Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/437624

Exploring the Correlation between the Cognitive Benefits of Drug Combinations in a Clinical Alzheimer Disease Database and the Efficacies of the Same Drug Combinations Predicted from a Computational Model

Anastasio, T. J.
View original source ↗Export metadata ↓

Abstract

INTRODUCTIONIdentification of drug combinations that could be effective in Alzheimers treatment is made difficult by the number of possible combinations. This analysis identifies as potentially therapeutic those drug combinations that rank highest when their efficacy is determined jointly from two independent data sources.\n\nMETHODSEstimates of the efficacy of the same drug combinations were derived from a clinical dataset and from pre-clinical data, in the form of a computational model of neuroinflammation. Standard linear regression was used to show that the two sets of estimates were correlated, and to rule out possible confounds.\n\nRESULTSThe ten highest ranking, jointly determined drug combinations most frequently consisted of COX2 inhibitors and aspirin, along with various antihypertensive medications.\n\nDISCUSSIONTen combinations of from five to nine drugs, and the three-drug combination of a COX2 inhibitor, aspirin, and a calcium-channel blocker, are discussed as candidates for consideration in future clinical and pre-clinical studies.

Source connections

Explore related subjects

pharmacology and toxicologyPreprint

Keep this discovery

BibTeXRIS

Anastasio, T. J.. 2018-10-08. Exploring the Correlation between the Cognitive Benefits of Drug Combinations in a Clinical Alzheimer Disease Database and the Efficacies of the Same Drug Combinations Predicted from a Computational Model. https://doi.org/10.1101/437624

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Lipid-ASO therapeutics exhibit differential tissue targeted delivery upon systemic or local CNS administration

Antisense oligonucleotides (ASOs) are a powerful therapeutic modality, but their full potential is hindered by pharmacokinetic properties that affect tissue and cellular delivery. Lipid conjugation is increasingly used to modulate ASO's biodistribution and promote extrahepatic activity, yet lipid dependent effects on in vivo functional delivery, particularly in the central nervous system (CNS), remain less explored. Here, we performed a side by side in vivo comparison of cholesterol, palmitic acid (C16:0), docosanoic acid (C22:0), and eicosapentaenoic acid (C20:5) conjugated to a fully phosphorothioated 3 10 3 LNA gapmer ASO targeting the Malat1 long non coding RNA. Lipid-ASO conjugates were administered systemically or locally in the brain of mice and evaluated for tissue level and cellular level distribution by imaging, qPCR and single-cell RNA sequencing, simultaneously annotating cell origin and global transcriptional changes within the cell. Following systemic administration in mice, lipid conjugation improved overall multi organ efficacy compared to unconjugated ASO, but with pronounced tissue specific differences. Single cell sequencing of liver and heart transcriptomes revealed lipid dependent cellular uptake patterns and transcriptional responses distinct from administration of unconjugated ASO. After intracerebroventricular administration, selected fatty acid conjugates enhanced silencing in deep brain regions such as the striatum, whereas cholesterol conjugation impaired functional delivery despite increased CNS retention. Light-sheet microscopy showed restricted parenchymal penetration of cholesterol ASOs compared with broader but heterogeneous distribution of palmitic acid conjugate. Together, these findings demonstrate that lipid identity critically determines ASO efficacy, productive cellular uptake, and regional CNS engagement, emphasizing the need for context specific lipid design in ASO therapeutic development.

pharmacology and toxicology↗
bioRxiv2026

Novel Dissymmetric Ionizable Lipid-Assembled Lipid Nanoparticles for Delivery of Ferroptosis-Related siRNA in Diabetic Treatment

Small interfering RNA (siRNA) enables precise post-transcriptional gene silencing for refractory diseases, yet its clinical translation remains limited by the lack of safe and efficient delivery vectors. Inspired by the dissymmetric alkyl chain architecture of natural membrane phospholipids, we designed and synthesized 34 novel ionizable lipids with dissymmetric hydrophobic tails and formulated them into lipid nanoparticles (LNPs). Through systematic physicochemical and biological assessments, we established clear structure-activity relationships and identified two lead LNPs (O14-LNP, H18a-LNP) with superior endosomal escape capacity, enhanced in vivo gene silencing potency, and favorable biosafety relative to the clinical benchmark MC3-LNP. In both streptozotocin-induced and spontaneous db/db type 2 diabetes (T2D) mouse models, lead LNPs delivering ferroptosis-related siRNAs effectively ameliorated glucose and lipid metabolic disorders, restored islet function, and alleviated hepatic steatosis. This study not only lays a theoretical foundation for the rational design of novel ionizable lipids, but also validates the therapeutic potential of siRNA therapy targeting ferroptosis, providing a versatile delivery platform and targeted therapeutic strategy for the treatment of T2D.

pharmacology and toxicology↗
bioRxiv2018

Characterization of BSN175: A Drug to Treat Prader-Willi Syndrome

The purpose of this research is to choose the best analytical method for determining stability of BSN175. This research uses an accelerated stability study to compare the decomposed and stable drug using IR and 1H NMR spectroscopy. The Bootstrap Error-adjusted Single-sample Technique (BEST) was used to compare the effectiveness of these analytical methods and choose the best option for determining stability.

pharmacology and toxicology↗