Shahid Sadoughi University of Medical Sciences
https://en.ssu.ac.ir/publications/Advances in Pharmacology and Therapeutics Journal2783-34456120260801The AI Revolution in Drug Discovery: From Computational Innovation to Clinical Translation110517ENMohsenZabihi0000-0002-8929-3684Journal Article20260721Artificial intelligence (AI) has rapidly evolved from a computational research tool into a major driver of innovation across the pharmaceutical development pipeline. Advances in deep learning, foundation models, protein structure prediction, and generative molecular design have accelerated target identification, compound optimization, toxicity prediction, and biomarker discovery. These developments have substantially reduced the time required to generate and prioritize therapeutic hypotheses.Despite this remarkable progress, the translation of computational predictions into clinically effective medicines remains challenging. Drug development continues to be limited by biological complexity, patient heterogeneity, incomplete datasets, and the need for rigorous experimental and clinical validation. AI can improve decision-making, but it cannot replace the biological evidence required for regulatory approval or patient care.This editorial discusses the evolving role of AI in modern drug discovery while highlighting the importance of explainable algorithms, high-quality biomedical data, real-world evidence, and interdisciplinary collaboration. Rather than viewing AI as a replacement for scientists, clinicians, or pharmacologists, it should be considered a powerful partner that enhances scientific reasoning and accelerates translational research.The future of pharmaceutical innovation will depend on integrating computational intelligence with experimental pharmacology, clinical medicine, and regulatory science. Responsible implementation—not computational sophistication alone—will determine whether AI ultimately delivers safer, more effective, and more personalized therapies for patients.https://aptjournal.ssu.ac.ir/article_517_38913e1d6a7b94cb0f55994f679f5956.pdfShahid Sadoughi University of Medical Sciences
https://en.ssu.ac.ir/publications/Advances in Pharmacology and Therapeutics Journal2783-34456120260829Development of Drug Resistance in the Treatment of Systemic Candidiasis: New Challenges and Future Solutions1113514ENAbbas AliJafari-nodoushan0000-0003-3986-1249Journal Article20260718Systemic candidiasis continues to be the most prevalent healthcare-associated invasive fungal infection, contributing significantly with a high mortality. While Candida albicans continues to be the predominant causative agent, other species such as C. glabrata, C. parapsilosis, C. tropicalis, C. krusei, and various rare Candida species exhibit resistance to fluconazole and other triazole antifungals. The increasing prevalence of fluconazole-resistant C. parapsilosis, echinocandin-resistant C. glabrata, and a new reported multidrug-resistant species, Candida auris, has made clinical management more challenging. Effective antifungal treatment must be chosen based on patient-specific factors, the severity of the disease, history of antifungal use, local epidemiological data, organ involvement, the presence of indwelling medical devices, and accurate species identification. Currently, the challenges associated with antifungal treatments comprise the slow diagnosis reducing from traditional culture techniques and the restricted application of rapid diagnostic tools in clinical settings. To resolve these challenges, it is essential to develop innovative antifungal agents, improve stewardship programs, and enhance global resistance monitoring to maximize treatment results and maintain the effectiveness of antifungal therapies.https://aptjournal.ssu.ac.ir/article_514_59b90e1005a220e2ebc542eb9d950b1e.pdfShahid Sadoughi University of Medical Sciences
https://en.ssu.ac.ir/publications/Advances in Pharmacology and Therapeutics Journal2783-34456120260829Recent Treatment Advances in Bacterial Vaginosis (BV) and Vaginal Candidiasis (VC): Herbal Medicine, Antibiotics, and Probiotics1423521ENMojtabaNorouzi0009-0000-9767-5941RominaKardan0000-0002-7468-5888SomayehMalekmohammadJaberHemmati0000-0003-3539-2238Journal Article20260530The vaginal microbiota is a dynamic ecosystem that changes throughout the menstrual cycle and the life course. Disruption of the healthy vaginal environment can lead to infection and inflammation, most notably bacterial vaginosis (BV) and vaginal candidiasis (VC), two common vaginal diseases affecting women of reproductive age worldwide. BV arises from an imbalance in the vaginal flora, characterized by reduced Lactobacillus abundance and the overgrowth of anaerobic bacteria such as Gardnerella and Mobiluncus. BV presents with symptoms such as abnormal discharge and an unpleasant odor; more importantly, it increases the risk of complications such as pelvic inflammatory disease (PID), adverse pregnancy outcomes, and sexually transmitted infections (STIs). Various factors, including hormonal fluctuations, sexual behavior, poor hygiene, and antibiotic use, influence the stability of the vaginal flora and susceptibility to BV. VC is mainly caused by Candida albicans, but it is increasingly associated with non albicans species and results in inflammation of the vulva and vagina. Its hallmark symptoms include itching, burning, redness, and thick, white discharge. Although VC is treatable with antifungal agents, recurrent or untreated infections can lead to cervicitis, PID, or