25 papers · ranked by Valyu relevance
Getnet Molla, Molalegne Bitew, Kunhong Xiao, Leanne Labriola
The field of personalized medicine is undergoing a transformative shift through the integration of multi-omics data, which mainly encompasses genomics, transcriptomics, proteomics, and metabolomics. This synergy allows for a comprehensive understanding of individual health by analyzing genetic, molecular, and…
Junwen Su, Lamei Yang, Ziran Sun, Xianquan Zhan
Personalized medicine can reduce adverse effects, enhance drug efficacy, and optimize treatment outcomes, which represents the essence of personalized medicine in the pharmacy field. Protein drugs are crucial in the field of personalized drug therapy and are currently the mainstay, which possess higher target…
Ahmed Bakr, Youssef Basem, Abanoub Sherif, Alamer Ata + 6 more
Precision medicine, which relies on genomic, multi-omic, phenotypic, and environmental data, has the potential to transform healthcare from population-focused heuristics to individualized prevention, diagnosis, and treatment. Moreover, recent advances in sequencing, molecular profiles, wearable sensors, and machine…
Hanumantha Rao Balaji Raghavendran, Govindasamy Kumaramanickavel, Takeshi Iwata
'Takeshi Iwata'] Personalized medicine is a cutting-edge subspecialty of medicine. The American Cancer Society states that “Precision medicine is a way for healthcare professionals to offer and plan specific care for their patients, based on the specific genes, proteins, and other substances in a person's body” (1).…
Yalan Zhou, Siqi Peng, Huizhen Wang, Xinyin Cai + 2 more
In recent years, the FDA has approved numerous anti-cancer drugs that are mutation-based for clinical use. These drugs have improved the precision of treatment and reduced adverse effects and side effects. Personalized therapy is a prominent and hot topic of current medicine and also represents the future direction of…
Alexander Muacevic, John R Adler, Dharani S, Kamaraj R
Personalized medicine integrates genomics with clinical and familial histories, revolutionizing healthcare by tailoring treatments to individual patient characteristics. At its core, pharmacogenomics enables the customization of medication prescriptions based on genetic profiles, enhancing drug efficacy and safety.…
Michael S. Yao, Osbert Bastani, Alma Andersson, Tommaso Biancalani + 2 more
The goal of personalized medicine is to discover a treatment regimen that optimizes a patient's clinical outcome based on their personal genetic and environmental factors. However, candidate treatments cannot be arbitrarily administered to the patient to assess their efficacy; we often instead have access to an in…
Gal Dinstag, Eldad D. Shulman, Efrat Elis, Doreen S. Ben-Zvi + 27 more
Precision oncology is gradually advancing into mainstream clinical practice, demonstrating significant survival benefits. However, eligibility and response rates remain limited in many cases, calling for better predictive biomarkers. We present ENLIGHT, a transcriptomics-based computational approach that identifies…
Dingxin Lu, Shurui Wu, Xinyi Huang
With the timely formation of personalized intervention plans based on high-dimensional heterogeneous time series information has become an important challenge in the medical field today. As electronic medical records, wearables and other multi-source medical data are increasingly generated and diversified. In this…
Liya Popova, Valerie J. Carabetta
The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine.…
Rida Nasir Butt, Bibi Amina, Muhammad Umer Sultan, Zain Bin Tanveer + 8 more
Computational modeling and analysis of biomolecular network models annotated with cancer patient-specific multi-omics data can enable the development of personalized therapies. Current endeavors aimed at employing in silico models towards personalized cancer therapeutics remain to be fully translated. In this work, we…
Elizaveta Savchenko, Svetlana Bunimovich‐Mendrazitsky
In today's complex healthcare landscape, the pursuit of delivering optimal patient care while navigating intricate economic dynamics poses a significant challenge for healthcare service providers (HSPs). In this already complex dynamics, the emergence of clinically promising personalized medicine based treatment aims…
Kishi Kobe Yee Francisco, Andrane Estelle Carnicer Apuhin, Myles Joshua Toledo Tan, Mickael Cavanaugh Byers + 3 more
The rapid evolution of biomedical data and computational tools is driving transformative changes in healthcare, with personalized medicine (PM) at the forefront (Tawfik et al., 2023). Often called precision medicine, PM leverages an individual's unique genetic, environmental, and lifestyle data to guide treatment…
