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Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development.

The discovery and advances of medicines may be considered as the ultimate relevant translational science effort that adds to human invulnerability and happiness. But advancing a fresh medication is a quite convoluted, costly, and protracted operation, normally costing USD ~2.6 billion and consuming a mean time span of 12 years. Methods to cut back expenditure and hasten new drug discovery have prompted an arduous and compelling brainstorming exercise in the pharmaceutical industry. The engagement of Artificial Intelligence (AI), including the deep-learning (DL) component in particular, has bee

Deep Learning Techniques to Characterize the RPS28P7 Pseudogene and the Metazoa-SRP Gene as Drug Potential Targets in Pancreatic Cancer Patients.

The molecular explanation about why some pancreatic cancer (PaCa) patients die early and others die later is poorly understood. This study aimed to discover potential novel markers and drug targets that could be useful to stratify and extend expected survival in prospective early-death patients. We deployed a deep learning algorithm and analyzed the gene copy number, gene expression, and protein expression data of death versus alive PaCa patients from the GDC cohort. The genes with higher relative amplification (copy number >4 times in the dead compared with the alive group) were EWSR1, FLT3,

Artificial intelligence in immunotherapy: revolutionizing diagnostic and therapeutic applications in cancer and autoimmune diseases.

Artificial intelligence (AI) is increasingly advancing precision immunotherapy by integrating high-dimensional biomedical data to support diagnosis, treatment selection, and longitudinal monitoring in both cancer and autoimmune diseases. This review summarizes AI applications in biomarker discovery, prediction of immune checkpoint inhibitor (ICI) response and toxicity, neoantigen prioritization, CAR-T cell optimization, and therapeutic antibody engineering. In oncology, multimodal models combining multi-omics, medical imaging, and clinical variables improve patient stratification and non-invas

Long-term projections of cancer prevalence in Australia to 2050: a population-based statistical modelling study.

BACKGROUND: Cancer prevalence is the number of people alive with a past cancer diagnosis in a specified number of previous years (e.g., last 5 or 30 years). This study estimates 1- to 30-year cancer prevalence in Australia for each year in 2025-2050, for 24 cancer types, the group of remaining cancers, and for all cancers combined. METHODS: We used validated methods to estimate prevalence as a function of incidence and survival, using tabulated data from the Australian Institute of Health and Welfare and incorporating the effect of influential cancer-specific factors. The number of people liv

Seasonal clustering of sinopulmonary mucormycosis in patients with hematologic malignancies at a large comprehensive cancer center.

BackgroundInvasive Mucorales infections (IMI) lead to significant morbidity and mortality in immunocompromised hosts. The role of season and climatic conditions in case clustering of IMI remain poorly understood.MethodsFollowing detection of a cluster of sinopulmonary IMIs in patients with hematologic malignancies, we reviewed center-based medical records of all patients with IMIs and other invasive fungal infections (IFIs) between January of 2012 and August of 2015 to assess for case clustering in relation to seasonality.ResultsA cluster of 7 patients were identified with sinopulmonary IMIs (

A Rebalancing of Financial Valuations and Expectations Moving Forward in the Telehealth Sector as the United States Moves Toward a Post-COVID-19 Reality.

The telehealth sector of health care delivery experienced significant growth at the start of the pandemic as web-based care quickly became essential for the ongoing safety of patients and health care providers, such as clinicians and other health care professionals. After vaccines were introduced, however, telehealth companies lost value as the need for web-based care appeared to lessen. Presently, both existing telehealth companies and new entrants to the space are seeking ways to innovate, gain investor and customer buy-in, and overcome competitors. New companies are hoping to be seen not as

Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life Years for 29 Cancer Groups From 2010 to 2019: A Systematic Analysis for the Global Burden of Disease Study 2019.

IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over

Revolutionizing hematological disorder diagnosis: unraveling the role of artificial intelligence.

