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Kanagavel M, Sparjan Samuvel RM, Ramalingam V, Nechipadappu SK. Repurposing of Antifungal Drug Flucytosine/Flucytosine Cocrystals for Anticancer Activity against Prostate Cancer Targeting Apoptosis and Inflammatory Signaling Pathways. Mol Pharm 2024; 21:2577-2589. [PMID: 38647021 DOI: 10.1021/acs.molpharmaceut.4c00156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2024]
Abstract
This study aimed to repurpose the antifungal drug flucytosine (FCN) for anticancer activity together with cocrystals of nutraceutical coformers sinapic acid (SNP) and syringic acid (SYA). The cocrystal screening experiments with SNP resulted in three cocrystal hydrate forms in which two are polymorphs, namely, FCN-SNP F-I and FCN-SNP F-II, and the third one with different stoichiometry in the asymmetric unit (1:2:1 ratio of FCN:SNP:H2O, FCN-SNP F-III). Cocrystallization with SYA resulted in two hydrated cocrystal polymorphs, namely, FCN-SYA F-I and FCN-SYA F-II. All the cocrystal polymorphs were obtained concomitantly during the slow evaporation method, and one of the polymorphs of each system was produced in bulk by the slurry method. The interaction energy and lattice energies of all cocrystal polymorphs were established using solid-state DFT calculations, and the outcomes correlated with the experimental results. Further, the in vitro cytotoxic activity of the cocrystals was determined against DU145 prostate cancer and the results showed that the FCN-based cocrystals (FCN-SNP F-III and FCN-SYA F-I) have excellent growth inhibitory activity at lower concentrations compared with parent FCN molecules. The prepared cocrystals induce apoptosis by generating oxidative stress and causing nuclear damage in prostate cancer cells. The Western blot analysis also depicted that the cocrystals downregulate the inflammatory markers such as NLRP3 and caspase-1 and upregulate the intrinsic apoptosis signaling pathway marker proteins, such as Bax, p53, and caspase-3. These findings suggest that the antifungal drug FCN can be repurposed for anticancer activity.
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Affiliation(s)
- Manimurugan Kanagavel
- Centre for X-ray Crystallography, Department of Analytical & Structural Chemistry, CSIR-Indian Institute of Chemical Technology, Hyderabad 500 007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Rajan Marystella Sparjan Samuvel
- Department of Natural Products and Medicinal Chemistry, CSIR-Indian Institute of Chemical Technology, Hyderabad 500 007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Vaikundamoorthy Ramalingam
- Department of Natural Products and Medicinal Chemistry, CSIR-Indian Institute of Chemical Technology, Hyderabad 500 007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Sunil Kumar Nechipadappu
- Centre for X-ray Crystallography, Department of Analytical & Structural Chemistry, CSIR-Indian Institute of Chemical Technology, Hyderabad 500 007, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
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Alsultan A, Dasuqi SA, Almohaizeie A, Aljutayli A, Aljamaan F, Omran RA, Alolayan A, Hamad MA, Alotaibi H, Altamimi S, Alghanem SS. External Validation of Obese/Critically Ill Vancomycin Population Pharmacokinetic Models in Critically Ill Patients Who Are Obese. J Clin Pharmacol 2024; 64:353-361. [PMID: 37862131 DOI: 10.1002/jcph.2375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 10/17/2023] [Indexed: 10/22/2023]
Abstract
Obesity combined with critical illness might increase the risk of acquiring infections and hence mortality. In this patient population the pharmacokinetics of antimicrobials vary significantly, making antimicrobial dosing challenging. The objective of this study was to assess the predictive performance of published population pharmacokinetic models of vancomycin in patients who are critically ill or obese for a cohort of critically ill patients who are obese. This was a multi-center retrospective study conducted at 2 hospitals. Adult patients with a body mass index of ≥30 kg/m2 were included. PubMed was searched for published population pharmacokinetic studies in patients who were critically ill or obese. External validation was performed using Monolix software. A total of 4 models were identified in patients who were obese and 5 models were identified in patients who were critically ill. In total, 138 patients who were critically ill and obese were included, and the most accurate models for these patients were the Goti and Roberts models. In our analysis, models in patients who were critically ill outperformed models in patients who were obese. When looking at the most accurate models, both the Goti and the Roberts models had patient characteristics similar to ours in terms of age and creatinine clearance. This indicates that when selecting the proper model to apply in practice, it is important to account for all relevant variables, besides obesity.
