Author Archives: administrare

Precision oncology: A narrative review of recent developments and challenges

Carolyn Muruthi1, Japheth Wambani Rapando2

1. Department of Biomedical Sciences, Medical College, Aga Khan University, Nairobi, Kenya
2. Department of Medical Microbiology and Parasitology, School of Medicine, Moi University, Eldoret, Kenya

DOI: 10.2478/amma-2025-0056

The mainstay generic therapies of cancer including chemotherapy, are partly effective in a subset of the patient population due to the complexity and heterogenous nature of the disease. Nevertheless, the inherent variability of cancer has steered cancer therapy towards the concept of precision medicine. The approach focuses on matching effective and accurate treatment on the genetic profile of a patient and different unique characteristics that distinguishes one patient from another. Currently, precision oncology has been driven by various innovations including liquid biopsy, next generation sequencing (NGS) and multi-omics integration. Recent advances in next generation-based sequences have enabled the analysis of analytes including circulating DNA and genomic DNA. Liquid biopsy has enabled minimal invasion alternative and real-time monitoring of tumour dynamics and analysis of treatment responses. Moreover, emerging technologies including artificial intelligence and nanotechnology has enhanced the sensitivity of liquid biopsy. Similarly, multi-omics integration offers insights into the interactions between transcriptomic, proteomic, epigenomic and genomic enabling the unravelling the complex molecular mechanism driving carcinogenesis. These advances have resulted in the discovery of novel biomarkers and diverse therapeutic targets for different types of cancers. However, despite the promising advancements, challenges remain, such as concerns on data privacy, need for clinical validation and computational limitations. Ongoing research is, therefore, critical to embrace precision oncology in routine clinical care.

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Development and optimization of an LC-MS method for the separation of nitrosamine impurities

Alina Balint1, Lénárd Farczádi2, Anca Gabriela Cârje1, Valentin Ion1

1. Analytical Chemistry and Drug Analysis Department, Faculty of Pharmacy, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Targu Mures, Romania
2. Center for Advanced Medical and Pharmaceutical Research, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Targu Mures, Romania

DOI: 10.2478/amma-2025-0055

Objective: This research foucuses on the development of a liquid chromatographic method for the rapid and reliable separation and identification of major nitrosamine impurities, ensuring both short analysis time and adequate resolution. Given the toxicological relevance of nitrosamines, their occurrence in pharmaceutical formulations has raised substantial concerns, leading to the reassessment of multiple drug products. In response, reverse-phase HPLC with UV detection and LC-MS techniques have been widely applied as powerful analytical tools for their detection and control.
Methods: The following impurities of the N-nitrosamine class are separated and identified by the LC-MS technique: NDMA (N-nitrosodimethylamine), NDEA (N-nitrosodiethylamine), NMEA (N-nitrosomethylethylamine) NDIPA (N-nitrosodiisopropylamine), NDBA (N-nitrosodibutylamine) NPIP (N-nitrosopiperidine). A standard solution of nitrosamines mix was prepared and subsequently diluted in methanol to achieve a final concentration of 20 µg/mL for each compound. The analysis was performed using a UHPLC chromatography system Flexar FX10 (Perkin Elmer) with MS QTOF (AB Sciex TripleTOF4600), Phenomenex Luna Omega 3 C18 (150×4.6mm, 3μm) column, column temperature 450C, mobile phase methanol and formic acid 0.1% in ultrapure water, gradient elution, flow 0.45 mL/min., injected volume 5 µl. The proposed LC-MS conditions are significantly improved compared to the European Pharmacopoeia recommendations for N-Nitrosamines impurities in active substances analysis.
Results: Based on the mass fragmentation profiles of the six investigated nitrosamines, chromatographic separation was successfully accomplished in less than 25 minutes, with the elution sequence established as follows: NDMA, NMEA, NDEA, NPIP, NDIP, NDBA.
Conclusions: The development of optimal chromatographic conditions allows further separation and identification of nitrosamines impurities in pharmaceutical products.

