Effect of long-term statin therapy on liver enzymes in diabetic patients Q. A. Qasim, A. S. Hillfy, K. A. Kadhim, H. A. Al-Hussaniy Regulatory Mechanisms in Biosystems, 2026 Statins are regularly prescribed to patients with type 2 diabetes mellitus (T2DM) to lower the risk of cardiovascular outcomes, although the risk of hepatotoxicity remains an issue. Our o bjective was to as sess the impact of statin -based long-term therapy in Iraqi adults with T2DM on liver enzymes and the factors that are related to elevated liver enzymes. Our research involved 280 adults with T2DM who received statins over 12 months, between January 2021 and Dece m ber 2025 . L iver enzyme abnormalities were defined in terms of local upper normal limits. Logistic regression was e m ployed in order to determine independent predictors of enzyme elevation. A subgroup of 96 patients had matched pre- and on statin liver tests. The mean ALT, AST and ALP, GGT and bilirubin values were or near the r eference range. The occu r rence rate of any liver enzyme elevation was 25.0% of all patients with only a few clinical ly significant elevations per parameter (less than 3%), while the incidence of acute liver failure or liver-related hospitalisation was nil. Data in multiva r iable analysis showed that NAFLD, obesity (BMI 30 kg/m2), HbA1c 9%, and high-intensity statin therapy were ind e pendently related to enzyme elevation and NAFLD had the most significant effect. In the matched group, the significant increase in ALT and AST observed after initiation of statin s was not significant. Long-term statin therapy in Iraqi patients with T2DM is generally hepatically safe. Liver enzyme abnormalities are driven mainly by underlying metabolic liver disease rather than statin exposure, supporting guideline-directed statin use with targeted follow-up liver function testing .
Development of a smart pillbox system to improve medication adherence Hanyakel Al_hussaniy, Amjad Ibrahim Oraibi Revista Colombiana De Ciencias Quimico Farmaceuticas Colombia, 2026 Introduction: The aging population and associated polypharmacy increase the risk of medication non-adherence, negatively affecting health and quality of life. Existing smart pillboxes help improve adherence but fall short in other aspects. Medication management requires training and education to be effective. Objective: This study was aimed at designing, developing and testing an original pillbox system that would automate the process of medicine preparation, dispensing and monitoring medication adherence and provide real-time feedback and cloud-based communication with caregivers and healthcare professionals. Methods: The prototype was built on a control system based on the Arduino platform, infrared sensors, GSM/Wi-Fi communication modules, and a real-time clock in the form of a modular prototype. The system was interconnected to a cloud network and an Android remote monitoring application. Laboratory validation of the prototype was done, Usability testing was conducted on the prototype with older people, and a field trial was conducted to estimate the improvement in adherence, reliability and user satisfaction. The quantitative measures of performance were dispensing accuracy, adherence rate, system-up-time and alert response-time. Results: Laboratory experiments showed the pill dispensing of 98.6%, sensor detection of 98 and continuous backup power of 5 hours in case of simulated outage. The results of usability testing on 17 participants contributed to the mean System Usability Scale (SUS) score of 84/100, which demonstrates that users are highly satisfied and find it easy to use it. Post-intervention adherence was 92.0% (SD 4.1%), compared to baseline 88.7% (SD 5.3%), absolute difference 3.3% (95% CI: 1.2–5.4). Response times of cloud synchronization were less than 5 seconds, and system uptime was 99.2%. Conclusion: The innovative pillbox system developed had potential to enhance medication adherence and reliability, decrease number of missed doses and provide the caregivers with reliable real time monitoring. Its great usability and technical stability promise to be a good assistive technology among the elderly and chronically ill patients. Further efforts in the field should be devoted to the extensive clinical validation, the long-term performance assessment, and the collaboration with electronic health records and AI-powered predictive analytics.
Comparative evaluation of renal function in patients using different antihypertensive drug classes Qutaiba Qasim, Ali Hadi, Kadhim Kadhim, Hany Al-Hussaniy Tropical Journal of Pharmaceutical Research, 2026 Purpose: To compare renal function in hypertensive adults treated with antihypertensive drug classes in a tertiary private clinic in Basra, Iraq.Method: A retrospective cohort comprised 450 adults with hypertension on stable therapy for 6 months from January 2024 to December 2025 in Al-Fayhaa Teaching Hospital, Basra, Iraq. Five monotherapy groups (60 patients each): angiotensin converting enzyme (ACE) inhibitor, angiotensin receptor blocker (ARB), calcium channel blocker (CCB), β-blocker, diuretic, and combination therapy (150 patients) comprising any two or more antihypertensive medications. Demographic and laboratory data were obtained. Analysis of variance and the Kh2 test were used to compare estimated glomerular filtration rate (eGFR), serum creatinine, and urine albumin-creatinine ratio (UACR).Results: The highest mean eGFR occurred in ACE-inhibitor and ARB-groups, and the lowest mean eGFR in β-blocker and diuretic groups. Non-RAAS monotherapy groups (Group 3 (calcium channel blockers), Group 4 (beta blockers)) were more common in terms of chronic kidney disease (CKD; eGFR < 60 mL/min/1.73 m2) and moderate-to-severe albuminuria. Diuretic and β-blocker monotherapy were associated with lower eGFR and a twofold increase in the odds of CKD and albuminuria in comparison with ACE inhibitor therapy after confounder adjustment. Still, ARB and RAAS-combination therapy had renal profiles comparable to ACE inhibitor therapy.Conclusion: The RAAS-blocking regimens comprising ARB and ACE inhibitors were associated with more favorable renal outcomes than non-RAAS monotherapies (CCB, β-blocker, and diuretic), supporting the prioritization of ACE inhibitors or ARBs as first-line therapy in hypertensive patients at renal risk.
