Previous
Plant metabolites are an invaluable source of bioactive molecules, and a high percentage of them can react covalently with their targets. Lipid-derived α,β-unsaturated systems (Michael acceptors), which are present in all plants, regulate signaling pathways in cells. In addition, they potentially represent novel molecular targets and mechanisms of action in drug development. The irreversible covalent binding of the majority of these electrophilic molecules to their corresponding molecular targets, combined with, in certain cases, unfavorable pharmacokinetic properties, i.e., absorption, distribution, metabolism, and excretion (ADME), has shifted their use predominantly to that of molecular probes for target identification. In this review, we present examples of structural modification of the original naturally occurring Michael acceptor-containing compounds, as well as examples of incorporating naturally occurring functionalities in the design of reversible covalent probes and drug candidates in order to improve ADME and increase target selectivity.
Plant metabolites are an invaluable source of bioactive molecules, and a high percentage of them can react covalently with their targets. Lipid-derived α,β-unsaturated systems (Michael acceptors), which are present in all plants, regulate signaling pathways in cells. In addition, they potentially represent novel molecular targets and mechanisms of action in drug development. The irreversible covalent binding of the majority of these electrophilic molecules to their corresponding molecular targets, combined with, in certain cases, unfavorable pharmacokinetic properties, i.e., absorption, distribution, metabolism, and excretion (ADME), has shifted their use predominantly to that of molecular probes for target identification. In this review, we present examples of structural modification of the original naturally occurring Michael acceptor-containing compounds, as well as examples of incorporating naturally occurring functionalities in the design of reversible covalent probes and drug candidates in order to improve ADME and increase target selectivity.
DOI: https://doi.org/10.37349/eds.2026.1008178
This article belongs to the special issue The Rise of Targeted Covalent Inhibitors in Drug Discovery
Cannabis sativa has a long history in ethnomedicine, but advances in molecular biology and regulatory shifts have reignited global interest in its therapeutic potential. Cannabinoid research in the 21st century spans molecular pharmacology, clinical applications, and public health integration. This study provides a comprehensive synthesis of the current state of knowledge. This narrative review synthesizes evidence from Scopus, PubMed, and Google Scholar using Medical Subject Headings-based search strategies. Only articles published in English were included, without restrictions on publication year; however, greater emphasis was placed on recent studies to ensure currency, while seminal and historically important publications were included where necessary to provide foundational context. Relevant studies were thematically analyzed and summarized under predefined headings. Major phytocannabinoids have been identified, with Δ9-tetrahydrocannabinol, cannabidiol, and cannabigerol as key therapeutic candidates. Preclinical studies have shown neuroprotective, anti-inflammatory, analgesic, immunomodulatory, and anticancer effects, but clinical translation remains limited by variability, dosing challenges, and inconsistent reproducibility. These effects are mediated through the endocannabinoid system and related receptor networks. Emerging evidence suggests that epigenetic regulation and precision medicine approaches may enhance individualized cannabinoid therapy. However, safety concerns, including cognitive and psychiatric effects, drug interactions, and dependence, require robust pharmacovigilance. Fragmented regulatory frameworks continue to hinder research and equitable access, underscoring the need for standardized formulations, clinician training, and equity-focused integration into health systems. Cannabinoid therapeutics represent a rapidly evolving field with promise in multiple medical domains. Future progress hinges on harmonizing regulations, expanding clinical evidence, and integrating precision medicine, equity, and public health principles to maximize therapeutic benefits while minimizing risks.
Cannabis sativa has a long history in ethnomedicine, but advances in molecular biology and regulatory shifts have reignited global interest in its therapeutic potential. Cannabinoid research in the 21st century spans molecular pharmacology, clinical applications, and public health integration. This study provides a comprehensive synthesis of the current state of knowledge. This narrative review synthesizes evidence from Scopus, PubMed, and Google Scholar using Medical Subject Headings-based search strategies. Only articles published in English were included, without restrictions on publication year; however, greater emphasis was placed on recent studies to ensure currency, while seminal and historically important publications were included where necessary to provide foundational context. Relevant studies were thematically analyzed and summarized under predefined headings. Major phytocannabinoids have been identified, with Δ9-tetrahydrocannabinol, cannabidiol, and cannabigerol as key therapeutic candidates. Preclinical studies have shown neuroprotective, anti-inflammatory, analgesic, immunomodulatory, and anticancer effects, but clinical translation remains limited by variability, dosing challenges, and inconsistent reproducibility. These effects are mediated through the endocannabinoid system and related receptor networks. Emerging evidence suggests that epigenetic regulation and precision medicine approaches may enhance individualized cannabinoid therapy. However, safety concerns, including cognitive and psychiatric effects, drug interactions, and dependence, require robust pharmacovigilance. Fragmented regulatory frameworks continue to hinder research and equitable access, underscoring the need for standardized formulations, clinician training, and equity-focused integration into health systems. Cannabinoid therapeutics represent a rapidly evolving field with promise in multiple medical domains. Future progress hinges on harmonizing regulations, expanding clinical evidence, and integrating precision medicine, equity, and public health principles to maximize therapeutic benefits while minimizing risks.
DOI: https://doi.org/10.37349/eds.2026.1008177
The therapeutic landscape for obesity is changing rapidly, driven by the recognition of obesity as a chronic, biologically heterogeneous disease, with clinically relevant organ consequences. In this context, the phase 3 SYNCHRONIZE™-1 trial of survodutide, a once-weekly dual agonist of glucagon receptor and glucagon-like peptide 1 (GLP-1) receptor, is notable not simply because it adds another effective incretin-based therapy, but because it tests a broader metabolic concept. By pairing GLP-1-mediated appetite suppression with glucagon-mediated effects on energy expenditure and hepatic lipid handling, survodutide aims to extend treatment beyond appetite control towards coordinated modulation of adiposity, cardiometabolic risk and steatotic liver disease. In adults with obesity without diabetes, SYNCHRONIZE™-1 showed sustained body-weight reductions of approximately 12–13% over 76 weeks, compared with 5.4% with placebo, and increased the proportion of participants achieving clinically ambitious weight-loss thresholds, including at least 20% weight loss. Improvements in waist circumference, glycemic and lipid measures, together with reductions in visceral and liver fat content (LFC) in imaging analyses, support the possibility of benefits that are metabolically broader than scale weight alone. Yet the trial also illustrates familiar tensions in obesity pharmacotherapy: gastrointestinal tolerability, treatment discontinuation, the absence of an active comparator, unexpectedly high placebo-associated weight loss and limited outcome data. Thus, SYNCHRONIZE™-1 should be read as an important proof of principle for dual glucagon-GLP-1 receptor agonism rather than as a definitive positioning of the therapy within the treatment landscape. The next challenge is to determine whether this mechanism delivers durable cardiovascular, renal, and hepatic benefits, and in which patient populations.
