Results 111 to 120 of about 16,351 (263)
ABSTRACT Background For patients with unfavorable intermediate or high risk localized prostate cancer receiving definitive radiotherapy, androgen deprivation therapy reduces recurrence and improves survival but is underutilized due to toxicity concerns. Patients who forgo initial ADT may later require salvage ADT.
Jiaye Shen +4 more
wiley +1 more source
Abstract Intranasal diamorphine (IND), approved for managing breakthrough pain in the UK, has been identified as an acceptable alternative offering effective, expedient, and less traumatic analgesia for children. However, the current dose regimen in pediatric populations relies on clinical expertise while the pharmacokinetics properties are poorly ...
Lianjin Cai +6 more
wiley +1 more source
Abstract Myelodysplastic syndromes (MDS) represent a group of bone marrow disorders involving cytopenias, hypercellular bone marrow, and dysplastic hematopoietic progenitors. MDS remains a challenge to treat due to the complex interplay between disease‐induced and treatment‐related cytopenias.
Neha Thakre +5 more
wiley +1 more source
Abstract Mirikizumab is a p19‐directed anti‐interleukin‐23 antibody approved for the treatment of adults with moderate‐to‐severe ulcerative colitis (UC). Here, we report the first data of mirikizumab pharmacokinetics (PK) and exposure–response (E/R) relationships in pediatric participants (aged 2 to <18 years weighing >10 kg) with moderate‐to‐severe UC
Yuki Otani +5 more
wiley +1 more source
Advancing pharmacometrics in Africa—Transition from capacity development toward job creation
Abstract Trained pharmacometricians remain scarce in Africa due to limited training opportunities, lack of a pharmaceutical product development ecosystem, and emigration to high‐income countries. The Applied Pharmacometrics Training (APT) fellowship program was established to address these gaps and specifically foster job creation for talent retention.
Goonaseelan (Colin) Pillai +10 more
wiley +1 more source
Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma
ABSTRACT We employed a mechanistic learning approach, integrating on‐treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post‐progression survival (PPS)—the duration from the time of documented disease progression to death—and overall survival (OS) in Head and Neck Squamous Cell ...
Kevin Atsou +4 more
wiley +1 more source
Bivariate postprocessing of wind vectors
We introduce three novel bivariate postprocessing approaches and analyze their performance for joint postprocessing of bivariate wind‐vector components in Germany. Bivariate vine‐copula‐based models, a bivariate gradient‐boosted version of ensemble model output statistics (EMOS), and a bivariate distributional regression network (DRN) are compared with
Ferdinand Buchner +3 more
wiley +1 more source
Hybrid physics–data‐driven modeling for sea ice thermodynamics and transfer learning
Icepack–NN, a machine‐learning‐based hybrid version of the sea‐ice column model Icepack, is developed to correct state‐dependent forecast errors arising from misspecified snow thermodynamics, using neural networks applied online within the physical model.
G. De Cillis +7 more
wiley +1 more source
Species distribution models (SDMs) have been widely used in ecology to understand how species relate to environmental variation. Most SDMs are correlative, and they lack explicit reference to the underlying processes, and therefore, the reliability of ...
Jukka Sirén +2 more
doaj +1 more source

