Innovating Thiopurine Therapeutic Drug Monitoring: A Systematic Review and Meta-Analysis on DNA-Thioguanine Nucleotides (DNA-TG) as an Inclusive Biomarker in Thiopurine Therapy.

BACKGROUND AND OBJECTIVE: Thioguanine (TG), azathioprine (AZA), and mercaptopurine (MP) are thiopurine prodrugs commonly used to treat diseases, such as leukemia and inflammatory bowel disease (IBD). 6-thioguanine nucleotides (6-TGNs) have been commonly used for monitoring treatment. High levels of 6-TGNs in red blood cells (RBCs) have been associated with leukopenia, the cutoff levels that predict this side effect remain uncertain. Thiopurines are metabolized and incorporated into leukocyte DNA. Measuring levels of DNA-incorporated thioguanine (DNA-TG) may be a more suitable method for predicting clinical response and toxicities such as leukopenia. Unfortunately, most methodologies to assay 6-TGNs are unable to identify the impact of NUDT15 variants, effecting mostly ethnic populations (e.g., Chinese, Indian, Malay, Japanese, and Hispanics). DNA-TG tackles this problem by directly measuring thioguanine in the DNA, which can be influenced by both TPMT and NUDT15 variants. While RBC 6-TGN concentrations have traditionally been used to optimize thiopurine therapy due to their ease and affordability of measurement, recent developments in liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques have made measuring DNA-TG concentrations in lymphocytes accurate, reproducible, and affordable. The objective of this systematic review was to assess the current evidence of DNA-TG levels as marker for thiopurine therapy, especially with regards to NUDT15 variants. METHODS: A systematic review and meta-analysis were performed on the current evidence for DNA-TG as a marker for monitoring thiopurine therapy, including methods for measurement and the illustrative relationship between DNA-TG and various gene variants (such as TPMT, NUDT15, ITPA, NT5C2, and MRP4). PubMed and Embase were systematically searched up to April 2024 for published studies, using the keyword "DNA-TG" with MeSH terms and synonyms. The electronic search strategy was augmented by a manual examination of references cited in articles, recent reviews, editorials, and meta-analyses. A meta-analysis was performed using R studio 4.1.3. to investigate the difference between the coefficients (Fisher's z-transformed correlation coefficient) of DNA-TG and 6-TGNs levels. A meta-analysis was performed using RevMan version 5.4 to investigate the difference in DNA-TG levels between patients with or without leukopenia using randomized effect size model. The risk of bias was assessed using the Newcastle-Ottowa quality assessment scale. RESULTS: In this systematic review, 21 studies were included that measured DNA-TG levels in white blood cells for either patients with ALL (n = 16) or IBD (n = 5). In our meta-analysis, the overall mean difference between patients with leukopenia (ALL + IBD) versus no leukopenia was 134.15 fmol TG/µg DNA [95% confidence interval (CI) (83.78-184.35), P < 0.00001; heterogeneity chi squared of 5.62, I2 of 47%]. There was a significant difference in DNA-TG levels for patients with IBD with and without leukopenia [161.76 fmol TG/µg DNA; 95% CI (126.23-197.29), P < 0.00001; heterogeneity chi squared of 0.20, I2 of 0%]. No significant difference was found in DNA-TG level between patients with ALL with or without leukopenia (57.71 fmol TG/µg DNA [95% CI (- 22.93 to 138.35), P < 0.80]). DNA-TG monitoring was found to be a promising method for predicting relapse rates in patients with ALL, and DNA-TG levels are likely a better predictor for leukopenia in patients with IBD than RBC 6-TGNs levels. DNA-TG levels have been shown to correlate with various gene variants (TPMT, NUDT15, ITPA, and MRP4) in various studies, points to its potential as a more informative marker for guiding thiopurine therapy across diverse genetic backgrounds. CONCLUSIONS: This systematic review strongly supports the further investigation of DNA-TG as a marker for monitoring thiopurine therapy. Its correlation with treatment outcomes, such as relapse-free survival in ALL and the risk of leukopenia in IBD, underscores its role in enhancing personalized treatment approaches. DNA-TG effectively identifies NUDT15 variants and predicts late leukopenia in patients with IBD, regardless of their NUDT15 variant status. The recommended threshold for late leukopenia prediction in patients with IBD with DNA-TG is suggested to be between 320 and 340 fmol/µg DNA. More clinical research on DNA-TG implementation is mandatory to improve patient care and to improve inclusivity in thiopurine treatment.