The therapeutic landscape for obesity is changing rapidly, driven by the recognition of obesity as a chronic, biologically heterogeneous disease, with clinically relevant organ consequences. In this context, the phase 3 SYNCHRONIZE™-1 trial of survodutide, a once-weekly dual agonist of glucagon receptor and glucagon-like peptide 1 (GLP-1) receptor, is notable not simply because it adds another effective incretin-based therapy, but because it tests a broader metabolic concept. By pairing GLP-1-mediated appetite suppression with glucagon-mediated effects on energy expenditure and hepatic lipid handling, survodutide aims to extend treatment beyond appetite control towards coordinated modulation of adiposity, cardiometabolic risk and steatotic liver disease. In adults with obesity without diabetes, SYNCHRONIZE™-1 showed sustained body-weight reductions of approximately 12–13% over 76 weeks, compared with 5.4% with placebo, and increased the proportion of participants achieving clinically ambitious weight-loss thresholds, including at least 20% weight loss. Improvements in waist circumference, glycemic and lipid measures, together with reductions in visceral and liver fat content (LFC) in imaging analyses, support the possibility of benefits that are metabolically broader than scale weight alone. Yet the trial also illustrates familiar tensions in obesity pharmacotherapy: gastrointestinal tolerability, treatment discontinuation, the absence of an active comparator, unexpectedly high placebo-associated weight loss and limited outcome data. Thus, SYNCHRONIZE™-1 should be read as an important proof of principle for dual glucagon-GLP-1 receptor agonism rather than as a definitive positioning of the therapy within the treatment landscape. The next challenge is to determine whether this mechanism delivers durable cardiovascular, renal, and hepatic benefits, and in which patient populations.
DOI: https://doi.org/10.37349/eds.2026.1008175
Cancer treatment faces severe challenges such as drug resistance, side effects, and high costs. The “repurposing old drugs” strategy, which involves repositioning approved drugs for non-oncology indications for cancer treatment, has opened up new avenues for developing efficient, low-toxicity, and rapidly translatable combination therapies. This strategy can not only accelerate clinical translation by leveraging known pharmacological and safety data but also generate synergistic effects with standard chemotherapy, targeted therapy, or immunotherapy by targeting non-classical pathways such as the tumor microenvironment, metabolic reprogramming, and epigenetic regulation. This paper aims to systematically review the repositioning strategies of non-oncology drugs in cancer combination therapies, focusing on their mechanisms of action, synergistic principles, high-throughput screening and computational prediction methods, as well as pre-clinical and clinical research progress based on models such as patient-derived organoids. The paper systematically analyzes the synergistic effects and potential of representative drugs such as metformin, statins, antimalarials, antipsychotics, non-steroidal anti-inflammatory drugs, β-blockers, antihistamines, and cardiovascular drugs. It also summarizes the current challenges in drug screening, mechanism validation, commercial incentives, clinical trial design, and safety re-evaluation, aiming to provide a theoretical basis and future research directions for optimizing cancer combination treatment strategies.
Cancer treatment faces severe challenges such as drug resistance, side effects, and high costs. The “repurposing old drugs” strategy, which involves repositioning approved drugs for non-oncology indications for cancer treatment, has opened up new avenues for developing efficient, low-toxicity, and rapidly translatable combination therapies. This strategy can not only accelerate clinical translation by leveraging known pharmacological and safety data but also generate synergistic effects with standard chemotherapy, targeted therapy, or immunotherapy by targeting non-classical pathways such as the tumor microenvironment, metabolic reprogramming, and epigenetic regulation. This paper aims to systematically review the repositioning strategies of non-oncology drugs in cancer combination therapies, focusing on their mechanisms of action, synergistic principles, high-throughput screening and computational prediction methods, as well as pre-clinical and clinical research progress based on models such as patient-derived organoids. The paper systematically analyzes the synergistic effects and potential of representative drugs such as metformin, statins, antimalarials, antipsychotics, non-steroidal anti-inflammatory drugs, β-blockers, antihistamines, and cardiovascular drugs. It also summarizes the current challenges in drug screening, mechanism validation, commercial incentives, clinical trial design, and safety re-evaluation, aiming to provide a theoretical basis and future research directions for optimizing cancer combination treatment strategies.
DOI: https://doi.org/10.37349/eds.2026.1008176
This article belongs to the special issue Drug Repurposing: Accelerating Cancer Therapeutic Discoveries
Background:
Acid-hydrolyzed nanocrystalline starch has attracted interest as a sustainable pharmaceutical excipient because of its crystallinity, compactibility, and potential suitability for direct compression tableting. However, the available evidence on its fabrication methods, material attributes, and performance as a direct compression tablet excipient remains scattered.
Methods:
A systematic review was conducted using MEDLINE, Scopus, PubMed, Embase®, and Google Scholar to identify studies published from 2000 to 2025. Search terms included starch nanocrystals, acid-modified starch, hydrolyzed starch, acid-hydrolyzed starch, nanostarch, and direct compression fillers. Forward and backward snowballing were also performed. Studies were screened using predefined eligibility criteria, excluding reviews, conference abstracts, non-pharmaceutical applications, low crystallinity products, and studies lacking adequate characterization, particularly X-ray diffraction.
Results:
The search identified 651 records; after removal of 3 duplicate records, 648 records were screened, 51 underwent full text assessment, and 34 were included in the review. Acid hydrolysis was the most widely reported method for preparing nanocrystalline starch, while pretreatment strategies such as enzymatic treatment, ultrasonication, ball milling, heat moisture treatment, organic acid treatment, and mixed acid hydrolysis were reported to reduce preparation time or improve yield and crystallinity. Across tablet related studies, acid modified nanocrystalline starch generally showed improved crystallinity, compactibility, and tablet hardness compared with native starch. Spray drying and agglomeration further improved flow and direct compression performance in several studies.
Discussion:
Acid modified nanocrystalline starch shows promise as a sustainable direct compression tablet excipient. However, broader pharmaceutical adoption remains limited by low or variable yield, long processing time, botanical source variability, inconsistent powder flow, limited standardization, and unclear scale up pathways. Future studies should connect preparation methods, material characterization, powder flow engineering, and tablet performance testing to support industrial development.
Background:
Acid-hydrolyzed nanocrystalline starch has attracted interest as a sustainable pharmaceutical excipient because of its crystallinity, compactibility, and potential suitability for direct compression tableting. However, the available evidence on its fabrication methods, material attributes, and performance as a direct compression tablet excipient remains scattered.
Methods:
A systematic review was conducted using MEDLINE, Scopus, PubMed, Embase®, and Google Scholar to identify studies published from 2000 to 2025. Search terms included starch nanocrystals, acid-modified starch, hydrolyzed starch, acid-hydrolyzed starch, nanostarch, and direct compression fillers. Forward and backward snowballing were also performed. Studies were screened using predefined eligibility criteria, excluding reviews, conference abstracts, non-pharmaceutical applications, low crystallinity products, and studies lacking adequate characterization, particularly X-ray diffraction.