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Affiliation(s)
- Abdullah Alsultan
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Shereen A Dasuqi
- Department of Pharmacy, King Khalid University Hospital, King Saud University Medical City, Riyadh, Saudi Arabia
| | - Abdullah Almohaizeie
- Pharmaceutical Care Division, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Abdullah Aljutayli
- Department of Pharmaceutics, Faculty of Pharmacy, Qassim University, Riyadh, Saudi Arabia
| | - Fadi Aljamaan
- College of Medicine, King Saud University, Riyadh, Saudi Arabia
- Critical Care Department, King Saud University Medical City, King Saud University, Riyadh, Saudi Arabia
| | - Rasha A Omran
- Department of Pharmaceutics and Pharmaceutical Technology, School of Pharmacy, University of Jordan, Amman, Jordan
| | - Abdulaziz Alolayan
- Pharmacy Department, Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia, Riyadh, Saudi Arabia
| | - Mohammed A Hamad
- Critical Care Department, King Saud University Medical City, King Saud University, Riyadh, Saudi Arabia
- Department of Acute Medicine, Wirral University Teaching Hospital NHS Foundation Trust, Arrowe Park Hospital, Wirral, UK
| | - Haifa Alotaibi
- Pharmaceutical Care Division, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Sarah Altamimi
- Pharmaceutical Care Division, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Sarah S Alghanem
- Department of Pharmacy Practice, College of Pharmacy at Kuwait University, Safat, Kuwait
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Alsultan A, Alalwan AA, Alshehri B, Jeraisy MA, Alghamdi J, Alqahtani S, Albassam AA. Interethnic differences in drug response: projected impact of genetic variations in the Saudi population. Pharmacogenomics 2023; 24:685-696. [PMID: 37610881 DOI: 10.2217/pgs-2023-0105] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/25/2023] Open
Abstract
Ethnicity is known to have an impact on drug responses. This is particularly important for drugs that have a narrow therapeutic window, nonlinearity in pharmacokinetics and are metabolized by enzymes that demonstrate genetic polymorphisms. However, most clinical trials are conducted among Caucasians, which might limit the usefulness of the findings of such studies for other ethnicities. The representation of participants from Saudi Arabia in global clinical trials is low. Therefore, there is a paucity of evidence to assess the impact of ethnic variability in the Saudi population on drug response. In this article, the authors assess the projected impact of genetic polymorphisms in drug-metabolizing enzymes and drug targets on drug response in the Saudi population.
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Affiliation(s)
- Abdullah Alsultan
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Abdullah A Alalwan
- Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
| | - Bashayer Alshehri
- Pharmaceutical Care Department, King Abdulaziz Medical City, Riyadh, Saudi Arabia
| | - Majed Al Jeraisy
- Pharmaceutical Care Department, King Abdulaziz Medical City, Riyadh, Saudi Arabia
- College of Pharmacy, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
- King Abdullah International Medical Research Center, Riyadh, Saudi Arabia
| | - Jahad Alghamdi
- Saudi Food and Drug Authority, Drug Sector, Riyadh, Saudi Arabia
| | - Saeed Alqahtani
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Ahmed A Albassam
- Department of Clinical Pharmacy, College of Pharmacy, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia
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Vora LK, Gholap AD, Jetha K, Thakur RRS, Solanki HK, Chavda VP. Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design. Pharmaceutics 2023; 15:1916. [PMID: 37514102 PMCID: PMC10385763 DOI: 10.3390/pharmaceutics15071916] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 06/28/2023] [Accepted: 07/04/2023] [Indexed: 07/30/2023] Open
Abstract
Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic knowledge and provides expedited solutions to complex challenges. Remarkable advancements in AI technology and machine learning present a transformative opportunity in the drug discovery, formulation, and testing of pharmaceutical dosage forms. By utilizing AI algorithms that analyze extensive biological data, including genomics and proteomics, researchers can identify disease-associated targets and predict their interactions with potential drug candidates. This enables a more efficient and targeted approach to drug discovery, thereby increasing the likelihood of successful drug approvals. Furthermore, AI can contribute to reducing development costs by optimizing research and development processes. Machine learning algorithms assist in experimental design and can predict the pharmacokinetics and toxicity of drug candidates. This capability enables the prioritization and optimization of lead compounds, reducing the need for extensive and costly animal testing. Personalized medicine approaches can be facilitated through AI algorithms that analyze real-world patient data, leading to more effective treatment outcomes and improved patient adherence. This comprehensive review explores the wide-ranging applications of AI in drug discovery, drug delivery dosage form designs, process optimization, testing, and pharmacokinetics/pharmacodynamics (PK/PD) studies. This review provides an overview of various AI-based approaches utilized in pharmaceutical technology, highlighting their benefits and drawbacks. Nevertheless, the continued investment in and exploration of AI in the pharmaceutical industry offer exciting prospects for enhancing drug development processes and patient care.