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A data-driven approach to PCOS Diagnosis: Systematic review of machine learning applications in reproductive health

Akshay V P1, Ritvik Sriram2, Keerthana3, Delna N S4, Pranav Verma5, Bhanu Verma6, Mansi Trivedi7, Shanmukhi Mogalipuvvu8, Sasikala Kathiresan9, Lalitha Soumya Johnson10, Bhavit Bansal11, Muhammed Asif12, Shubhrit Shrivastava13, Liya Sebastian14

1. Mansarovar Global University, Bhopal, India
2. Tirunelveli Medical College, Tirunelveli, Tamil Nadu, India
3. IQVIA Bengaluru, Karnataka, India
4. BioDeskINDIA Labs, Bhopal, India
5. Chitkara college of pharmacy, Chitkara University, Rajpura, India
6. University School of Pharmaceutical Sciences, Rayat Bahra University, Sahauran, India
7. Humera Khan College of Pharmacy, University of Mumbai, Mumbai, India
8. Mamata academy of medical sciences, Hyderabad, Telangana, India
9. All India Institute of Medical Sciences, Madurai, India
10. Dr. Janaki Ammal Campus, Kannur University, Kannur, Kerala, India
11. Central Council for Research in Yoga and Naturopathy, Delhi, India
12. Centennial College, Toronto, Canada
13. BioDeskINDIA Labs, Bhopal, India
14. Nikola Tesla STEM High School, Redmond, USA

DOI: 10.2478/amma-2025-0054

Background and aim: Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine disorder in reproductive-aged women, characterized by hormonal imbalances, anovulation, and metabolic abnormalities. This systematic review aims to evaluate the effectiveness, types, and diagnostic performance of ML algorithms applied in PCOS detection and classification, and to identify the most frequently used input features and methodological challenges in existing studies.
Methods: A systematic search was conducted across scholarly databased, but not limited to PubMed, Scopus, and Google Scholar for studies published between 2014 and 2024 using keywords related to PCOS and machine learning. Inclusion criteria focused on original, peer-reviewed studies applying ML models for PCOS diagnosis. Data were extracted on model type, input features, diagnostic accuracy, and study design. Quality assessment was performed using the PROBAST tool.
Results: Out of 450 identified studies, 34 met the inclusion criteria and passed the quality assessment. Supervised learning models such as Random Forest, SVM, and XGBoost showed high accuracy (up to 99%). Deep learning approaches, particularly Convolutional Neural Networks (CNNs), achieved accuracies between 95% and 99.89% in analyzing ultrasound images. Hybrid models integrating clinical and imaging data further enhanced performance. Common input features included BMI, LH/FSH ratio, AMH, and ultrasound-based ovarian morphology. However, few studies validated models on external datasets, and input feature selection lacked standardization.
Conclusion: Machine learning models such as supervised, deep learning, and hybrid approaches show strong potential in improving PCOS diagnosis by identifying complex patterns across multi-dimensional datasets. Challenges such as limited generalizability and data standardization remain, therefore future studies should focus on developing explainable ML tools, validating models in clinical settings, and leveraging diverse data types for robust, personalized PCOS diagnosis.

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Preparation and evaluation of self-assembling mixed polymeric nanomicelles drug delivery system for canagliflozin

Nizar Awish Jassem

Department of Pharmaceutics, College of Pharmacy, Ashur University, Baghdad, Iraq

