Microsampling has revolutionized pharmaceutical drug development and clinical research by reducing sample volume requirements, allowing sample collection at home or nontraditional sites, minimizing animal and patient burden, and enabling more flexible study designs. This perspective paper discusses the transformative impact of microsampling and patient-centric sampling (PCS) techniques, emphasizing their advantages in drug development and clinical trials. We highlight the integration of liquid chromatography-mass spectrometry (LC-MS) strategies for analyzing PCS samples, focusing on our research experience and a review of current literatures. The paper reviews commercially available PCS devices, their regulatory status, and their application in clinical trials, underscoring the benefits of PCS in expanding patient enrollment diversity and improving study designs. We also address the operational challenges of implementing PCS, including the need for bridging studies to ensure data comparability between traditional and microsampling methods, and the analytical challenges posed by PCS samples. The paper proposes future directions for PCS, including the development of global regulatory standards, technological advancements to enhance user experience, the increased concern of sustainability and patient data privacy, and the integration of PCS with other technologies for improved performance in drug development and clinical studies. By advancing microsampling and PCS techniques, we aim to foster patient-centric approaches in pharmaceutical sciences, ultimately enhancing patient care and treatment efficacy.
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http://dx.doi.org/10.1002/jms.5023 | DOI Listing |
Crit Rev Anal Chem
January 2025
Chemistry Department, Faculty of Science, Cairo University, Giza, Egypt.
Epilepsy is a serious neurological disease that impacts all facets of a patient's life, including their socioeconomic situation. The failure to identify underlying epileptic signatures in their early stages might result in severe harm to the central nervous system (CNS) and permanent adverse changes to some organs. Therefore, numerous antiepileptic drugs (AEDs are frequently used to control and treat the frequency of seizures.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
Department of Pharmacology, School of Pharmacy, China Medical University, Shenyang, 110122, China.
Hydrogen sulfide (HS)-mediated protein S-sulfhydration has been shown to play critical roles in several diseases. Tumor-associated macrophages (TAMs) are the predominant population of immune cells present within solid tumor tissues, and they function to restrict antitumor immunity. However, no previous study has investigated the role of protein S-sulfhydration in TAM reprogramming in breast cancer (BC).
View Article and Find Full Text PDFArch Dermatol Res
January 2025
Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Observational studies have shown that the risk of developing herpes zoster (HZ) increases with the use of statins. However, there are many confounding factors in observational studies. Therefore, our Mendelian randomization (MR) study aimed to explore the causal role of lipids in HZ and to assess the causal impact of lipid-lowering drug targets on HZ risk.
View Article and Find Full Text PDFDiscov Oncol
January 2025
Department of Bioscience and Biotechnology, Banasthali Vidyapith, Niwai-Tonk, Rajasthan, 304022, India.
The prominence of circular RNAs (circRNAs) has surged in cancer research due to their distinctive properties and impact on cancer development. This review delves into the role of circRNAs in four key cancer types: colorectal cancer (CRC), gastric cancer (GC), liver cancer (HCC), and lung cancer (LUAD). The focus lies on their potential as cancer biomarkers and drug targets.
View Article and Find Full Text PDFSci Rep
January 2025
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, 700 032, India.
We have adopted the classification Read-Across Structure-Activity Relationship (c-RASAR) approach in the present study for machine-learning (ML)-based model development from a recently reported curated dataset of nephrotoxicity potential of orally active drugs. We initially developed ML models using nine different algorithms separately on topological descriptors (referred to as simply "descriptors" in the subsequent sections of the manuscript) and MACCS fingerprints (referred to as "fingerprints" in the subsequent sections of the manuscript), thus generating 18 different ML QSAR models. Using the chemical spaces defined by the modeling descriptors and fingerprints, the similarity and error-based RASAR descriptors were computed, and the most discriminating RASAR descriptors were used to develop another set of 18 different ML c-RASAR models.
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