Raghunandan Wable, Achuth Suresh Nair, Anirudh Pappu, Widnie Pierre-Louis + 6 more
Timely understanding of biological secrets of complex diseases will ultimately benefit millions of individuals by reducing the high risks for mortality and improving the quality of life with personalized diagnoses and treatments. Due to the advancements in sequencing technologies and reduced cost, genomics data is…
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Ensuring the trustworthiness of machine learning (ML) models in high-stake applications is crucial. One such application is predicting anti-cancer drug sensitivity, where ML models are built with the final goal of integrating them into treatment recommendation systems for personalized medicine. Here, we propose a…
Anuj Ojha, Shu-Jun Zhao, Jian-Ting Zhang, Kerri A. Simo + 1 more
In this study, using RNA-Seq gene expression data and advanced machine learning techniques, we identified distinct gene expression profiles between male and female pancreatic ductal adenocarcinoma (PDAC) patients. Building upon this insight, we developed sex-specific 3-year survival predictive models, which achieved…
Lingli Wang, Rumeng Qu, Qialing Huang, Min Hu + 1 more
Tumor heterogeneity highlights the necessity of precision cancer medicine, making the evaluation and screening of anticancer drugs a core challenge in cancer therapy. However, current cell-based efficacy assessment methods struggle to quantify the holistic impact of drugs on cellular behavior through specific target…
Xiaoxi Li, Ling Liu, Yuanyuan Yan, Mengfang Yang + 3 more
Tumor heterogeneity plays a critical role in tumor relapse and the development of drug resistance. Current personalized strategies, based on genetic profiling or bulk tumor drug sensitivity testing, offer limited clinical value as they overlook clonal heterogeneity. Here, through establishing primary tumor cell…
Zhaoqi Li, Emma Brunskill
From medicine to marketing to social sciences, the promise of tailoring interventions to individuals is undeniable. However, practical applications force weighing personalization's potential benefits with its possible increased cost and fragility. We introduce a statistical hypothesis test that evaluates, given…
Theodore M. Nelson, Julianna K. Rose, Claire E. Walter, Gresia L. Cervantes-Navarro + 11 more
Ten years ago, it was predicted that the multi-omics revolution would also revolutionize space pharmacogenomics. Current barriers related to the findable, accessible, interoperable, and reproducible use of space-flown pharmaceutical data have contributed to a lack of progress beyond application of earth-based…
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Immuno-oncology, a rapidly evolving field at the forefront of cancer research, leverages the body’s immune system to fight cancer. In this follow up report, we extend our natural language processing (NLP)-based analysis to pinpoint the context of emergence of the previously identified emerging concepts. To achieve this…
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This conceptual framework proposes an out-of-the-box approach to innovate non-biological drugs that surpass biologics by 200-fold in efficacy and safety for cancer treatment. Integrating advanced paradigms from physics, chemistry, medicine, biology, engineering, and materials science, we delineate a multi-dimensional…
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Integrating machine learning (ML) into drug discovery has ushered in a new era of innovation, dramatically enhancing the efficiency and precision of identifying and developing new therapeutics. This review provides a comprehensive analysis of the current applications of machine learning in drug discovery, focusing on…
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Despite $100 billion in investment and more than 100,000 publications, nanomedicine translation fails primarily at biological validation, not at synthesis or characterization. We present the first systematic technology readiness assessment across autonomous nanomedicine components, revealing a critical finding: while…
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In this report, we examine the extensive research landscape of CRISPR with an emphasis on CRISPR therapeutics and showcase our results from an in-depth analysis of the most up-to-date scientific information consisting of more than 53,000 publications encompassing academic journal articles and patents, spanning nearly…