Results:
The search identified 651 records; after removal of 3 duplicate records, 648 records were screened, 51 underwent full text assessment, and 34 were included in the review. Acid hydrolysis was the most widely reported method for preparing nanocrystalline starch, while pretreatment strategies such as enzymatic treatment, ultrasonication, ball milling, heat moisture treatment, organic acid treatment, and mixed acid hydrolysis were reported to reduce preparation time or improve yield and crystallinity. Across tablet related studies, acid modified nanocrystalline starch generally showed improved crystallinity, compactibility, and tablet hardness compared with native starch. Spray drying and agglomeration further improved flow and direct compression performance in several studies.
Discussion:
Acid modified nanocrystalline starch shows promise as a sustainable direct compression tablet excipient. However, broader pharmaceutical adoption remains limited by low or variable yield, long processing time, botanical source variability, inconsistent powder flow, limited standardization, and unclear scale up pathways. Future studies should connect preparation methods, material characterization, powder flow engineering, and tablet performance testing to support industrial development.
DOI: https://doi.org/10.37349/eds.2026.1008174
Human milk is widely recognized as the biological standard for early-life nutrition, providing both essential nutrients and bioactive components that support immune development. However, breastfeeding is not always feasible, and infant formula remains a necessary alternative in specific clinical and social contexts. Despite advances in formulation, significant immunological differences persist between breastfed and formula-fed infants, contributing to the so-called “immunological gap.” This review critically examines the potential of human milk-derived antimicrobial peptides (HM-AMPs) as functional ingredients to partially address this gap. Current evidence indicates that these peptides, derived from proteins such as lactoferrin, caseins, and α-lactalbumin, exhibit antimicrobial and immunomodulatory activities through mechanisms including membrane disruption and modulation of inflammatory pathways. However, most available data are derived from in vitro and preclinical models, limiting direct translation to clinical outcomes. In addition, significant challenges remain, including peptide instability during industrial processing, uncertain bioavailability in the gastrointestinal tract, and limited clinical validation. While emerging computational and bioengineering strategies offer opportunities to optimize peptide functionality, their large-scale implementation remains constrained by technological and regulatory factors. Overall, HM-AMPs represent a promising but still developing approach to improving infant formula functionality. Their contribution should be interpreted as partial and context-dependent, rather than as a complete replication of the immunological properties of human milk.
Human milk is widely recognized as the biological standard for early-life nutrition, providing both essential nutrients and bioactive components that support immune development. However, breastfeeding is not always feasible, and infant formula remains a necessary alternative in specific clinical and social contexts. Despite advances in formulation, significant immunological differences persist between breastfed and formula-fed infants, contributing to the so-called “immunological gap.” This review critically examines the potential of human milk-derived antimicrobial peptides (HM-AMPs) as functional ingredients to partially address this gap. Current evidence indicates that these peptides, derived from proteins such as lactoferrin, caseins, and α-lactalbumin, exhibit antimicrobial and immunomodulatory activities through mechanisms including membrane disruption and modulation of inflammatory pathways. However, most available data are derived from in vitro and preclinical models, limiting direct translation to clinical outcomes. In addition, significant challenges remain, including peptide instability during industrial processing, uncertain bioavailability in the gastrointestinal tract, and limited clinical validation. While emerging computational and bioengineering strategies offer opportunities to optimize peptide functionality, their large-scale implementation remains constrained by technological and regulatory factors. Overall, HM-AMPs represent a promising but still developing approach to improving infant formula functionality. Their contribution should be interpreted as partial and context-dependent, rather than as a complete replication of the immunological properties of human milk.
DOI: https://doi.org/10.37349/eds.2026.1008173
Aim:
Squamous cell carcinoma (SCC) is one of the most common types of cancer affecting the oral cavity and the upper aerodigestive tract. In many cases, misdiagnosis leads to the progression of the disease to life-threatening stages, highlighting the importance of advancing anti-oral cancer therapeutics. In this study, we evaluated the cytotoxic activity against SCC of a series of synthetic peptides derived from bovine lactoferricin (bLFcin). To enhance the cationic and amphiphilic properties of lactoferricin-derived peptides, we designed branched and palindromic sequences from bLFcin(20-25) (i.e., 20RRWQWR25).
Methods:
A total of 14 peptides were synthesized using solid support synthesis. More than 90% peptide purity was obtained by solid-phase extraction, and the final products were characterized using reversed-phase liquid chromatography and mass spectrometry. The in vitro cytotoxic activity of the peptides was assessed in cancer cell lines SCC9 and FaDu; HEK001 keratinocytes were used as a non-cancerous control cell line. Additionally, scanning electron microscopy and flow cytometry provided further insights into the peptide-cell interaction. Finally, the dimeric peptide bLFcin(20-25)2 was evaluated in a chemically-induced carcinoma in vivo model.
Results:
Tetrameric and dimeric peptides with higher cationic charge and improved amphiphilic properties were cytotoxic to the oral carcinoma cell line FaDu. Scanning electron microscopy revealed membrane disruption and pore formation. In addition, flow cytometric analyses of cells treated with fluorescently tagged bLFcin(20-25)2 confirmed the interaction of the cationic peptide with the anionic cancer cells. Furthermore, the dimeric peptide bLFcin(20-25)2 inhibited tumor growth of chemically induced oral carcinoma in hamsters, demonstrating its in vivo efficacy.
Conclusions:
Branched peptides with a higher cationic charge were cytotoxic to the cancer cell line FaDu; they induced cell membrane lysis, as evidenced by electron microscopy, and inhibited tumor progression in hamsters. These preliminary results support further design and mechanistic evaluation of branched cationic peptides as potential oral cancer therapeutics.
Aim:
Squamous cell carcinoma (SCC) is one of the most common types of cancer affecting the oral cavity and the upper aerodigestive tract. In many cases, misdiagnosis leads to the progression of the disease to life-threatening stages, highlighting the importance of advancing anti-oral cancer therapeutics. In this study, we evaluated the cytotoxic activity against SCC of a series of synthetic peptides derived from bovine lactoferricin (bLFcin). To enhance the cationic and amphiphilic properties of lactoferricin-derived peptides, we designed branched and palindromic sequences from bLFcin(20-25) (i.e., 20RRWQWR25).
Methods:
A total of 14 peptides were synthesized using solid support synthesis. More than 90% peptide purity was obtained by solid-phase extraction, and the final products were characterized using reversed-phase liquid chromatography and mass spectrometry. The in vitro cytotoxic activity of the peptides was assessed in cancer cell lines SCC9 and FaDu; HEK001 keratinocytes were used as a non-cancerous control cell line. Additionally, scanning electron microscopy and flow cytometry provided further insights into the peptide-cell interaction. Finally, the dimeric peptide bLFcin(20-25)2 was evaluated in a chemically-induced carcinoma in vivo model.
