Future innovative therapies targeting cardiovascular disease (CVD) have the potential to improve health outcomes and to contain rising healthcare costs. Unsustainable increases in the size, cost and duration of clinical trial programs necessary for regulatory approval, however, threaten the entire innovation enterprise. Rising costs for clinical trials are due in large part to increasing demands for hard cardiovascular clinical endpoints as measures of therapeutic efficacy. The development and validation of predictive and surrogate biomarkers, as laboratory or other objective measures predictive or reflective of clinical endpoints, are an important part of the solution to this challenge. This review will discuss insights applicable to CVD derived from the use of predictive biomarkers in oncologic drug development, the evolving role of high density lipoprotein (HDL) in CVD drug development and the impact biomarkers and surrogates have on the continued investment from multiple societal sources critical for innovative CVD drug discovery and development.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s11883-013-0321-0 | 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.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!