The integration of artificial intelligence (AI) into medical diagnostics is transforming the landscape of healthcare, particularly in hematology. AI technologies, leveraging advanced machine learning algorithms and big data analytics, are revolutionizing the diagnosis of hematological disorders such as anemia, leukemia, and lymphoma. This review explores how AI enhances diagnostic accuracy, efficiency, and patient outcomes by processing complex datasets and identifying patterns beyond human capability. AI-driven advancements in hematology include innovations in image analysis, genomic data int

Model-Informed Drug Development for Ixazomib, an Oral Proteasome Inhibitor.

Model-informed drug development (MIDD) was central to the development of the oral proteasome inhibitor ixazomib, facilitating internal decisions (switch from body surface area (BSA)-based to fixed dosing, inclusive phase III trials, portfolio prioritization of ixazomib-based combinations, phase III dose for maintenance treatment), regulatory review (model-informed QT analysis, benefit-risk of 4 mg dose), and product labeling (absolute bioavailability and intrinsic/extrinsic factors). This review discusses the impact of MIDD in enabling patient-centric therapeutic optimization during the develo

Burden of All Cancers Along With Attributable Risk Factors in China From 1990 to 2019: Comparison With Japan, European Union, and USA.

BackgroundUnderstanding the epidemiological characteristics of various cancers can optimize the prevention and control strategies in the national cancer control plan. This study aimed to report the burden differences, pattern trend, and potential risk factors of all neoplasm types in China in recent 30 years, and further compared with top economies in the world.MethodsThe disability-adjusted life-years (DALYs) and age-standardized DALY rate (ASDR) of all neoplasms with the attributable risk factors from 1990 to 2019 in China, Japan, European Union, USA, and the world were extracted from the Gl

Reimbursement of licensed cell and gene therapies across the major European healthcare markets.

ObjectiveThe aim of this research is to identify the pricing, reimbursement, and market access (P&R&MA) considerations most relevant to advanced therapy medicinal products (ATMPs) in the Big5EU, and to inform their manufacturers about the key drivers for securing adoption at a commercially viable reimbursed price.MethodologyThe research was structured following three main steps: 1) Identifying the market access pathways relevant to ATMPs through secondary research; 2) Validating the secondary research findings and addressing any data gaps in primary research, by qualitative interviews with nat

Developing and validating a discrete-event simulation model of multiple myeloma disease outcomes and treatment pathways using a national clinical registry.

Multiple myeloma is a haematological malignancy typically characterised by neoplastic plasma cell infiltration of the bone marrow. Treatment for multiple myeloma consists of multi-line chemotherapy with or without autologous stem cell transplantation and has been rapidly evolving in recent years. However, clinical trials are unable to provide patients and clinicians with long-term prognostic information nor policymakers with the full body of evidence needed to perform economic evaluation of new therapies or make reimbursement decisions. To address these limitations of the available evidence, t

Machine learning-based identification of co-expressed genes in prostate cancer and CRPC and construction of prognostic models.

The objective of this study was to employ machine learning to identify shared differentially expressed genes (DEGs) in prostate cancer (PCa) initiation and castration resistance, aiming to establish a robust prognostic model and enhance understanding of patient prognosis for personalized treatment strategies. mRNA transcriptome data associated with Castration-Resistant Prostate Cancer (CRPC) were obtained from the GEO database. Differential expression analysis was conducted using the limma R package to compare normal prostate samples with PCa samples, and PCa samples with CRPC samples. Next, w

Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines.

OBJECTIVE: Bloodstream infection (BSI) is a significant cause of mortality in patients with hematologic malignancies(HMs), particularly amid rising antibiotic resistance. This study aimed to analyze pathogen distribution, drug-resistance patterns and develop a novel predictive model for 30-day mortality in HM patients with BSIs. METHODS: A retrospective analysis of 231 HM patients with positive blood cultures was conducted. Logistic regression identified risk factors for 30-day mortality. Th1/Th2 cytokines were collected at BSI onset, with LASSO regression and restricted cubic spline analysis

Тенденции смертности от почечной недостаточности среди многих пациентов в возрасте от миэломы ≥ 45 годы, 1999-2023Анализ данных ЦКЗ.