Results:
Tetrameric and dimeric peptides with higher cationic charge and improved amphiphilic properties were cytotoxic to the oral carcinoma cell line FaDu. Scanning electron microscopy revealed membrane disruption and pore formation. In addition, flow cytometric analyses of cells treated with fluorescently tagged bLFcin(20-25)2 confirmed the interaction of the cationic peptide with the anionic cancer cells. Furthermore, the dimeric peptide bLFcin(20-25)2 inhibited tumor growth of chemically induced oral carcinoma in hamsters, demonstrating its in vivo efficacy.
Conclusions:
Branched peptides with a higher cationic charge were cytotoxic to the cancer cell line FaDu; they induced cell membrane lysis, as evidenced by electron microscopy, and inhibited tumor progression in hamsters. These preliminary results support further design and mechanistic evaluation of branched cationic peptides as potential oral cancer therapeutics.
DOI: https://doi.org/10.37349/eds.2026.1008171
Aim:
Antimicrobial resistance (AMR) among vaginal bacterial pathogens is an increasing clinical concern, particularly where empirical therapy is common and local susceptibility data are limited. This study investigated the prevalence, resistance patterns, and multidrug resistance (MDR) burden of bacterial isolates recovered from human high vaginal swabs (HVSs).
Methods:
A retrospective laboratory-based analysis was performed on 220 bacterial isolates recovered from HVS specimens. Organism distribution, antibiotic resistance prevalence, MDR status, MRSA/ESBL phenotypes, MDR scores, hierarchical clustering, heatmap patterns, and principal component analysis were evaluated using R-based statistical and multivariate methods.
Results:
Staphylococcus aureus was the most frequent isolate (50.0%), followed by Escherichia coli (38.6%). The highest overall resistance was observed against ceftazidime (89.1%), clarithromycin (83.6%), erythromycin (80.9%), cefoxitin (79.1%), levofloxacin (77.7%), and penicillin (77.3%). In contrast, vancomycin (10.9%), chloramphenicol (11.4%), imipenem (11.8%), linezolid (15.5%), and amikacin (20.0%) retained comparatively better activity. MDR was detected in 95.0% of isolates, with a mean MDR score of 5.19. Clustering, heatmap, and PCA analyses demonstrated distinct resistance groupings and strong co-resistance patterns among the major pathogens.
Conclusions:
The study demonstrates a high burden of AMR and MDR among HVS-derived bacterial isolates, especially among S. aureus and E. coli. These findings support routine culture-based susceptibility testing and stronger antimicrobial stewardship in women with vaginal infections.
Aim:
Antimicrobial resistance (AMR) among vaginal bacterial pathogens is an increasing clinical concern, particularly where empirical therapy is common and local susceptibility data are limited. This study investigated the prevalence, resistance patterns, and multidrug resistance (MDR) burden of bacterial isolates recovered from human high vaginal swabs (HVSs).
Methods:
A retrospective laboratory-based analysis was performed on 220 bacterial isolates recovered from HVS specimens. Organism distribution, antibiotic resistance prevalence, MDR status, MRSA/ESBL phenotypes, MDR scores, hierarchical clustering, heatmap patterns, and principal component analysis were evaluated using R-based statistical and multivariate methods.
Results:
Staphylococcus aureus was the most frequent isolate (50.0%), followed by Escherichia coli (38.6%). The highest overall resistance was observed against ceftazidime (89.1%), clarithromycin (83.6%), erythromycin (80.9%), cefoxitin (79.1%), levofloxacin (77.7%), and penicillin (77.3%). In contrast, vancomycin (10.9%), chloramphenicol (11.4%), imipenem (11.8%), linezolid (15.5%), and amikacin (20.0%) retained comparatively better activity. MDR was detected in 95.0% of isolates, with a mean MDR score of 5.19. Clustering, heatmap, and PCA analyses demonstrated distinct resistance groupings and strong co-resistance patterns among the major pathogens.
Conclusions:
The study demonstrates a high burden of AMR and MDR among HVS-derived bacterial isolates, especially among S. aureus and E. coli. These findings support routine culture-based susceptibility testing and stronger antimicrobial stewardship in women with vaginal infections.
DOI: https://doi.org/10.37349/eds.2026.1008172
Hepatitis C virus (HCV) remains a major global health burden, causing significant morbidity, mortality, and economic costs. Direct-acting antivirals (DAAs) have become the primary treatment for patients with hepatitis C. Since the first approval in 2011, more effective agents have entered the market. Different guidelines for hepatitis treatment are implemented worldwide. The American Association for the Study of Liver Diseases (AASLD) and the European Association for the Study of the Liver (EASL) recommend using DAAs in combination to achieve better outcomes and reduce resistance. The guidelines include regimens for treatment-naive and -experienced patients. They also include treatment recommendations for cirrhotic patients and unique populations. With mass screening, treatment over the last few years, and possible vaccination, eradication is attainable.
Hepatitis C virus (HCV) remains a major global health burden, causing significant morbidity, mortality, and economic costs. Direct-acting antivirals (DAAs) have become the primary treatment for patients with hepatitis C. Since the first approval in 2011, more effective agents have entered the market. Different guidelines for hepatitis treatment are implemented worldwide. The American Association for the Study of Liver Diseases (AASLD) and the European Association for the Study of the Liver (EASL) recommend using DAAs in combination to achieve better outcomes and reduce resistance. The guidelines include regimens for treatment-naive and -experienced patients. They also include treatment recommendations for cirrhotic patients and unique populations. With mass screening, treatment over the last few years, and possible vaccination, eradication is attainable.
DOI: https://doi.org/10.37349/eds.2026.1008169
This article belongs to the special issue Innovations in Hepatology: Bridging Drug Development and Biomarker Discovery
Aim:
To address the limitations of current metabolomics analysis, including the neglect of metabolite interdependencies, poor interpretability of black-box models, and incomplete utilization of biological information due to pathway annotation limitations. This study aims to develop and validate a dual-branch biologically informed neural network (Dual-BINN) that integrates metabolic pathway hierarchy and molecular structural hierarchy for improved prediction and interpretability in metabolomics.
Methods:
We developed a Dual-BINN, which explicitly incorporates metabolic pathway hierarchy and molecular structural category hierarchy into the model architecture. Pathway and structure subnetworks were constructed and integrated via an adaptive fusion mechanism. SHAP was employed for interpretability analysis. The model was evaluated using multi-center plasma metabolomics data for gastric cancer and a breast cancer dataset.
Results:
On the independent gastric cancer test set, Dual-BINN achieved a recall of 0.937, which compares favorably with the recall of 0.905 reported by the 10-DM model on the same dataset split. Key metabolites were enriched in the tricarboxylic acid cycle, one-carbon metabolism, and energy metabolism pathways, while structurally concentrated in organic acids, amino acids, and nucleoside-related compounds. The model also demonstrated excellent classification performance on the breast cancer dataset, confirming strong cross-disease generalization ability.