Incidence of Hirschsprung Disease at the Central Pediatrics Teaching Hospital in Iraq: A Pathological Overview Ikram Fakhri Abed Al-Zughaibi, Nada K. Mehdi, Hany Akeel Al-hussaniy Endocrine Metabolic and Immune Disorders Drug Targets, 2026 Background: Hirschsprung disease (HD) is a congenital disorder associated with specific missense mutations in the RET proto-oncogene. This study aimed to demonstrate the incidence of Hirschsprung disease and its clinical and pathological aspects in an Iraqi pediatric cohort from a major referral hospital in Baghdad. Methods: A retrospective analysis was conducted over a ten-year period, reviewing the clinical and surgical records of patients diagnosed with Hirschsprung disease. Pathological sections were re-evaluated, and patient medical histories, prior surgeries, and other relevant clinical data were confirmed. Results: A total of 106 cases of Hirschsprung disease were identified. The mean age at diagnosis was 2.4 ± 3.0 years, with 40.6% of cases diagnosed within the first year of life. The male-to-female ratio was 2.6:1. The most commonly affected anatomical sites were the colon (35.8%) and rectum (23.6%). Pathological evaluation revealed the absence of ganglion cells in 57.5% of cases. Rectal biopsy was the most frequently performed diagnostic procedure (64.2%), and colon resection was required in 35.8% of cases. A significant association was found between disease presence and anatomical site involvement (P = 0.010) and surgical intervention (P = 0.046). Conclusion: The study highlights a male predominance in Hirschsprung disease, with the majority of cases diagnosed within the first year of life. The rectum and colon were the most commonly affected sites. Significant associations were observed between disease presence and anatomical site involvement, as well as surgical interventions, emphasizing the importance of early diagnosis and appropriate management strategies.
Data-Driven Toxicity Prediction: Advances in Machine Learning, Deep Learning, and Predictive Tools - A Systematic Review Hany Akeel Al-Hussaniy, Kadhim Adnan Ali, Samer Tareq Jasim, Ali Al-samydai Current Reviews in Clinical and Experimental Pharmacology, 2026 Introduction/Objective: High rate of attrition still inhibits drug discovery and development, with toxicity accounting for one of the primary causes of failure in preclinical and clinical development. This review summarizes Machine Learning (ML), Deep Learning (DL), and emerging post-deep learning strategies in drug discovery and environmental safety. Methods: Following PRISMA guidelines, a systematic search was conducted across PubMed, Web of Science, Scopus, and ScienceDirect for the years 2015–2025, yielding 1,020 articles. Additional records were obtained from Google Scholar and the reference lists of about 60 articles. The studies were included when they used ML/DL to predict toxicity, provided quantitative measures of performance (e.g., accuracy, AUC, F1-score), or when they described the predictive tools and platforms. Eligibility criteria were: the study was entirely experimental toxicology with no computational modeling of the study, lacked an adequate description of the methodology, or was in a non- English language. The last study count of the paper is 50 articles. Results: DL models like convolutional and graph neural networks are more effective in cases when the size of the datasets is large. Recent methods that address the problem of data scarcity are property augmentation, transfer learning, and semi-supervised learning. A number of web-based applications (e.g., ADMETlab 3.0, admetSAR 3.0, ProTox 3.0) have been published that allow using multi-endpoint prediction with different measures of accuracy and interpretability. Discussion: Traditional ML methods, particularly support vector machines and random forests, remain valuable for smaller datasets due to their robustness and interpretability. However, the adoption of deep learning architectures, such as convolutional and graph neural networks, has markedly improved predictive accuracy when applied to large and complex datasets. Conclusions: Data-driven methods have significantly advanced toxicity prediction, offering faster and more cost-effective tools compared with traditional assays. However, the field still faces challenges related to limited datasets, variable data quality, and a lack of mechanistic interpretability.