Numerical analysis of permeate flux in reverse osmosis by varying strand geometry.

In regions with limited potable water availability, membrane desalination is being employed to filter water using a pressure-driven approach. Because of the high energy consumption required to produce the pressure differential needed for this method, researchers have been trying different geometric designs of spacer filaments to enhance the amount of permeate flux in terms of energy utilization. The purpose of spacer filaments is to support membranes structurally and induce turbulent mixing in spiral wound membrane desalination. In this paper, the improvement of mass transfer in desalination driven by reverse osmosis has been studied using Computational Fluid Dynamics (CFD) with the introduction of spiral wound membranes that are lined with spacer filaments in a zig-zag formation having alternating diameters for strands. The fluid flow characteristics for a 2-dimensional geometric model were resolved using the open-source program OpenFOAM by changing the Reynolds number to just before the inception of instabilities. Ratios of alternate strand diameters were also varied between one and two. Based on a detailed analysis of velocity contours, pressure distribution, wall shear stresses, and steady-state vortex systems, the research findings offer guidance for employing alternating strand design in zig-zag formation for optimum mass transfer and minimal pressure drop when accounting for concentration polarization.

Unrealized potential of drug repositioning in europe during COVID-19 and beyond: a physcian's perspective.

Drug repositioning is the scientific strategy of investigating existing drugs for additional clinical indications. The advantages of drug repositioning are that it benefits patients and that it adds new indications to existing drugs for lower costs compared to de novo drug development. Clinical research groups recognizing efficacy of these "old" drugs for a new indications often face an uphill struggle due to a lack of funding and support because of poor structural and regulatory support for clinical drug development. The current framework for drug repositioning allows "venture capital" companies to abuse loopholes in the legislation to gain long-term market authorization among with excessive high pricing. A new regulatory framework is needed to prevent abuse of the legislation and promote clinical investigator-driven drug repositioning. The COVID-19 pandemic has boosted funding and regulatory support for drug repositioning. The lessons learned from the COVID-19 pandemic should be implemented in a new clear blueprint for drug repositioning. This blueprint should guide clinicians through legislation for drug repositioning in the EU. This review summarizes the routes for registration and discusses the current state of drug repositioning in Europe.

Establishing a many-cytokine signature via multivariate anomaly detection.

Establishing a cytokine signature associated to some medical condition is an important task in immunology. Increasingly, large numbers of cytokines are used for signatures, via lists of reference ranges for each individual cytokine or ratios of cytokines. Here we argue that this common approach has weaknesses, especially when many different cytokines are analysed. Instead, we propose that establishing signatures can be framed as a multivariate anomaly detection problem, and hence exploit the many statistical methods available for this. In this framework, whether or not a given subject's profile matches the cytokine signature of some condition is determined by whether or not the profile is typical of reference samples of that condition, as judged by an anomaly detection algorithm. We examine previously published cytokine data sets associated to pregnancy complications, brain tumours, and rheumatoid arthritis, as well as normal healthy control samples, and test the performance of a range of anomaly detection algorithms on these data, identifying the best performing methods. Finally, we suggest that this anomaly detection approach could be adopted more widely for general multi-biomarker signatures.

On using experimentally estimated wall shear stresses to validate numerically predicted results.

The objective of this investigation was to assess the use of experimentally estimated wall shear stresses to validate numerically predicted results. The most commonly cited haemodynamic factor implicated in the disease initiation and proliferation processes at graft/artery junctions is wall shear stress (WSS). WSS can be determined from the product of the viscosity of the fluid and the wall shear rate. Numerically, the wall shear rate is predicted using velocity values stored in the computational cell near the wall and assuming zero velocity at the wall. Experimentally, the wall shear rate is estimated by applying a curve-fit to near-wall velocity measurements and evaluating the shear rate at a specific distance from the wall. When estimating the wall shear rate from the laser Doppler anemometry (LDA) point velocity measurements, large differences between the experimentally estimated and numerically predicted WSSs were introduced. It was found that the estimated WSS distributions from the experimental results are highly dependent on the curve-fitting method used to calculate the wall shear rate. However, the velocity profiles for both the experimental and numerical investigations show extremely good comparison. It is concluded that numerical models should be validated using unprocessed LDA point velocity measurement and not estimated WSS values.