Conclusions:
The proposed framework enhances predictive performance while providing biologically meaningful structured interpretations, offering a robust computational approach for metabolomic mechanism analysis and biomarker discovery in complex diseases.
Aim:
To address the limitations of current metabolomics analysis, including the neglect of metabolite interdependencies, poor interpretability of black-box models, and incomplete utilization of biological information due to pathway annotation limitations. This study aims to develop and validate a dual-branch biologically informed neural network (Dual-BINN) that integrates metabolic pathway hierarchy and molecular structural hierarchy for improved prediction and interpretability in metabolomics.
Methods:
We developed a Dual-BINN, which explicitly incorporates metabolic pathway hierarchy and molecular structural category hierarchy into the model architecture. Pathway and structure subnetworks were constructed and integrated via an adaptive fusion mechanism. SHAP was employed for interpretability analysis. The model was evaluated using multi-center plasma metabolomics data for gastric cancer and a breast cancer dataset.
Results:
On the independent gastric cancer test set, Dual-BINN achieved a recall of 0.937, which compares favorably with the recall of 0.905 reported by the 10-DM model on the same dataset split. Key metabolites were enriched in the tricarboxylic acid cycle, one-carbon metabolism, and energy metabolism pathways, while structurally concentrated in organic acids, amino acids, and nucleoside-related compounds. The model also demonstrated excellent classification performance on the breast cancer dataset, confirming strong cross-disease generalization ability.
Conclusions:
The proposed framework enhances predictive performance while providing biologically meaningful structured interpretations, offering a robust computational approach for metabolomic mechanism analysis and biomarker discovery in complex diseases.
DOI: https://doi.org/10.37349/eds.2026.1008170
A diabetic foot ulcer (DFU) is an open sore or wound, usually on the bottom of the foot, affecting about 15% of people with diabetes. Caused by nerve damage, poor circulation, and high pressure, these ulcers often present as swelling, drainage, redness, or foot deformities. Treatment focuses on infection control, debridement, and offloading pressure, often taking weeks to months to heal. Despite treatment, recurrence and amputation remain major clinical concerns. Gene therapy for DFUs is an emerging, promising field aiming to accelerate healing in chronic, non-healing wounds by delivering therapeutics (e.g., growth factors) directly to the site to promote angiogenesis and tissue regeneration. Key approaches include topically applied, multi-target gene therapies (e.g., AUP1602-C reporting 83% healing rate) and plasmid-based therapies (e.g., VM202/Engensis). This narrative review aims to describe the molecular aspects of wound healing, pathogenesis and management of DFU, followed by evolving gene therapies including AUP-16, VM202, and gene targets like SCUBE1, RNF103-CHMP3 and PGI1. We have also discussed emerging targets such as C-X-C motif chemokine receptor 4 (CXCR4), thrombospondin 1 (TSP1), yes-associated protein-transcriptional co-activator with PDZ binding motif (YAP-TAZ) pathway, and others as potential targets for gene therapy to promote healing in chronic non-healing DFUs.
A diabetic foot ulcer (DFU) is an open sore or wound, usually on the bottom of the foot, affecting about 15% of people with diabetes. Caused by nerve damage, poor circulation, and high pressure, these ulcers often present as swelling, drainage, redness, or foot deformities. Treatment focuses on infection control, debridement, and offloading pressure, often taking weeks to months to heal. Despite treatment, recurrence and amputation remain major clinical concerns. Gene therapy for DFUs is an emerging, promising field aiming to accelerate healing in chronic, non-healing wounds by delivering therapeutics (e.g., growth factors) directly to the site to promote angiogenesis and tissue regeneration. Key approaches include topically applied, multi-target gene therapies (e.g., AUP1602-C reporting 83% healing rate) and plasmid-based therapies (e.g., VM202/Engensis). This narrative review aims to describe the molecular aspects of wound healing, pathogenesis and management of DFU, followed by evolving gene therapies including AUP-16, VM202, and gene targets like SCUBE1, RNF103-CHMP3 and PGI1. We have also discussed emerging targets such as C-X-C motif chemokine receptor 4 (CXCR4), thrombospondin 1 (TSP1), yes-associated protein-transcriptional co-activator with PDZ binding motif (YAP-TAZ) pathway, and others as potential targets for gene therapy to promote healing in chronic non-healing DFUs.
DOI: https://doi.org/10.37349/eds.2026.1008168
This article belongs to the special issue Advances and Innovations in Gene-Based Medicine
PKPDindex() is a free and open-source R package for analysing pharmacokinetic/pharmacodynamic (PK/PD) indices, including AUC/MIC, Cmax/MIC, and T>MIC. Development was motivated by previously identified inconsistencies in PK/PD index modelling and reporting practices. The package fits eight variations of the Emax model to data and compares model performance using the Akaike information criterion (AIC) and R2 values. As input, the package requires a dataset containing PK/PD indices and a response variable. As output, it generates tables summarising all fitted models, identifies the best-fitting model for each index, and produces customisable plots of model fits with parameter estimates. PKPDindex() is freely available on CRAN (https://CRAN.R-project.org/package=PKPDindex).
PKPDindex() is a free and open-source R package for analysing pharmacokinetic/pharmacodynamic (PK/PD) indices, including AUC/MIC, Cmax/MIC, and T>MIC. Development was motivated by previously identified inconsistencies in PK/PD index modelling and reporting practices. The package fits eight variations of the Emax model to data and compares model performance using the Akaike information criterion (AIC) and R2 values. As input, the package requires a dataset containing PK/PD indices and a response variable. As output, it generates tables summarising all fitted models, identifies the best-fitting model for each index, and produces customisable plots of model fits with parameter estimates. PKPDindex() is freely available on CRAN (https://CRAN.R-project.org/package=PKPDindex).
DOI: https://doi.org/10.37349/eds.2026.1008167
This article belongs to the special issue Precision Dosing: From Therapeutic Drug Monitoring to AI-Driven Personalization
Today, researchers have already made great progress in finding drug-based clinical solutions against microbial infections. It has become an essential part of a healthy human lifestyle. High antibiotic consumption has accelerated antibiotic resistance in microbial species (multi-drug-resistant microbial strains, like Staphylococcus aureus and Mycobacterium tuberculosis, have already been reported). Loss of microflora is also associated with the heavy and unnecessary use of drugs. This review presents bacteriophage as an alternative to antibiotics. The supporting bacteriophage characteristics include bacteriophage lytic mode of replication, specificity towards its host, bacteriophage mass production, and bacteriophage genetic modification (BRED and CRISPR) to make it capable of degrading microbial biofilm. The author has also tried to inculcate previous work that has already been done with bacteriophages for some clinical therapies. Potential administration routes (oral, intravenous, and intraoperative) used in clinical therapies are discussed.