DOI: 10.2478/amma-2025-0053

Background and objective: Mixed polymeric nanomicelles are nanoscale structures produced by the self-assembly of two or more amphiphilic polymers in an aqueous solution. These nanomicelles are of great interest in a variety of fields, including medication delivery, due to their capacity to encapsulate both hydrophobic and hydrophilic drugs, as well as their stability and capacity to enhance the solubility and bioavailability of poorly water-soluble medications. Our study focuses on preparing and evaluating mixed polymeric self-nanomicellizing solid dispersions (MP-SNMSD) of Canagliflozin (CFZ), a sodium-glucose co-transporter-2 inhibitor used in managing Type 2 Diabetes Mellitus (T2DM). Its poor aqueous solubility and bioavailability remain significant challenges.
Materials and methods: The solvent evaporation technique was employed to create CFZ-MP-SNMSDs using Soluplus® as a main carrier and Solutol® HS15 or D-α-tocopherol polyethylene glycol succinate (TPGS) as the second carrier.
Results: Ten formulations with high drug loading and stability are prepared. Optimized CFZ-MP-SNMSD formula, consisting of 1:1:4 of CFZ: Solutol® HS15: Soluplus®, exhibited reduced particle size (68.44 nm) and improved dissolution rates under non-sink conditions in phosphate buffer pH 6.8, with a 58% release in 60 minutes compared to 18% for the pure drug. X-ray diffraction revealed a transition of CFZ to an amorphous state in an optimized CFZ-MP-SNMSD formula, enhancing solubility. The MP-SNMSD formulations demonstrated significant enhancements in solubility and dissolution efficiency, which will improve the oral bioavailability of CFZ.
Conclusion: These findings suggest that MP- SNMSD formulations represent a promising approach to overcoming the limitations of CFZ, providing a foundation for more effective oral drug delivery systems of hydrophobic drugs and improving therapeutic outcomes.

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Maternal car accidents during pregnancy and their impact on newborns

Claudia Kosztelnik1, Manuela Camelia Cucerea2,3

1. Neonatology Department, Bistrita Emergency County Clinical Hospital, Bistrita, Romania
2. Neonatology Department, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Romania
3. Neonatology Department, Mures Clinical County Hospital, Targu Mures, Romania

DOI: 10.2478/amma-2025-0047

Introduction: Car accidents are among the most common causes of fetal trauma during pregnancy. The most frequent maternal complications include placental abruption, uterine rupture, and hypovolemic shock, while fetal complications include premature birth, cranial injuries, skull fractures, and even death.
Objective: To examine how car accidents affect pregnant women and their newborns.
Methods: Three cases of newborns delivered by mothers involved in car accidents during pregnancy were analyzed. The data were collected from the medical records of the neonatology department.
Results: These three clinical cases demonstrate the significant impact of maternal trauma from car accidents on perinatal outcomes and neonatal development, with a wide range of clinical manifestations, from transient neonatal complications to neonatal death. Properly using seatbelts during pregnancy is essential to prevent injuries to both the mother and the fetus.
Conclusions: Maternal motor vehicle accidents can have severe and diverse consequences for newborns, ranging from transient complications to congenital malformations and neonatal death. Proper and correct use of seatbelts during pregnancy is a critical preventive measure to reduce maternal and fetal injuries. Immediate neonatal resuscitation and thorough post-trauma evaluation, are essential for improving outcomes. Long-term pediatric monitoring is recommended due to the risk of delayed complications. Further research is needed to develop standardized protocols for trauma management in pregnancy and to better understand the effects of intrauterine trauma on fetal development.

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Locum model for pharmacists: A quantitative research study

Andrei Șuteu-Albu, Marius Călin Cherecheș

George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Romania

DOI: 10.2478/amma-2025-0052

Objective: This study aimed to explore the feasibility and impact of implementing locum pharmacist models in Romanian community pharmacies, in the context of growing workforce shortages and operational challenges in the pharmaceutical sector.
Methods: A cross-sectional survey was conducted using a 15-question structured questionnaire distributed via a national locum platform and professional forums. A total of 116 valid responses were collected. The questionnaire covered demographics, professional preferences, and financial expectations. Data were analysed using statistical software to identify correlations between variables such as professional experience, interest in locum work, and expected remuneration.
Results: Respondents represented a diverse age and experience range, with the majority having between 10 and 20 years of professional experience. Community pharmacy was the dominant area of current employment (76%). Most pharmacists reported difficulty in finding replacements during leave, particularly in rural areas. Over half expressed willingness to work locum shifts if adequately compensated, preferring hourly rates 50% to 100% higher than standard wages. Data indicated a correlation between years of experience and higher salary expectations. The study highlighted distinct professional preferences between administrative and patient-facing roles and emphasised the stress associated with excessive workloads and reduced rest periods.
Conclusions: Locum work presents a viable solution to mitigate staffing shortages in Romanian pharmacies, offering flexibility and increased earning potential for pharmacists. However, challenges such as professional isolation, inconsistency in pharmacy systems, and lack of formal support must be addressed to optimise implementation. Integration strategies and legislative clarity will be essential for the long-term success of locum models in the pharmaceutical sector.

