study on subjects such as negative pregnancy results and mother’s death.
A novel technique for dealing with EHR data top quality problems for scientific encounters
- 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.
- Recap : Professional experience data can be a rich source for research, however it commonly varies significantly throughout suppliers, facilities, and organizations, making it hard to evenly evaluate. This inconsistency is magnified when multisite electronic health and wellness document (EHR) information is networked with each other in a central database. In this study, researchers created an unique, generalizable approach for resolving scientific experience data for evaluation by combining related experiences right into composite “macrovisits.” This approach aids adjust and fix EHR experience information concerns in a generalizable, repeatable means, enabling scientists to more easily open the possibility of this abundant information for large studies.
Improving transparency in phenotyping for Long COVID research study and beyond
- Magazine : 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 Recuperate Consortia
- Recap : Phenotyping, the process of evaluating and categorizing a microorganism’s attributes, can aid researchers much better comprehend the distinctions in between people and teams of individuals, and to identify particular qualities that may be connected to particular conditions or problems. Artificial intelligence (ML) can help acquire phenotypes from data, however these are challenging to share and reproduce due to their intricacy. Scientists in this research study devised and trained an ML-based phenotype to recognize patients very potential to have Lengthy COVID, a significantly urgent public wellness factor to consider, and revealed applicability of this technique for other atmospheres. This is a success story of just how transparent technology and cooperation can make phenotyping formulas a lot more accessible to a broad audience of scientists in informatics, lowering copied work and offering them with a tool to reach insights quicker, including for various other diseases.
Navigating challenges for multisite real world data (RWD) databases
- 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 : Collaborating with huge range centralized EHR data sources such as N 3 C for research requires specialized understanding and mindful analysis of information quality and completeness. This research study takes a look at the process of examining data high quality to prepare for research study, concentrating on medication effectiveness researches. Researchers recognized several approaches and ideal methods to better identify important research study components consisting of exposure to therapy, standard wellness comorbidities, and essential end results of rate of interest. As large range, streamlined real life databases end up being a lot more widespread, this is a useful advance in helping researchers better browse their unique information difficulties while opening crucial applications for medication advancement.
What’s Next for Health And Wellness Research at Palantir
While 2023 saw important development, the new year brings with it new opportunities, in addition to a seriousness to apply the current technical innovations to one of the most vital health and wellness concerns facing people, communities, and the public at large. For example, in 2023, the united state Federal government reaffirmed its dedication to combating systemic illness such as cancer cells, and even launched a new health and wellness company, the Advanced Research Projects Company for Wellness ( ARPA-H
Moreover, in 2024, Palantir is honored to be a market companion in the cutting-edge National AI Research Source (NAIRR) pilot program , developed under the auspices of the National Science Foundation (NSF) and with funding from the NIH. As component of the NAIRR pilot– whose launch was routed by the Biden Management’s Exec Order on Artificial Intelligence — Palantir will certainly be dealing with its veteran companions at the National Institutes of Wellness (NIH) and N 3 C to support research study ahead of time safe, protected, and reliable AI, along with the application of AI to challenges in medical care.
In 2024, we’re delighted to work with partners, brand-new and old, on problems of critical value, using our discoverings on data, tools, and research to aid allow purposeful enhancements in health and wellness results for all.
To get more information regarding our proceeding work across wellness and life scientific researches, browse through https://www.palantir.com/offerings/federal-health/
* Authors associated with Palantir Technologies