Today, researchers have already made great progress in finding drug-based clinical solutions against microbial infections. It has become an essential part of a healthy human lifestyle. High antibiotic consumption has accelerated antibiotic resistance in microbial species (multi-drug-resistant microbial strains, like Staphylococcus aureus and Mycobacterium tuberculosis, have already been reported). Loss of microflora is also associated with the heavy and unnecessary use of drugs. This review presents bacteriophage as an alternative to antibiotics. The supporting bacteriophage characteristics include bacteriophage lytic mode of replication, specificity towards its host, bacteriophage mass production, and bacteriophage genetic modification (BRED and CRISPR) to make it capable of degrading microbial biofilm. The author has also tried to inculcate previous work that has already been done with bacteriophages for some clinical therapies. Potential administration routes (oral, intravenous, and intraoperative) used in clinical therapies are discussed.
DOI: https://doi.org/10.37349/eds.2026.1008166
Schizophrenia affects approximately 24 million people worldwide, representing 0.3–0.7% of the global population, and remains a leading cause of years lived with disability. The disorder contributes to over 13 million disability-adjusted life years, underscoring its substantial global health and socioeconomic burden. This review critically examines the convergence of artificial intelligence (AI) and advanced oral drug delivery systems as an emerging strategy in schizophrenia management. Conventional diagnostic frameworks, reliant on subjective symptom assessment, often result in delayed or inaccurate diagnosis, while standard oral antipsychotics are limited by poor bioavailability, extensive first-pass metabolism, and inadequate brain targeting. Recent advances in AI, including natural language processing (NLP), neuroimaging analytics, electrophysiological modeling, and multi-omics integration, support diagnostic classification, risk prediction, symptom monitoring, and patient stratification. Simultaneously, nanotechnology-driven oral delivery platforms such as lipid nanoparticles, dendrimers, and proliposomes enhance pharmacokinetics, central nervous system targeting, and therapeutic adherence. The integration of AI with pharmacogenomics, wearable monitoring, and digital twin models further facilitates real-time dose optimization and personalized therapy. Despite promising preclinical and clinical outcomes, challenges related to data privacy, algorithmic bias, scalability, and regulatory translation persist. This review highlights a shift toward precision psychiatry, where AI-enabled diagnostics and smart oral therapeutics may support predictive, personalized, and adaptive care in schizophrenia.
Schizophrenia affects approximately 24 million people worldwide, representing 0.3–0.7% of the global population, and remains a leading cause of years lived with disability. The disorder contributes to over 13 million disability-adjusted life years, underscoring its substantial global health and socioeconomic burden. This review critically examines the convergence of artificial intelligence (AI) and advanced oral drug delivery systems as an emerging strategy in schizophrenia management. Conventional diagnostic frameworks, reliant on subjective symptom assessment, often result in delayed or inaccurate diagnosis, while standard oral antipsychotics are limited by poor bioavailability, extensive first-pass metabolism, and inadequate brain targeting. Recent advances in AI, including natural language processing (NLP), neuroimaging analytics, electrophysiological modeling, and multi-omics integration, support diagnostic classification, risk prediction, symptom monitoring, and patient stratification. Simultaneously, nanotechnology-driven oral delivery platforms such as lipid nanoparticles, dendrimers, and proliposomes enhance pharmacokinetics, central nervous system targeting, and therapeutic adherence. The integration of AI with pharmacogenomics, wearable monitoring, and digital twin models further facilitates real-time dose optimization and personalized therapy. Despite promising preclinical and clinical outcomes, challenges related to data privacy, algorithmic bias, scalability, and regulatory translation persist. This review highlights a shift toward precision psychiatry, where AI-enabled diagnostics and smart oral therapeutics may support predictive, personalized, and adaptive care in schizophrenia.
DOI: https://doi.org/10.37349/eds.2026.1008165
This article belongs to the special issue Nanoformulations for Non-Intravenous Drug Delivery
Brazil harbors remarkable biological and cultural diversity, reflected in a rich body of traditional knowledge regarding the medicinal use of plants. This study synthesized ethnobotanical evidence on plants traditionally used for skin and wound healing in Brazil and examined their convergence with available antibacterial data. An integrative literature review identified twenty ethnobotanical studies, mainly involving rural populations and local residents, reporting 51 plant species traditionally used for skin and wound healing across 22 genera, predominantly native and mainly documented in the Northeastern and Northern regions. The most frequently cited species included Aloe vera (L.) Burm.f. and Anacardium occidentale L., followed by Stryphnodendron adstringens (Mart.) Coville. Fabaceae and Anacardiaceae concentrated the highest number of species with confirmed antibacterial activity, followed by Piperaceae and Euphorbiaceae, which also showed a high proportional representation of active species. A meaningful convergence between ethnobotanical use and experimental antibacterial evidence was observed for more than half of the plants, frequently against Staphylococcus aureus, a key pathogen in wound infections. Antibacterial data were predominantly derived from in vitro assays using non-standardized extracts, and only a limited number of studies reported possible mechanisms of action, such as membrane disruption and biofilm inhibition. Furthermore, few investigations evaluated antibacterial activity in infected wound models or quantified bacterial load reduction in vivo. Future studies should prioritize chemically standardized extracts, testing against resistant clinical strains and mature biofilm models, and validation of safety and therapeutic efficacy in clinical investigations. These findings reveal a gap between traditional use and clinically validated applications, underscoring the urgent need for standardized research approaches and reinforcing Brazil’s potential as a strategic reservoir of bioactive plant resources for primary health care. Addressing these limitations is essential to strengthening the translational basis for the rational use of medicinal plants in primary health care and public health contexts.
Brazil harbors remarkable biological and cultural diversity, reflected in a rich body of traditional knowledge regarding the medicinal use of plants. This study synthesized ethnobotanical evidence on plants traditionally used for skin and wound healing in Brazil and examined their convergence with available antibacterial data. An integrative literature review identified twenty ethnobotanical studies, mainly involving rural populations and local residents, reporting 51 plant species traditionally used for skin and wound healing across 22 genera, predominantly native and mainly documented in the Northeastern and Northern regions. The most frequently cited species included Aloe vera (L.) Burm.f. and Anacardium occidentale L., followed by Stryphnodendron adstringens (Mart.) Coville. Fabaceae and Anacardiaceae concentrated the highest number of species with confirmed antibacterial activity, followed by Piperaceae and Euphorbiaceae, which also showed a high proportional representation of active species. A meaningful convergence between ethnobotanical use and experimental antibacterial evidence was observed for more than half of the plants, frequently against Staphylococcus aureus, a key pathogen in wound infections. Antibacterial data were predominantly derived from in vitro assays using non-standardized extracts, and only a limited number of studies reported possible mechanisms of action, such as membrane disruption and biofilm inhibition. Furthermore, few investigations evaluated antibacterial activity in infected wound models or quantified bacterial load reduction in vivo. Future studies should prioritize chemically standardized extracts, testing against resistant clinical strains and mature biofilm models, and validation of safety and therapeutic efficacy in clinical investigations. These findings reveal a gap between traditional use and clinically validated applications, underscoring the urgent need for standardized research approaches and reinforcing Brazil’s potential as a strategic reservoir of bioactive plant resources for primary health care. Addressing these limitations is essential to strengthening the translational basis for the rational use of medicinal plants in primary health care and public health contexts.
