FDA General

From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.

Vascular endothelial growth factor receptor 2 (VEGFR-2) stands as a prominent therapeutic target in oncology, playing a critical role in angiogenesis, tumor growth, and metastasis. FDA-approved VEGFR-2 inhibitors are associated with diverse side effects. Thus, finding novel and more effective inhibitors is of utmost importance. In this study, a deep learning (DL) classification model was first dev...

Artificial intelligence for small molecule anticancer drug discovery.

INTRODUCTION: The transition from conventional cytotoxic chemotherapy to targeted cancer therapy with small-molecule anticancer drugs has enhanced treatment outcomes. This approach, which now dominates cancer treatment, has its advantages. Despite the regulatory approval of several targeted molecules for clinical use, challenges such as low response rates and drug resistance still persist. Convent...

Ensuring food safety by artificial intelligence-enhanced nanosensor arrays.

Current analytical methods utilized for food safety inspection requires improvement in terms of their cost-efficiency, speed of detection, and ease of...

Challenges and opportunities in the development and clinical implementation of artificial intelligence based synthetic computed tomography for magnetic resonance only radiotherapy.

Synthetic computed tomography (sCT) generated from magnetic resonance imaging (MRI) can serve as a substitute for planning CT in radiation therapy (RT...

DeepRA: A novel deep learning-read-across framework and its application in non-sugar sweeteners mutagenicity prediction.

Non-sugar sweeteners (NSSs) or artificial sweeteners have long been used as food chemicals since World War II. NSSs, however, also raise a concern abo...

Attitudes of Algorithms: An Exploration of the Ethics of CRISPR Cas9 through the Lens of ChatGPT.

The controversies surrounding CRISPR Cas9 are multifaceted, encompassing concerns related to unintended genetic consequences, ethical and legal consid...

Deep learning-based flocculation sensor for automatic control of flocculant dose in sludge dewatering processes during wastewater treatment.

In sludge dewatering of most wastewater treatment plants (WWTPs), the dose of polymer flocculant is manually adjusted through direct visual inspection...

Application of molecular dynamics-based pharmacophore and machine learning approaches to identify novel Mcl1 inhibitors through drug repurposing and mechanics research.

Myeloid cell leukemia 1 (Mcl1), a critical protein that regulates apoptosis, has been considered as a promising target for antitumor drugs. The conven...

Trust but Verify: Lessons Learned for the Application of AI to Case-Based Clinical Decision-Making From Postmarketing Drug Safety Assessment at the US Food and Drug Administration.

Adverse drug reactions are a common cause of morbidity in health care. The US Food and Drug Administration (FDA) evaluates individual case safety repo...

Does an App a Day Keep the Doctor Away? AI Symptom Checker Applications, Entrenched Bias, and Professional Responsibility.

The growing prominence of artificial intelligence (AI) in mobile health (mHealth) has given rise to a distinct subset of apps that provide users with ...

PPRTGI: A Personalized PageRank Graph Neural Network for TF-Target Gene Interaction Detection.

Transcription factors (TFs) regulation is required for the vast majority of biological processes in living organisms. Some diseases may be caused by i...

Study on breast cancerization and isolated diagnosis in situ by HOF-ATR-MIR spectroscopy with deep learning.

Mid-infrared (MIR) spectroscopy can characterize the content and structural changes of macromolecular components in different breast tissues, which ca...

Using a hybrid neural network architecture for DNA sequence representation: A study on N-methylcytosine sites.

N-methylcytosine (4mC) is a modified form of cytosine found in DNA, contributing to epigenetic regulation. It exists in various genomes, including the...

Determination of Patulin in Apple Juice and Apple-Derived Products Using a Robotic Sample Preparation System and LC-APCI-MS/MS.

Patulin, a toxic mycotoxin, can contaminate apple-derived products. The FDA has established an action level of 50 ppb (ng/g) for patulin in apple juic...

Establishing a Validation Infrastructure for Imaging-Based Artificial Intelligence Algorithms Before Clinical Implementation.

With promising artificial intelligence (AI) algorithms receiving FDA clearance, the potential impact of these models on clinical outcomes must be eval...

Respiratory Syncytial Virus Vaccine Design Using Structure-Based Machine-Learning Models.

When designing live-attenuated respiratory syncytial virus (RSV) vaccine candidates, attenuating mutations can be developed through biologic selection...

Hepatic toxicity prediction of bisphenol analogs by machine learning strategy.

Toxicological studies have demonstrated the hepatic toxicity of several bisphenol analogs (BPs), a prevalent type of endocrine disruptor. The developm...

BiLSTM- and CNN-Based m6A Modification Prediction Model for circRNAs.

m6A methylation, a ubiquitous modification on circRNAs, exerts a profound influence on RNA function, intracellular behavior, and diverse biological pr...

Implications of Large Language Models for Quality and Efficiency of Neurologic Care: Emerging Issues in Neurology.

Large language models (LLMs) are advanced artificial intelligence (AI) systems that excel in recognizing and generating human-like language, possibly ...

Accelerating reliable multiscale quantum refinement of protein-drug systems enabled by machine learning.

Biomacromolecule structures are essential for drug development and biocatalysis. Quantum refinement (QR) methods, which employ reliable quantum mechan...