Множественная миелома (ММ) — плазменная порча клеток, которая часто осложняется почечным расстройством, что значительно ухудшает прогноз. Несмотря на то, что терапевтический прогресс улучшил выживание ММ, почечная недостаточность по-прежнему является одной из основных причин неблагоприятных последствий. В этом исследовании были рассмотрены долгосрочные тенденции и демографические различия в показателях смертности среди лиц, умерших в США, при этом ММ была названа основной причиной смерти и почечной недостаточности, которая была названа одной из причин смертности. Данные о смертности среди взро

Глобальное, региональное и национальное бремя связанных с табаком неврологических расстройств 1990 в адрес 2021Тенденции и прогнозы на будущее.

ВВЕДЕНИЕ: Потребление табака является одной из основных проблем здравоохранения во всем мире, отрицательно сказывающейся на качестве жизни. Цель нашего исследования состоит в том, чтобы проанализировать тенденции изменения бремени связанных с табаком неврологических расстройств на глобальном, региональном и национальном уровнях. 1990 в адрес 2021, а также потенциальные будущие тенденции. МЕТОДЫ: Мы провели вторичный анализ наборов данных для оценки смертности и лет жизни с поправкой на инвалидность (DALYs) с использованием данных, полученных в рамках исследования глобального бремени болезней,

A Comparative Analysis of Multiple Myeloma Disease Burden in China and Globally From 1990 to 2023 and Future Trend Projections.

BACKGROUND: Multiple myeloma (MM) is a prevalent hematologic malignancy. A systematic comparison of the temporal trends in MM disease burden between China and the global level is important for optimizing prevention and control strategies. This study describes trends in the age- and sex-specific burden of MM in China from 1990 to 2023, including incidence, prevalence, mortality, and disability-adjusted life years (DALYs); projects sex-specific incidence to 2050; and compares findings globally. METHODS: Using the Global Burden of Disease (GBD) 2023 database, we extracted data on MM in China and

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… Population projections for 2024–2050 were obtained from the Global Fertility, Mortality, Migration, and Population Forecasts 2017–2100, produced by the Institute for Health Metrics and Evaluation and available through the GBD Foresight visualization tool. …

Exploring novel therapeutic strategies: Could psychedelic perspectives offer promising solutions for Alzheimer's disease comorbidities?

The increasing prevalence of dementia within an ageing global population, combined with prolonged life expectancy, accentuates Alzheimer's disease (AD) as a multifaceted healthcare challenge. This challenge is further compounded by the limited therapeutic options currently available. Addressing the intricacies of AD management, the mitigation of comorbidities has emerged as a pivotal facet of treatment. Comorbid conditions, such as neurobehavioral symptoms, play a role in shaping the clinical course, management, and outcomes of this pathology; highlighting the importance of comprehensive care

Стратегии интеграции искусственного интеллекта и когнитивной оценки для прогнозирования развития инвалидности в релапсирующихся множестве склерозов: исследование по разработке моделей.

Серийная когнитивная оценка при множественном склерозе может помочь выявить пациентов, подверженных более высокому риску развития инвалидности, однако высокая масштабность данных о времени реакции затрудняет анализ. Мы разработали метод преобразования данных о времени продольной реакции в изображения и применили модели глубокого выживания для прогнозирования развития инвалидности в релапсирующих MS (RRMS). В этом когортном исследовании клинические данные были получены из регистра MSBase и когнитивных данных из компьютеризированной когнитивной батареи MSRector в период с февраля 2016 года по се

Биомаркеры крови отражают патологию мозга - от общих земель до редких границ.

Понимание патологических изменений в мозге имеет важное значение для принятия решений о лечении травм мозга и заболеваний. Несмотря на значительные достижения в методах сканирования мозга, клиническая практика по-прежнему сталкивается с проблемами из-за зависимости от инфраструктуры и высоких потребностей в ресурсах. В ходе этого обзора изучаются нынешние знания о биомаркерах на основе крови, которые указывают на патологию мозга, которая может помочь в идентификации пациентов, подверженных риску, диагностике пациентов, прогнозировании прогрессии заболеваний и лечении. Мы сосредоточимся на унас