DOI: https://doi.org/10.37349/eds.2026.1008164
This article belongs to the special issue Discovery and development of new antibacterial compounds
Aim:
This study investigated the anti-inflammatory effect of the extract and fractions of Eucalyptus camaldulensis and also profiled the secondary metabolites of its most active fraction.
Methods:
The leaves of E. camaldulensis were collected, authenticated and extracted with methanol. The extract (100, 200, and 400 mg/kg), normal saline (negative control), and aspirin (positive control) were administered orally to egg-induced paw oedema rats of five groups of five rats each. The extract was partitioned, and each of the solvent fractions was assayed for its anti-inflammatory activity. The results obtained were subjected to one-way analysis of variance (ANOVA) followed by Bonferroni post hoc tests, and p < 0.05 was considered significant. Also, the most active fraction was subjected to gas chromatography-mass spectrometry (GC-MS) analysis.
Results:
The extract at 100 mg/kg demonstrated the best anti-inflammatory effect at 29%, while the n-hexane (N-HEX) fraction gave the highest inflammatory inhibition at 43%. α-Phellandrene, o-cymene, n-hexadecanoic acid, and beta-sitosterol were identified as the most abundant compounds in the N-HEX fraction.
Conclusions:
The study concluded that the methanol extract of E. camaldulensis possesses good anti-inflammatory properties, and its non-polar fraction was responsible for the observed activity. Bioassay-guided purification of anti-inflammatory constituents of the N-HEX fraction is recommended for future studies.
Aim:
This study investigated the anti-inflammatory effect of the extract and fractions of Eucalyptus camaldulensis and also profiled the secondary metabolites of its most active fraction.
Methods:
The leaves of E. camaldulensis were collected, authenticated and extracted with methanol. The extract (100, 200, and 400 mg/kg), normal saline (negative control), and aspirin (positive control) were administered orally to egg-induced paw oedema rats of five groups of five rats each. The extract was partitioned, and each of the solvent fractions was assayed for its anti-inflammatory activity. The results obtained were subjected to one-way analysis of variance (ANOVA) followed by Bonferroni post hoc tests, and p < 0.05 was considered significant. Also, the most active fraction was subjected to gas chromatography-mass spectrometry (GC-MS) analysis.
Results:
The extract at 100 mg/kg demonstrated the best anti-inflammatory effect at 29%, while the n-hexane (N-HEX) fraction gave the highest inflammatory inhibition at 43%. α-Phellandrene, o-cymene, n-hexadecanoic acid, and beta-sitosterol were identified as the most abundant compounds in the N-HEX fraction.
Conclusions:
The study concluded that the methanol extract of E. camaldulensis possesses good anti-inflammatory properties, and its non-polar fraction was responsible for the observed activity. Bioassay-guided purification of anti-inflammatory constituents of the N-HEX fraction is recommended for future studies.
DOI: https://doi.org/10.37349/eds.2026.1008163
Advanced Therapy Medicinal Products (ATMPs) represent a transformative class of innovative therapies based on genes, cells, or engineered tissues that aim to modify, repair, or replace biological functions at a fundamental level. This review provides a foundational overview of ATMPs, addressing their scientific basis, regulatory classification, clinical translation, and key challenges for future development. The article outlines the four principal categories of ATMPs: gene therapy medicinal products, somatic cell therapy medicinal products, tissue-engineered products, and combined ATMPs, and discusses their distinct mechanisms of action and therapeutic applications. Recent clinical successes, including chimeric antigen receptor T-cell therapies, gene replacement therapies for inherited disorders, and tissue-engineered constructs for regenerative medicine, demonstrate the paradigm shift from symptomatic management towards disease modification or potential cure. However, the clinical implementation of ATMPs presents substantial challenges related to safety monitoring, long-term efficacy, complex manufacturing processes, regulatory evaluation, high treatment costs, and equitable patient access. Ethical considerations, including informed consent, long-term follow-up obligations, and global disparities in availability, further complicate their integration into routine clinical practice. Regulatory agencies have introduced adaptive pathways and accelerated approval mechanisms to facilitate timely patient access while maintaining rigorous standards of quality, safety, and efficacy. Continued technological innovation, coupled with sustainable healthcare policies and international collaboration, will be essential to realise the full therapeutic potential of ATMPs. As evidence accumulates from clinical trials and real-world use, ATMPs are expected to play an increasingly prominent role in modern medicine and the future of personalised healthcare.
Advanced Therapy Medicinal Products (ATMPs) represent a transformative class of innovative therapies based on genes, cells, or engineered tissues that aim to modify, repair, or replace biological functions at a fundamental level. This review provides a foundational overview of ATMPs, addressing their scientific basis, regulatory classification, clinical translation, and key challenges for future development. The article outlines the four principal categories of ATMPs: gene therapy medicinal products, somatic cell therapy medicinal products, tissue-engineered products, and combined ATMPs, and discusses their distinct mechanisms of action and therapeutic applications. Recent clinical successes, including chimeric antigen receptor T-cell therapies, gene replacement therapies for inherited disorders, and tissue-engineered constructs for regenerative medicine, demonstrate the paradigm shift from symptomatic management towards disease modification or potential cure. However, the clinical implementation of ATMPs presents substantial challenges related to safety monitoring, long-term efficacy, complex manufacturing processes, regulatory evaluation, high treatment costs, and equitable patient access. Ethical considerations, including informed consent, long-term follow-up obligations, and global disparities in availability, further complicate their integration into routine clinical practice. Regulatory agencies have introduced adaptive pathways and accelerated approval mechanisms to facilitate timely patient access while maintaining rigorous standards of quality, safety, and efficacy. Continued technological innovation, coupled with sustainable healthcare policies and international collaboration, will be essential to realise the full therapeutic potential of ATMPs. As evidence accumulates from clinical trials and real-world use, ATMPs are expected to play an increasingly prominent role in modern medicine and the future of personalised healthcare.