infertility. Risk factors such as diabetes, pregnancy, immunosuppression, and excessive antibiotic use contribute to the high recurrence rates, negatively affecting women’s physical comfort and mental health. Both BV and VC are closely linked to disturbances in the vaginal microbiota. Understanding their microbial and immunological mechanisms is crucial for effective prevention and treatment. Current therapies include conventional antibiotics and antifungal agents, as well as emerging interventions such as probiotics and microbiota modulating strategies to restore balance. Herbal medicine approaches are also gaining attention for their potential to complement conventional treatments through herbal formulations and external applications. By integrating modern medical and traditional perspectives, researchers aim to develop more personalized and microbiome targeted treatments, thereby improving women’s reproductive and overall health.https://aptjournal.ssu.ac.ir/article_521_07563a3fe3bbe7e3ba84431ad9d055af.pdfShahid Sadoughi University of Medical Sciences
https://en.ssu.ac.ir/publications/Advances in Pharmacology and Therapeutics Journal2783-34456120260829Investigating the Relationship Between Salivary Sialic Acid and HbA1c and Fasting Blood Sugar in Prediabetic and Type 2 Diabetic Individuals2432522ENHojatollahHossainian0000-0001-5558-9850Amir HosseinDoustimotlagh0000-0002-9166-419XLeilaManzourie0000-0002-1684-8693Journal Article20260718Background and Objectives: Diabetes monitoring requires repeated invasive methods. Saliva is a rich source of biomarkers without the need for an invasive method for its collection. Sialic acid is proposed as an acute-phase protein in chronic inflammation of diabetes. This study aimed to determine the association between total salivary sialic acid (TSA) and HbA1c and fasting blood sugar (FBS) in prediabetic and type 2 diabetic individuals, and to evaluate its potential diagnostic utility as a non-invasive biomarker for differentiating these two groups.Methods: This cross-sectional study was carried out on 70 participants (34 with prediabetes, 36 with type 2 diabetes) who were referred to Shahid Moffateh Clinic, Yasuj, Iran. Convenience sampling was employed. Unstimulated saliva (spitting method) and fasting venous blood samples were obtained. TSA was assessed by spectrophotometry, whereas HbA1c and FBS were measured using standard biochemical methods. Data were analyzed with SPSS 23 using Spearman/Pearson correlation tests.Results: Mean age of participants was 50.38±10.14 and 51.50±9.13 years in prediabetic and diabetic groups, respectively. Mean FBS (mg/dL), HbA1c (%), and TSA (mg/dL) levels in prediabetics were 108.94±9.04, 5.63±0.246, and 1764.7±742.02, and in diabetics were 167.05±55.83, 7.02±1.67, and 1672.51±576.59, respectively. No significant correlation was found between TSA and FBS (P=0.53 for prediabetic, P=0.19 for diabetic) and TSA and HbA1c (P=0.90 for prediabetic, P=0.62 for diabetic) in either group. The ROC curve area was 0.44 (P=0.38), indicating poor diagnostic power.Conclusion: Based on our findings, total salivary sialic acid is not a suitable biomarker to replace HbA1c for monitoring prediabetic and type 2 diabetic individuals. Further studies investigating other salivary biomarkers or free sialic acid are recommended.https://aptjournal.ssu.ac.ir/article_522_53fde96fcc4b4ce72d7739202324cd49.pdfShahid Sadoughi University of Medical Sciences
https://en.ssu.ac.ir/publications/Advances in Pharmacology and Therapeutics Journal2783-34456120260829Effects of the Sinopharm Vaccine on the Incidence of Type 2 Diabetes Mellitus and its Complications: A Post-COVID Case Report3336523ENAliNosrati Andevari0000-0002-8699-4688Journal Article20260526Background: SARS-CoV-2, by inducing inflammatory conditions, contributes to the development of Coronavirus disease 2019 (COVID-19) and complications associated with Type 2 diabetes mellitus (T2DM). The Sinopharm COVID-19 vaccine primed the body to respond to subsequent infections by stimulating the immune system. However, this case report investigated the effects of the Sinopharm vaccine on the incidence and complications of T2DM.Case Presentation: A 57-year-old man with a history of prediabetes visited the Amol Health Center (April 18, 2023). Initial and laboratory evaluations showed weight gain, hypertension, hypertriglyceridemia, abnormal glucose profile, and the occurrence of T2DM. The patient reported no prior COVID-19. However, they had been administered a third booster dose of the Sinopharm COVID-19 vaccine around one year earlier. About three years ago, the patient underwent angiography under the supervision of a cardiologist. Prior to the diagnosis of T2DM, the patient was not on any hypoglycemic medication. After approximately three years of quarterly follow-up and drug therapy, significant improvements were observed in the patient's hyperglycemia, hypertriglyceridemia, and hypertension.Discussion and Conclusion: No significant evidence links the Sinopharm vaccine to the pathogenic mechanisms of T2DM. The Sinopharm vaccine might serve as a metabolic stressor that triggers the development of T2DM and its complications in predisposed individuals with prediabetes. Although the risk of T2DM after COVID-19 infection is notably higher than after vaccination, vaccination remains an important protective measure. However, more frequent follow-up could have allowed earlier identification of T2DM in this individual.https://aptjournal.ssu.ac.ir/article_523_2bb232c0b13c774965ef8558f0fbd615.pdf