Integrating Model-Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation.

The pharmaceutical industry constantly strives to improve drug development processes to reduce costs, increase efficiencies, and enhance therapeutic outcomes for patients. Model-Informed Drug Development (MIDD) uses mathematical models to simulate intricate processes involved in drug absorption, distribution, metabolism, and excretion, as well as pharmacokinetics and pharmacodynamics. Artificial intelligence (AI), encompassing techniques such as machine learning, deep learning, and Generative AI, offers powerful tools and algorithms to efficiently identify meaningful patterns, correlations, and drug-target interactions from big data, enabling more accurate predictions and novel hypothesis generation.

Visualizing lipid nanoparticle trafficking for mRNA vaccine delivery in non-human primates.

mRNA delivered using lipid nanoparticles (LNPs) has become an important subunit vaccine modality, but mechanisms of action for mRNA vaccines remain incompletely understood. Here, we synthesized a metal chelator-lipid conjugate enabling positron emission tomography (PET) tracer labeling of LNP/mRNA vaccines for quantitative visualization of vaccine trafficking in live mice and non-human primates (NHPs). Following i.

A Digital Phenotypic Assessment in Neuro-Oncology (DANO): A Pilot Study on Sociability Changes in Patients Undergoing Treatment for Brain Malignancies.

Background: The digital phenotyping tool has great potential for the deep characterization of neurological and quality-of-life assessments in brain tumor patients. Phone communication activities (details on call and text use) can provide insight into the patients' sociability.

Methods: We prospectively collected digital-phenotyping data from six brain tumor patients.

Optimized Prime Editing of Human Induced Pluripotent Stem Cells to Efficiently Generate Isogenic Models of Mendelian Diseases.

Prime editing (PE) is a CRISPR-based tool for genome engineering that can be applied to generate human induced pluripotent stem cell (hiPSC)-based disease models. PE technology safely introduces point mutations, small insertions, and deletions (indels) into the genome. It uses a Cas9-nickase (nCas9) fused to a reverse transcriptase (RT) as an editor and a PE guide RNA (pegRNA), which introduces the desired edit with great precision without creating double-strand breaks (DSBs).

Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats.

The COVID-19 pandemic exposed a global deficiency of systematic, data-driven guidance to identify high-risk individuals. Here, we illustrate the utility of routinely recorded medical history to predict the risk for 1741 diseases across clinical specialties and support the rapid response to emerging health threats such as COVID-19. We developed a neural network to learn from health records of 502,489 UK Biobank participants.

Post-transcriptional cross- and auto-regulation buffer expression of the human RNA helicases and .

The Y-linked gene and its X-linked homolog survived the evolution of the human sex chromosomes from ordinary autosomes. encodes a multifunctional RNA helicase, with mutations causing developmental disorders and cancers. We find that, among X-linked genes with surviving Y homologs, is extraordinarily dosage sensitive.

Effects of maze appearance on maze solving.

As mazes are typically complex, cluttered stimuli, solving them is likely limited by visual crowding. Thus, several aspects of the appearance of the maze - the thickness, spacing, and curvature of the paths, as well as the texture of both paths and walls - likely influence the performance. In the current study, we investigate the effects of perceptual aspects of maze design on maze-solving performance to understand the role of crowding and visual complexity.

Induced seismicity and geothermal energy production in the Salton Sea Geothermal Field, California.

We analyze the relationship between geothermal energy production and seismic hazards in the Salton Sea Geothermal Field (SSGF) between 1972 and 2022. A clear increase in seismic activity accompanies geothermal energy production and is greatest to the east of the Brawley fault, where the amount of injection exceeds the amount of production. We estimate that, whereas there was a 2% chance of a M6.

Designer topological-single-atom catalysts with site-specific selectivity.

Designing catalysts with well-defined, identical sites that achieve site-specific selectivity, and activity remains a significant challenge. In this work, we introduce a design principle of topological-single-atom catalysts (T-SACs) guided by density functional theory (DFT) and Ab initio molecular dynamics (AIMD) calculations, where metal single atoms are arranged in asymmetric configurations that electronic shield topologically misorients d orbitals, minimizing unwanted interactions between reactants and the support surface. Mn/CeO catalysts, synthesized via a charge-transfer-driven approach, demonstrate superior catalytic activity and selectivity for NO removal.

Radiosynthesis and evaluation of novel F labeled PET ligands for imaging monoacylglycerol lipase.

Monoacylglycerol lipase (MAGL) is a 33 kDa cytosolic serine hydrolase that is widely distributed in the central nervous system and peripheral tissues. MAGL hydrolyzes monoacylglycerols into fatty acids and glycerol, playing a crucial role in endocannabinoid degradation. Inhibition of MAGL in the brain elevates levels of 2-arachidonoylglycerol and leads to decreased pro-inflammatory prostaglandin and thromboxane production.

Learning the language of antibody hypervariability.

Protein language models (PLMs) have demonstrated impressive success in modeling proteins. However, general-purpose "foundational" PLMs have limited performance in modeling antibodies due to the latter's hypervariable regions, which do not conform to the evolutionary conservation principles that such models rely on. In this study, we propose a transfer learning framework called Antibody Mutagenesis-Augmented Processing (AbMAP), which fine-tunes foundational models for antibody-sequence inputs by supervising on antibody structure and binding specificity examples.

Metastable state preceding shear zone instability: Implications for earthquake-accelerated landslides and dynamic triggering.

Understanding the dynamic response of granular shear zones under cyclic loading is fundamental to elucidating the mechanisms triggering earthquake-induced landslides, with implications for broader fields such as seismology and granular physics. Existing prediction methods struggle to accurately predict many experimental and in situ landslide observations due to inadequate consideration of the underlying physical mechanisms. The mechanisms that influence landslide dynamic triggering, a transition from static (or extremely slow creeping) to rapid runout, remain elusive.