DOI: https://doi.org/10.37349/eds.2026.1008162
The global rise of antimicrobial resistance (AMR) has emerged as one of the most pressing threats to public health. This crisis calls for the urgent development of alternative therapeutic agents against antibiotic-resistant pathogens. Antimicrobial peptides (AMPs) are widely present in nature, with a broad range of effects and a low risk of causing drug resistance. Therefore, they are an ideal choice for the development of the next generation of antimicrobial drugs. To overcome the inefficiencies of traditional AMP discovery, artificial intelligence (AI) and machine learning (ML) technologies have been increasingly used to predict and design AMPs. Multiple AMP databases were used to train ML models for predicting the activity of AMPs or generating AMP sequences. This review briefly provides a comprehensive overview of AMP databases and computational tools, highlighting their capabilities and challenges. Future work should integrate larger datasets and experimental validation to accelerate clinical translation.
The global rise of antimicrobial resistance (AMR) has emerged as one of the most pressing threats to public health. This crisis calls for the urgent development of alternative therapeutic agents against antibiotic-resistant pathogens. Antimicrobial peptides (AMPs) are widely present in nature, with a broad range of effects and a low risk of causing drug resistance. Therefore, they are an ideal choice for the development of the next generation of antimicrobial drugs. To overcome the inefficiencies of traditional AMP discovery, artificial intelligence (AI) and machine learning (ML) technologies have been increasingly used to predict and design AMPs. Multiple AMP databases were used to train ML models for predicting the activity of AMPs or generating AMP sequences. This review briefly provides a comprehensive overview of AMP databases and computational tools, highlighting their capabilities and challenges. Future work should integrate larger datasets and experimental validation to accelerate clinical translation.
DOI: https://doi.org/10.37349/eds.2026.1008161
This article belongs to the special issue Discovery and development of new antibacterial compounds
Aim:
Two empirical methods were used to predict the absolute bioavailability (F) of medicines in adults and children following oral administration in the absence of intravenous (IV) dosing. This study systematically evaluates the predictive performance of Equation 1 to predict F in adults and children.
Methods:
Equation 3 [F = Q/(Q + CLoral)] was used for the prediction of F in adults and children. In Equation 3, clearance is the observed oral clearance following oral administration of a medicine and Q is either liver blood or plasma flow rate. The predictive performance of Equation 3 was evaluated in adults and children for three categories of medicines; medicines which are mainly metabolized in the liver, medicines which are metabolized both in the liver and the gut, and medicines which are mainly renally excreted. From the literature, oral clearance and F values for adults and children were obtained. The predictive performance of these two methods (blood or plasma flow rate) was assessed by comparing the predicted F of the medicines used in this study with the observed F (obtained from clinical studies).
Results:
More than 90% predicted F values were within 0.5–2-fold prediction error in adults and children by both methods for all three categories of medicines. Plasma flow rate provided slightly better results than the blood flow rate.
Conclusions:
The proposed methods indicate that the estimation of F of medicines in adults and children is possible with reasonable accuracy (within 0.5–2-fold prediction error). The method is useful to estimate F, especially in children, because it is not ethical to administer medicines by both IV and oral routes to children just for the sake of estimating F.
Aim:
Two empirical methods were used to predict the absolute bioavailability (F) of medicines in adults and children following oral administration in the absence of intravenous (IV) dosing. This study systematically evaluates the predictive performance of Equation 1 to predict F in adults and children.
Methods:
Equation 3 [F = Q/(Q + CLoral)] was used for the prediction of F in adults and children. In Equation 3, clearance is the observed oral clearance following oral administration of a medicine and Q is either liver blood or plasma flow rate. The predictive performance of Equation 3 was evaluated in adults and children for three categories of medicines; medicines which are mainly metabolized in the liver, medicines which are metabolized both in the liver and the gut, and medicines which are mainly renally excreted. From the literature, oral clearance and F values for adults and children were obtained. The predictive performance of these two methods (blood or plasma flow rate) was assessed by comparing the predicted F of the medicines used in this study with the observed F (obtained from clinical studies).
Results:
More than 90% predicted F values were within 0.5–2-fold prediction error in adults and children by both methods for all three categories of medicines. Plasma flow rate provided slightly better results than the blood flow rate.
Conclusions:
The proposed methods indicate that the estimation of F of medicines in adults and children is possible with reasonable accuracy (within 0.5–2-fold prediction error). The method is useful to estimate F, especially in children, because it is not ethical to administer medicines by both IV and oral routes to children just for the sake of estimating F.
DOI: https://doi.org/10.37349/eds.2026.1008160
Antimicrobial resistance (AMR) poses a growing global health threat, progressively undermining the clinical effectiveness of conventional antibiotic therapies. Despite their proven efficacy and standardized clinical frameworks, antibiotics exert strong selective pressures that accelerate resistance, disrupt host microbiota, and limit treatment options for chronic, biofilm-associated, and multidrug-resistant infections. Bacteriophage therapy has re-emerged as a potential adjunct or alternative approach, offering pathogen-specific antibacterial activity, preservation of commensal microbiota, and the capacity for co-evolution with bacterial hosts. This focused review critically compares antibiotics and bacteriophage therapy across mechanistic foundations, preclinical and clinical evidence, translational readiness, and real-world implementation challenges. While preclinical models consistently demonstrate robust antibacterial activity of bacteriophages, clinical evidence remains heterogeneous, with few randomized controlled studies available. Key system-level barriers, including regulatory inconsistency, manufacturing complexity, and lack of standardization, currently limit widespread clinical integration. Rather than positioning bacteriophages as replacements for antibiotics, this review emphasizes their potential role as complementary agents, particularly through bacteriophage-antibiotic synergy, to enhance treatment efficacy and mitigate resistance. Addressing methodological gaps, standardizing clinical trial designs, and developing integrated stewardship models will be critical to defining the future role of bacteriophage therapy in modern infectious disease management.
Antimicrobial resistance (AMR) poses a growing global health threat, progressively undermining the clinical effectiveness of conventional antibiotic therapies. Despite their proven efficacy and standardized clinical frameworks, antibiotics exert strong selective pressures that accelerate resistance, disrupt host microbiota, and limit treatment options for chronic, biofilm-associated, and multidrug-resistant infections. Bacteriophage therapy has re-emerged as a potential adjunct or alternative approach, offering pathogen-specific antibacterial activity, preservation of commensal microbiota, and the capacity for co-evolution with bacterial hosts. This focused review critically compares antibiotics and bacteriophage therapy across mechanistic foundations, preclinical and clinical evidence, translational readiness, and real-world implementation challenges. While preclinical models consistently demonstrate robust antibacterial activity of bacteriophages, clinical evidence remains heterogeneous, with few randomized controlled studies available. Key system-level barriers, including regulatory inconsistency, manufacturing complexity, and lack of standardization, currently limit widespread clinical integration. Rather than positioning bacteriophages as replacements for antibiotics, this review emphasizes their potential role as complementary agents, particularly through bacteriophage-antibiotic synergy, to enhance treatment efficacy and mitigate resistance. Addressing methodological gaps, standardizing clinical trial designs, and developing integrated stewardship models will be critical to defining the future role of bacteriophage therapy in modern infectious disease management.
DOI: https://doi.org/10.37349/eds.2026.1008159
