Identification of the key target profiles underlying the drugs of narrow therapeutic index for treating cancer and cardiovascular disease

Therapeutic and diagnostic applications of carbon nanotubes in cancer: recent advances and challenges

Carbon nanotubes (CNTs) are allotropes of carbon, composed of carbon atoms forming a tube-like structure. Their high surface area, chemical stability, and rich electronic polyaromatic structure facilitate their drug-carrying capacity. Therefore, CNTs have been intensively explored for several biomedical applications, including as a potential treatment option for cancer. By incorporating smart fabrication strategies, CNTs can be designed to specifically target cancer cells. This targeted drug delivery approach not only maximizes the therapeutic utility of CNTs but also minimizes any potential side effects of free drug molecules. CNTs can also be utilised for photothermal therapy (PTT) which uses photosensitizers to generate reactive oxygen species (ROS) to kill cancer cells, and in immunotherapeutic applications. Regarding the latter, for example, CNT-based formulations can preferentially target intra-tumoural regulatory T-cells. CNTs also act as efficient antigen presenters. With their capabilities for photoacoustic, fluorescent and Raman imaging, CNTs are excellent diagnostic tools as well. Further, metallic nanoparticles, such as gold or silver nanoparticles, are combined with CNTs to create nanobiosensors to measure biological reactions. This review focuses on current knowledge about the theranostic potential of CNT, challenges associated with their large-scale production, their possible side effects and important parameters to consider when exploring their clinical usage.

An extended Bayesian semi-mechanistic dose-finding design for phase I oncology trials using pharmacokinetic and pharmacodynamic information

We propose a model-based, semi-mechanistic dose-finding (SDF) design for phase I oncology trials that incorporates pharmacokinetic/pharmacodynamic (PK/PD) information when modeling the dose-toxicity relationship. This design is motivated by a phase Ib/II clinical trial of anti-CD20/CD3 T cell therapy in non-Hodgkin lymphoma patients; it extends a recently proposed SDF model framework by incorporating measurements of a PD biomarker relevant to the primary dose-limiting toxicity (DLT). We propose joint Bayesian modeling of the PK, PD, and DLT outcomes. Our extensive simulation studies show that on average the proposed design outperforms some common phase I trial designs, including modified toxicity probability interval (mTPI) and Bayesian optimal interval (BOIN) designs, the continual reassessment method (CRM), as well as an SDF design assuming a latent PD biomarker (SDF-woPD), in terms of the percentage of correct selection of maximum tolerated dose (MTD) and average number of patients allocated to MTD, under a variety of dose-toxicity scenarios. When the working PK model and the class of link function between the cumulative PD effect and DLT probability is correctly specified, the proposed design also yields better estimated dose-toxicity curves than CRM and SDF-woPD. Our sensitivity analyses suggest that the design's performance is reasonably robust to prior specification for the parameter in the link function, as well as misspecification of the PK model and class of the link function.

Impact of clinical pharmacist interventions on economic outcomes in a cardiology setting in Qatar

We sought to investigate the economic impact of preventing adverse events in a cardiology setting in Qatar as an effect of the clinical pharmacist as an intervention. This is a retrospective study of interventions by clinical pharmacists within an adult cardiology setting in a public healthcare setting (i.e Hamad Medical Corporation). The study included interventions that took place in March 2018, July 15, 2018-August 15, 2018, and January 2019. The economic impact was measured via calculating the total benefit, defined as the sum of the cost savings and the cost avoidance. Sensitivity analyses were adopted to confirm the robustness of the results. The pharmacist intervened in 262 patients, resulting in 845 interventions, with appropriate therapy (58.6%) and dosing/administration (30.2%) being the most frequent categories of reported interventions. Cost savings and cost avoidance resulted in QAR-11,536 (USD-3,169) and QAR1,607,484 (USD 441,616), respectively, yielding a total benefit of QAR1,595,948 (USD438,447) per three months and QAR6,383,792 (USD1,753,789) per a year.

Effect of concomitant oral administration of ethanol on the pharmacokinetics of nicardipine in rats

Ethanol intake can alter pharmacokinetics by increasing the solubility or enhancing the absorption of concomitant drugs. Here, a selective, sensitive and reproducible high-performance liquid chromatography-tandem mass spectrometry method for the quantitative analysis of nicardipine in rat plasma was developed using simple protein precipitation. The calibration curve was linear over a concentration range of 1-2,000 ng/ml (r²  > 0.998). Accuracy ranged from 93.4 to 112.2% and precision was within 12.1% from three independent analytical batches. Stable conditions for the quantification of nicardipine in rat plasma were established in various conditions, including sample storage and handling. The matrix effect was negligible, and recovery was consistent at three different levels of quality control sample. The method was applied to assessment for the effect of ethanol on the pharmacokinetics of nicardipine in rats. The oral bioavailability of nicardipine was increased from 5.4 to 9.4% in Sprague-Dawley rats by concomitant oral administration of ethanol whereas the half-life was not altered. The findings indicated that concomitant ethanol intake can increase systemic drug exposure by increasing gastrointestinal absorption, especially poorly soluble drugs. This study provides an insight for further investigation of the alteration of the pharmacological effect of poorly soluble drugs owing to ethanol intake.

VARIDT 2.0: structural variability of drug transporter

The structural variability data of drug transporter (DT) are key for research on precision medicine and rational drug use. However, these valuable data are not sufficiently covered by the available databases. In this study, a major update of VARIDT (a database previously constructed to provide DTs' variability data) was thus described. First, the experimentally resolved structures of all DTs reported in the original VARIDT were discovered from PubMed and Protein Data Bank. Second, the structural variability data of each DT were collected by literature review, which included: (a) mutation-induced spatial variations in folded state, (b) difference among DT structures of human and model organisms, (c) outward/inward-facing DT conformations and (d) xenobiotics-driven alterations in the 3D complexes. Third, for those DTs without experimentally resolved structural variabilities, homology modeling was further applied as well-established protocol to enrich such valuable data. As a result, 145 mutation-induced spatial variations of 42 DTs, 1622 inter-species structures originating from 292 DTs, 118 outward/inward-facing conformations belonging to 59 DTs, and 822 xenobiotics-regulated structures in complex with 57 DTs were updated to VARIDT (https://idrblab.org/varidt/ and http://varidt.idrblab.net/). All in all, the newly collected structural variabilities will be indispensable for explaining drug sensitivity/selectivity, bridging preclinical research with clinical trial, revealing the mechanism underlying drug-drug interaction, and so on.

Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents

Drug discovery relies on the knowledge of not only drugs and targets, but also the comparative agents and targets. These include poor binders and non-binders for developing discovery tools, prodrugs for improved therapeutics, co-targets of therapeutic targets for multi-target strategies and off-target investigations, and the collective structure-activity and drug-likeness landscapes of enhanced drug feature. However, such valuable data are inadequately covered by the available databases. In this study, a major update of the Therapeutic Target Database, previously featured in NAR, was therefore introduced. This update includes (a) 34 861 poor binders and 12 683 non-binders of 1308 targets; (b) 534 prodrug-drug pairs for 121 targets; (c) 1127 co-targets of 672 targets regulated by 642 approved and 624 clinical trial drugs; (d) the collective structure-activity landscapes of 427 262 active agents of 1565 targets; (e) the profiles of drug-like properties of 33 598 agents of 1102 targets. Moreover, a variety of additional data and function are provided, which include the cross-links to the target structure in PDB and AlphaFold, 159 and 1658 newly emerged targets and drugs, and the advanced search function for multi-entry target sequences or drug structures. The database is accessible without login requirement at: https://idrblab.org/ttd/.