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Quantitative Real-Time PCR testing in the control of hepatitis B and C: Progress and challenges towards eradication by 2030

Iulia Patrascu

Clinical County Emergency Hospital Bistrita-Nasaud, Bistrița, Romania

DOI: 10.2478/amma-2025-0046

Worldwide, chronic hepatitis B and C infections remain a significant public health challenge, causing millions of cases of liver disease globally.
The objective of this article is to highlight the need for testing and monitoring hepatitis B and C virus infections using Real-Time PCR, as well as to analyze the implementation of strategies for the eradication of hepatitis in accordance with WHO targets for 2030.
This narrative review highlights the necessity, performance, advantages, limitations, and challenges of implementing Real-Time PCR testing in clinical practice and public health policies for hepatitis B and C.
The results show that Real-Time PCR has superior sensitivity and specificity in the early detection of active infection and monitoring of viral load, facilitating optimal therapeutic management. Serological testing retains its essential role in initial screening, identifying exposure to viruses. Vulnerable groups, including hemodialysis patients, people who inject drugs, HIV-positive patients, healthcare workers, and marginalized populations, have increased prevalence and require prioritization in testing. The main limitations reported include unequal access to PCR technology and potential technical errors. Proposed strategies for improving testing include expanding access to molecular techniques, awareness campaigns, standardization of protocols, and international collaborations to support screening and treatment.
The conclusions emphasize that integrating serological testing with Real-Time PCR and focusing on vulnerable groups are crucial for achieving the objectives.

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C-reactive protein/albumin ratio as an early indicator of severe acute pancreatitis: A preliminary study

Crina Fofiu1,2, Alina Boeriu1, Laura Nat2

1. Gastroenterology Department, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Targu Mures, Romania
2. Internal Medicine Department, Bistrița Clinical County Emergency Hospital, Bistrița, Romania

DOI: 10.2478/amma-2025-0049

Objective: To evaluate the prognostic accuracy of the C-reactive protein (CRP)/albumin ratio in predicting severe acute pancreatitis (SAP) and its correlation with clinical complications.
Methods: This retrospective observational study included 40 adult patients diagnosed with acute pancreatitis between January and August 2024. Patients were categorized by severity using the Revised Atlanta Classification into moderately severe or severe groups. Laboratory data, clinical characteristics, and imaging findings were compared. Receiver operating characteristic (ROC) analysis with Youden’s Index evaluated the CRP/albumin ratio predictive performance and logistic regression identified independent predictors of SAP.
Results: The CRP/albumin ratio was significantly higher in SAP patients (median 5.0 [IQR 0.93–12.62]) compared to non-SAP (1.58 [IQR 0.28–8.6], p = 0.0187). ROC analysis showed an area under the curve (AUC) of 0.809 for the CRP/albumin ratio, superior to CRP alone (AUC 0.479) and comparable to the Ranson score (AUC 0.88). An optimal cut-off value of 4.22 provided 76.9% sensitivity and 85.2% specificity. Multivariable logistic regression identified absence of intestinal transit (p = 0.033) and splenic vein thrombosis (p = 0.026) as independent predictors of SAP. The CRP/albumin ratio correlated significantly with both these complications.
Conclusions: The CRP/albumin ratio is a valuable, non-invasive, and readily available prognostic marker for early identification of severe acute pancreatitis. Its predictive accuracy is comparable to established scoring systems and may aid in triage and clinical decision-making.