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Affiliation(s)
- Lalitkumar K Vora
- School of Pharmacy, Queen's University Belfast, 97 Lisburn Road, Belfast BT9 7BL, UK
| | - Amol D Gholap
- Department of Pharmaceutics, St. John Institute of Pharmacy and Research, Palghar 401404, Maharashtra, India
| | - Keshava Jetha
- Department of Pharmaceutics and Pharmaceutical Technology, L. M. College of Pharmacy, Ahmedabad 380009, Gujarat, India
- Ph.D. Section, Gujarat Technological University, Ahmedabad 382424, Gujarat, India
| | | | - Hetvi K Solanki
- Pharmacy Section, L. M. College of Pharmacy, Ahmedabad 380009, Gujarat, India
| | - Vivek P Chavda
- Department of Pharmaceutics and Pharmaceutical Technology, L. M. College of Pharmacy, Ahmedabad 380009, Gujarat, India
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Abouelkheir M, Almohaizeie A, Almutairi A, Almuhisen S, Alqahtani S, Alsultan A. Evaluation of vancomycin individualized model-based dosing approach in neonates. Pediatr Neonatol 2022; 64:327-334. [PMID: 36581523 DOI: 10.1016/j.pedneo.2022.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/18/2022] [Accepted: 10/06/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Vancomycin is commonly used to treat methicillin-resistant staphylococcal infections in neonates. Consensus on its ideal dosing in neonates has not been achieved. Model-based dosing recently has evolved as an important tool to optimize vancomycin initial dosing. The aim of this is to evaluate a population pharmacokinetic model-based approach in achieving the vancomycin therapeutic target of an AUC0-24 400 as recommended by the recent IDSA treatment guidelines. This model was implemented as a simple Excel calculator to individualize and optimize vancomycin initial dosing in neonates. METHODS An Excel calculator was developed using a previously published population pharmacokinetic model in neonates. It was evaluated using retrospectively retrieved data. For each patient, the initial empiric dose was calculated using the proposed Excel model and the most widely used neonatal dosing references. The probability of achieving the target AUC0-24 of >400 mg h/L using the model-based method was calculated and compared with that of the empiric doses using other references. RESULTS This analysis included 225 neonates. The probability of achieving the target AUC0-24 >400 was 89% using our model-based approach compared with 11%-59% using tertiary neonatal dosing references (p < 0.01 for all comparisons). CONCLUSION These innovative personalized dosing calculators are promising to improve vancomycin initial dosing in neonates and are easily applicable in routine practices.
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Affiliation(s)
- Manal Abouelkheir
- Department of Clinical Pharmacy, College of Pharmacy, Misr International University, Cairo, Egypt
| | - Abdullah Almohaizeie
- Pharmaceutical Care Division, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Abdulrahman Almutairi
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia; Department of Pharmaceutical Care, Prince Sultan Military Medical City, Riyadh, Saudi Arabia
| | - Sara Almuhisen
- Department of Clinical Pharmacy, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Saeed Alqahtani
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Abdullah Alsultan
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia.
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GU C, GAO Y, HAN R, GUO M, LIU H, GAO J, LIU Y, LI B, SUN L, BU R, LIU Y, HAO J, MENG Y, AN M, CAO X, SU C, LI G. Metabolomics of clinical samples reveal the treatment mechanism of lanthanum hydroxide on vascular calcification in chronic kidney disease. PROCEEDINGS OF THE JAPAN ACADEMY. SERIES B, PHYSICAL AND BIOLOGICAL SCIENCES 2022; 98:361-377. [PMID: 35908957 PMCID: PMC9363596 DOI: 10.2183/pjab.98.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 05/17/2022] [Indexed: 06/15/2023]
Abstract
Previous studies showed that lanthanum hydroxide (LH) has a therapeutic effect on chronic kidney disease (CKD) and vascular calcification, which suggests that it might have clinical value. However, the target and mechanism of action of LH are unclear. Metabolomics of clinical samples can be used to predict the mechanism of drug action. In this study, metabolomic profiles in patients with end-stage renal disease (ESRD) were used to screen related signaling pathways, and we verified the influence of LH on the ROS-PI3K-AKT-mTOR-HIF-1α signaling pathway by western blotting and quantitative real-time RT-qPCR in vivo and in vitro. We found that ROS and SLC16A10 genes were activated in patients with ESRD. The SLC16A10 gene is associated with six significant metabolites (L-cysteine, L-cystine, L-isoleucine, L-arginine, L-aspartic acid, and L-phenylalanine) and the PI3K-AKT signaling pathway. The results showed that LH inhibits the ESRD process and its cardiovascular complications by inhibiting the ROS-PI3K-AKT-mTOR-HIF-1α signaling pathway. Collectively, LH may be a candidate phosphorus binder for the treatment of vascular calcification in ESRD.