Modular DNA origami-based electrochemical detection of DNA and proteins.

The diversity and heterogeneity of biomarkers has made the development of general methods for single-step quantification of analytes difficult. For individual biomarkers, electrochemical methods that detect a conformational change in an affinity binder upon analyte binding have shown promise. However, because the conformational change must operate within a nanometer-scale working distance, an entirely new sensor, with a unique conformational change, must be developed for each analyte.

Voices of Nanomedicine: Blueprint Guidelines for Collaboration in Addressing Global Unmet Medical Needs.

The "" under this Perspective underline the importance of interdisciplinary collaboration and partnerships across several disciplines, such as medical science and technology, medicine, bioengineering, and computational approaches, in bridging the gap between research, manufacturing, and clinical applications. Effective communication is key to bridging team gaps, enhancing trust, and resolving conflicts, thereby fostering teamwork and individual growth toward shared goals. Drawing from the success of the COVID-19 vaccine development, we advocate the application of similar collaborative models in other complex health areas such as nanomedicine and biomedical engineering.

Ultrasensitive detection of intact SARS-CoV-2 particles in complex biofluids using microfluidic affinity capture.

Measuring virus in biofluids is complicated by confounding biomolecules coisolated with viral nucleic acids. To address this, we developed an affinity-based microfluidic device for specific capture of intact severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our approach used an engineered angiotensin-converting enzyme 2 to capture intact virus from plasma and other complex biofluids.

Doctors as Device Manufacturers? Regulation of Clinician-Generated Innovation in the ICU.

Critical care physicians are rich sources of innovation, developing new diagnostic, prognostic, and treatment tools they deploy in clinical practice, including novel software-based tools. Many of these tools are validated and promise to actively help patients, but physicians may be unlikely to distribute, implement, or share them with other centers noncommercially because of unsettled ethical, regulatory, or medicolegal concerns. This Viewpoint explores the potential barriers and risks critical care physicians face in disseminating device-related innovations for noncommercial purposes and proposes a framework for risk-based evaluation to foster clear pathways to safeguard equitable patient access and responsible implementation of clinician-generated technological innovations in critical care.

Repurposing Licensed Drugs with Activity Against Epstein-Barr Virus for Treatment of Multiple Sclerosis: A Systematic Approach.

Background: Epstein-Barr virus (EBV) is implicated as a necessary factor in the development of multiple sclerosis (MS) and may also be a driver of disease activity. Although it is not clear whether ongoing viral replication is the driver for MS pathology, MS researchers have considered the prospect of using drugs with potential efficacy against EBV in the treatment of MS. We have undertaken scientific and lived experience expert panel reviews to shortlist existing licensed therapies that could be used in later-stage clinical trials in MS.

Draft genome sequence of sp. SA01 isolated from seedlings collected in Cape Cod (USA).

A draft genome was generated for a strain of closely related to sp. ENV421 isolated from plants of smooth cordgrass germinated from seeds collected in a salt marsh in Cape Cod (USA). Genomic DNA was sequenced using paired-end Illumina technologies.

3D-Printable Elastomers for Real-Time Autonomous Self-Healing in Soft Devices.

Photocurable self-healing elastomers are promising candidates for producing complex soft devices that can mend damage. However, the practicality of these materials is limited by reliance on external stimuli, custom synthesis, manual realignment, and multihour healing cycles. This paper introduces a tough 3D-printable hybrid acrylate/thiol-ene elastomer (prepared with commercially available precursors) that exhibits nearly instantaneous damage repair in the absence of external stimuli.

Taurine prevents mitochondrial dysfunction and protects mitochondria from reactive oxygen species and deuterium toxicity.

Taurine, although not a coding amino acid, is the most common free amino acid in the body. Taurine has multiple and complex functions in protecting mitochondria against oxidative-nitrosative stress. In this comprehensive review paper, we introduce a novel potential role for taurine in protecting from deuterium (heavy hydrogen) toxicity.

UW supplementation with AP39 improves liver viability following static cold storage.

Static cold storage of donor livers at 4 °C incompletely arrests metabolism, ultimately leading to decreases in ATP levels, oxidative stress, cell death, and organ failure. Hydrogen Sulfide (HS) is an endogenously produced gas, previously demonstrated to reduce oxidative stress, reduce ATP depletion, and protect from ischemia and reperfusion injury. HS is difficult to administer due to its rapid release curve, resulting in cellular death at high concentrations.

Near-infrared fluorogenic RNA for in vivo imaging and sensing.

Fluorogenic RNA aptamers have various applications, including use as fluorescent tags for imaging RNA trafficking and as indicators of RNA-based sensors that exhibit fluorescence upon binding small-molecule fluorophores in living cells. Current fluorogenic RNA:fluorophore complexes typically emit visible fluorescence. However, it is challenging to develop fluorogenic RNA with near-infrared (NIR) fluorescence for in vivo imaging and sensing studies.

Deep learning generalization for diabetic retinopathy staging from fundus images.

Diabetic retinopathy (DR) is a serious diabetes complication that can lead to vision loss, making timely identification crucial. Existing data-driven algorithms for DR staging from digital fundus images (DFIs) often struggle with generalization due to distribution shifts between training and target domains. To address this, DRStageNet, a deep learning model, was developed using six public and independent datasets with 91,984 DFIs from diverse demographics.

Ena-bile-ing liver cancer growth.

Bile acids differentially affect immune cell responses to liver cancer.

The many misuses of the rape kit Vintage, 2025. 256 pp.

Haphazardly applied, frequently lost, and often ignored, the vital forensic tool also has a troubling past.