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Challenges in the management of a preterm neonate with respiratory distress and pneumothorax: A case report

Mihaela Maria Celsie1, Manuela Cucerea2,3

1. Bistrita Emergency County Clinical Hospital, Bistrita, Romania
2. Neonatology Department, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, Romania
3. Neonatology Department, Mures Clinical County Hospital, Targu Mures, Romania

DOI: 10.2478/amma-2025-0048

Introduction: Pneumothorax is a potentially life-threatening complication in preterm neonates, frequently associated with respiratory distress syndrome (RDS). Prompt diagnosis and individualized respiratory support are essential to avoid invasive interventions.
Objective: To describe the successful conservative management of a preterm neonate with respiratory distress syndrome complicated by pneumothorax and congenital infection, emphasizing the role of early respiratory support and infection control.
Methods: A male infant was born prematurely with clinical signs of systemic inflammation and respiratory distress. Initial management in the delivery room included thermal stabilization, tactile stimulation, and continuous positive airway support. Blood gas analysis revealed mild mixed acidosis. Chest radiography confirmed pneumothorax and respiratory distress syndrome. The patient was managed conservatively with intratracheal surfactant (100 mg per kilogram per dose), right lateral positioning and high-frequency oscillatory ventilation, without pleural drainage.
Results: The patient responded favorably to supportive management. Respiratory status improved progressively. Oxygen requirements decreased rapidly, and the pneumothorax resolved without invasive intervention. Extubation was achieved on the second day of life, and oxygen therapy was stopped by day six. The patient remained hemodynamically stable, tolerated enteral feeding, and showed appropriate weight gain. On day seven, he was transferred to the neonatal prematurity unit for continued monitoring of growth and jaundice.
Conclusions: This case supports the safety and effectiveness of conservative management in selected preterm neonates with pneumothorax. Early surfactant administration combined with high-frequency oscillatory ventilation (HFOV) can facilitate recovery while avoiding the risks associated with pleural drainage [2]. Tailored respiratory strategies and early control of systemic infection are essential for optimizing outcomes in vulnerable neonates.

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Polycystic ovary syndrome and infertility: A narrative review of diagnostic and therapeutic approaches

Adelina-Georgiana Vârciu1,2

1. Bistrița County Emergency Hospital, Bistrița, Romania
2. Platinia Medical Center, Bistrița, Romania

DOI: 10.2478/amma-2025-0050

Objective: To synthesize current evidence on mechanisms, diagnostic evaluation, and treatment of infertility in PCOS, with emphasis on phenotype-specific implications and integrative management.
Methods: A narrative review was conducted using PubMed, Scopus, and Web of Science from January 2015 to March 2024. Search terms included “PCOS,” “infertility,” “phenotype,” “letrozole,” “metformin,” “gonadotropins,” and “ART.” Eligible studies involved human females aged 18–45 years, written in English, and focused on PCOS-related infertility. Randomized trials, meta-analyses, and international guidelines were critically assessed for methodological rigor and clinical relevance.
Results: PCOS accounts for 70–80% of anovulatory infertility, with marked variability across phenotypes. Phenotype A, combining hyperandrogenism, ovulatory dysfunction, and polycystic ovarian morphology, carries the greatest reproductive and metabolic burden. Biomarkers such as AMH, testosterone, DHEAS, fasting insulin, and HOMA-IR improve risk stratification. Lifestyle modification restores ovulation in up to 60% of overweight patients. Letrozole is superior to clomiphene, while gonadotropins and ART are effective in resistant cases. Metformin enhances ovulatory and pregnancy outcomes in insulin-resistant women. IVF protocols using antagonists and agonist triggers improve safety by reducing ovarian hyperstimulation syndrome. Psychological comorbidities, particularly anxiety and depression, are frequent and negatively affect fertility outcomes.
Conclusion: PCOS-related infertility requires a personalized, multidisciplinary approach. Integration of phenotype-based assessment, biomarker evaluation, lifestyle intervention, and tailored reproductive strategies optimizes outcomes. Addressing metabolic and psychological dimensions further improves reproductive success and long-term health.

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