The Synergistic Effect of Nutlin-3a and a Wip1 Inhibitor in Inducing p53 Activity Ali Hikmat Alburghaif, Hany Akeel Al-Hussaniy, Ali Mahmoud Al-Samydai, Zainab Malik Saleem, Alhasan Ali Jabbar Current Molecular Medicine, 2026 Introduction: The p53 protein plays a major role in maintaining genome stability as well as the response of cells to stress. One of the principal things that regulates p53 is MDM2, and the way it interacts with p53 is of great significance in the degradation of p53. This dephosphorylation of p53 by Wip1 increases its affinity to MDM2, which causes p53 degradation. Wip1 is used to increase the growth of tumors by undermining the p53 pathway. However, the active form of p53 can be retained with the help of preventing Wip1, and this fact makes it useful as a target of cancer treatment. An ever-increasing body of preclinical evidence suggests the possibility that Wip1 inhibitors would be used alongside potent MDM2 inhibitors to enhance p53 activity and enhance treatment outcomes. The purpose of the review was to examine studies pertaining to the action of a Wip1 inhibitor and Nutlin-3a in order to induce p53 functionality. Method: We searched Google Scholar, PubMed, and other search engines using such terms as MDM2 inhibitors, Wip1 inhibitors, and Nutlin. Newer articles published after 2020 were chosen to ensure that the recent findings are included. Results: Wip1, an attractive antineoplastic target to control the p53 pathway, is a dephosphorylator of p53 at serine-15. Nutlin-3a with a Wip1 inhibitor appears to act synergistically to push p53 half-maximal inhibitory concentrations (IC50) into the low micromolar range. This combination greatly stimulates downstream p53-dependent response, which leads to a strong reduction of cell proliferation. Discussion: We find that MDM2 inhibitors in combination with Wip1 inhibitors are synergistic in stimulating p53 activity. The results emphasize the need to use a combination of p53 induction and the inactivation of its suppressors in the treatment of cancer. Conclusion: As p53 is the most commonly mutated gene across a broad range of tumors, enhancing p53 activity is a prerequisite for achieving potent therapeutic effects. We envision that combination therapies involving Nutlin-3a, Wip1 inhibitors, and other effective cancer treatments may synergistically improve p53 activity and enhance therapeutic outcomes.
Targeted Nanomedicine Approaches for Precision Cancer Therapy Ali Mahmoud Al-Samydai, Israa A. Almastafa, Muntadher Abdulsalam A. Al. Alrabeeah, Alhasan Ali Jabbar, Hany A. Al-hussaniy Research Journal of Pharmacy and Technology, 2026 Background: Chemotherapy and radiation therapy are two examples of the many serious drawbacks of traditional cancer therapies, including their systemic toxicity and lack of cancer cell selectivity. Drug delivery has been transformed by the development of nanotechnology, which has made it possible to create nanoparticles with exact control over their size, shape, and surface characteristics. By functionalizing these nanoparticles with targeting ligands, it is possible to maximize medication accumulation at the tumor location while reducing off-target effects by selectively binding to cancer cell receptors. The object of this review is to conclude and summarize the updated information targeted nanomedicine and it’s its role in cancer drug discovery and treatment. Method: A comprehensive literature search was conducted using electronic databases to identify relevant studies published in peer-reviewed journals. The search terms included "targeted nanomedicine," "precision cancer therapy," "nanoparticle drug delivery," and related keywords. The selected articles were critically evaluated to extract key findings and insights into targeted nanomedicine approaches for cancer therapy. Result: The review highlights the remarkable progress made in the development of targeted nanomedicine platforms for precision cancer therapy. These include nanoparticle formulations for targeted delivery of chemotherapeutic drugs, nucleic acid-based therapeutics, and imaging agents. Moreover, innovative strategies such as stimuli-responsive nanoparticles and combination therapy approaches have shown great potential in overcoming drug resistance and improving treatment efficacy. Conclusion: Targeted nanomedicine holds great promise for revolutionizing cancer therapy by enabling the precise delivery of therapeutic agents to tumor tissues while minimizing systemic side effects. Continued research efforts aimed at optimizing nanoparticle design, understanding tumor biology, and translating preclinical findings into clinical applications are crucial for realizing the full potential of targeted nanomedicine in precision cancer therapy.
SERUM VITAMIN B12, FOLIC ACID, HOMOCYSTEINE, AND GLYCEMIC CONTROL MARKERS IN PATIENTS WITH TYPE 2 DIABETES BY METFORMIN AND OTHER ORAL ANTIDIABETIC MEDICATIONS Georgian Medical News, 2025
MODELING DRUG–ORGAN INTERACTIONS AND OPTIMIZING IMMUNOTHERAPY: A QUANTITATIVE SYSTEMS PHARMACOLOGY AND ODRONEXTAMAB DYNAMICS Georgian Medical News, 2025
CORRELATION OF FETAL MEASUREMENTS WITH GESTATIONAL AGE IN 144 ABORTED FETUSES: A CROSS-SECTIONAL HOSPITAL-BASED OBSERVATIONAL STUDY Georgian Medical News, 2025