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Affiliation(s)
- Chao GU
- Department of Pharmacology, College of Pharmacy, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Yuan GAO
- Department of Pharmacology, College of Pharmacy, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Ruilan HAN
- Department of Pharmacology, College of Pharmacy, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Min GUO
- Department of Clinical Pharmacy, Ordos Central Hospital, Ordos City, Inner Mongolia Autonomous Region, China
| | - Hong LIU
- Department of Pharmacology, College of Pharmacy, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Jie GAO
- Department of Pharmacology, College of Pharmacy, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Yang LIU
- Department of Pharmacology, College of Pharmacy, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Bing LI
- Department of Pharmacology, College of Pharmacy, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Lijun SUN
- Department of Pharmacology, College of Pharmacy, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Ren BU
- Department of Pharmacology, College of Pharmacy, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Yang LIU
- Department of Clinical Pharmacy, Ordos Central Hospital, Ordos City, Inner Mongolia Autonomous Region, China
| | - Jian HAO
- Renal Division, The First Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Yan MENG
- Renal Division, The First Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Ming AN
- Department of Pharmaceutical analysis, School of Pharmacy, Baotou Medical College, Baotou, Inner Mongolia Autonomous Region, China
| | - Xiaodong CAO
- Department of Pharmacology, GLP Center, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
| | - Changhai SU
- Department of Clinical Pharmacy, Ordos Central Hospital, Ordos City, Inner Mongolia Autonomous Region, China
| | - Gang LI
- Department of Pharmacology, College of Pharmacy, Inner Mongolian Medical University, Hohhot, Inner Mongolia Autonomous Region, China
- Mongolian Medicine Collaborative Innovation Center, Inner Mongolia Medical University, Hohhot, Inner Mongolia Autonomous Region, China
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Aljawadi MH, Aldhahri RA, AlMetwazi MS, Arafah A, Khoja AT. The Characteristics of Clinical Studies Submitted to the Saudi Food and Drug Authority from 2009 until 2020. Saudi Pharm J 2021; 29:1155-1165. [PMID: 34703369 PMCID: PMC8523333 DOI: 10.1016/j.jsps.2021.08.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 08/01/2021] [Indexed: 12/01/2022] Open
Abstract
BACKGROUND Clinical trials are crucial in contemporary evidence-based medicine for discovering new treatments for diseases. Their registration in a registry increases the transparency in the dissemination of knowledge about clinical research. It is essential to understand the activity of clinical trials in a country, thus identifying research gaps. OBJECTIVE This study, therefore, aims to describe the clinical trial activity since the inception of clinical trials' administration and national clinical trials' registry within the Kingdom of Saudi Arabia (KSA). METHOD A descriptive study was conducted by reviewing all clinical studies that have been registered during 2009 and June 2020. The inclusion criterion was all phases of the clinical trials registered in the national registry during that period. Data analysis was done using descriptive statistics. RESULTS Since 2009, 352 studies have been registered. However, a total of 333 studies with complete data was included in the analysis. A total of 80 sponsors funded the clinical studies in the KSA. The majority of the clinical studies are funded by multinational pharmaceutical companies. Oncology (13.81%) and diabetes (11.71%) were the most common therapeutic areas and constituted the largest proportion of the overall studies. 44% were phase 4 and 40% were phase 3 studies. CONCLUSION With a population approaching 34 million, the number of clinical trials in the KSA is not sufficient. Since the inception of the clinical trial's administration and SCTR, the emphasis has been on phase 3 and phase 4 clinical studies. The most studied therapeutic areas were oncology and diabetes. Many clinical studies in the KSA were sponsored by multinational pharmaceutical companies.
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Affiliation(s)
- Mohammad H. Aljawadi
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Kingdom of Saudi Arabia
| | - Renad A. Aldhahri
- Department of Pharmaceutical Care, King Abdullah bin Abdulaziz University Hospital, Princess Nourah Bint Abdul Rahman University, Riyadh, Kingdom of Saudi Arabia
| | - Mansour S. AlMetwazi
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Kingdom of Saudi Arabia
| | - Azher Arafah
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Kingdom of Saudi Arabia
| | - Abdullah T. Khoja
- Public Health and Family Medicine Departments, College of Medicine, Al-Imam Muhammad ibn Saud Islamic University (IMSIU), Riyadh, Kingdom of Saudi Arabia
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