Search Results (91)

Background: Bipolar disorder (BD) is a chronic and disabling psychiatric condition characterized by recurring episodes of mania, hypomania, and depression. Despite the availability of mood stabilizers, antipsychotics, and antidepressants, long-term management remains challenging due to incomplete symptom control, adverse effects, and high relapse rates. Methods: This paper is a narrative review aimed at synthesizing emerging trends and future directions in the pharmacological treatment of BD. Results: Future pharmacotherapy for BD is likely to shift toward precision medicine, leveraging advances in genetics, biomarkers, and neuroimaging to guide personalized treatment strategies. Novel drug development will also target previously underexplored mechanisms, such as inflammation, mitochondrial dysfunction, circadian rhythm disturbances, and glutamatergic dysregulation. Physiological endophenotypes, such as immune-metabolic profiles, circadian rhythms, and stress reactivity, are emerging as promising translational tools for tailoring treatment and reducing associated somatic comorbidity and mortality. Recognition of the heterogeneous longitudinal trajectories of BD, including chronic mixed states, long depressive episodes, or intermittent manic phases, has underscored the value of clinical staging models to inform both pharmacological strategies and biomarker research. Disrupted circadian rhythms and associated chronotypes further support the development of individualized chronotherapeutic interventions. Emerging chronotherapeutic approaches based on individual biological rhythms, along with innovative monitoring strategies such as saliva-based lithium sensors, are reshaping the future landscape. Anti-inflammatory agents, neurosteroids, and compounds modulating oxidative stress are emerging as promising candidates. Additionally, medications targeting specific biological pathways implicated in bipolar pathophysiology, such as N-methyl-D-aspartate (NMDA) receptor modulators, phosphodiesterase inhibitors, and neuropeptides, are under investigation. Conclusions: Advances in pharmacogenomics will enable clinicians to predict individual responses and tolerability, minimizing trial-and-error prescribing. The future landscape may also incorporate digital therapeutics, combining pharmacotherapy with remote monitoring and data-driven adjustments. Ultimately, integrating innovative drug therapies with personalized approaches has the potential to enhance efficacy, reduce adverse effects, and improve long-term outcomes for individuals with bipolar disorder, ushering in a new era of precision psychiatry. Full article

Background/Objectives: This study examines the effectiveness of train-time computation, test-time computation, and their combination on the performance of large language modeling applied to an electronic medical record quality management system. It identifies the most effective combination of models to enhance clinical documentation performance and efficiency. Methods: A total of 597 clinical medical records were selected from the MEDEC-MS dataset, 10 of which were used for prompt engineering to guide model training. Eight large language models were employed for training, focusing on train-time computation and test-time computation. Model performance on specific error types was assessed using precision, recall, F1 score, and error correction accuracy. The dataset was divided into training and testing sets in a 7:3 ratio. The assembly model was created using binary logistic regression for assembly analysis of the top-performing models. Its performance was evaluated using area under the curve values and model weights. Results: GPT-4 and Deepseek R1 demonstrated higher overall accuracy in detecting errors. Models that focus on train-time computation exhibited shorter reasoning times and stricter error detection, while models emphasizing test-time computation achieved higher error correction accuracy. The GPT-4 model was particularly effective in addressing issues related to causal organisms, management, and pharmacotherapy, whereas models focusing on test-time computation performed better in tasks involving diagnosis and treatment. The assembly model, focusing on both train-time computation and test-time computation, outperformed any single large language model (Assembly model accuracy: 0.690 vs. GPT-4 accuracy: 0.477). Conclusions: Models focusing on train-time computation demonstrated greater efficiency in processing speed, while models focusing on test-time computation showed higher accuracy and interpretability in identifying and detecting quality issues in electronic medical records. Assembling the train-time and test-time computation strategies may strike a balance between high accuracy and model efficiency, thereby enhancing the development of electronic medical records and improving medical care. Full article

Increasing evidence demonstrates the mutualistic connection between the microbiome and acute myeloid leukemia (AML) treatment. Drugs disrupt the microbial balance and, conversely, changes in the microbiome influence therapy. A new field, pharmacomicrobiomics, examines the role of the microbiome in pharmacokinetics, pharmacodynamics, and drug toxicity. The multimodal therapeutic management of AML, along with disease-related immunosuppression, infection, and malnutrition, creates the unique microbial profile of AML patients, in which every delicate modification plays a crucial role in pharmacotherapy. While both preclinical and real-world data have confirmed a bilateral connection between standard chemotherapy and the microbiome, the impact of novel targeted therapies and immunotherapy remains unknown. Multi-omics technologies have provided qualitative and mechanistic insights into specific compositional and functional microbial signatures associated with the outcomes of AML therapy, but require a large-scale investigation to draw reliable conclusions. In this review, we outline the role of the microbiome within the therapeutic landscape of AML, focusing on the determinants of post-treatment dysbiosis and its effects on the therapeutic response and toxicity. We explore emerging strategies for microbiota modulation, highlighting their safety and efficacy. Advances in microbiome-based approaches are an inevitable step toward precision medicine in AML. However, clinical research in a well-defined group of immunocompromised patients is needed to study their variable effects on human health and determine safety issues. Full article

Rising morbidity and mortality from cardiovascular disease (CVD) have increased interest in precision and preventive management to reduce long-term sequelae. While retinal imaging has traditionally been recognized for identifying vascular changes in systemic conditions such as hypertension and type 2 diabetes mellitus, a new ophthalmologic field, cardiac-oculomics, has associated retinal biomarker changes with other cardiovascular diseases with retinal manifestations. Several imaging modalities visualize the retina, including color fundus photography (CFP), optical coherence tomography (OCT), and OCT angiography (OCTA), which visualize the retinal surface, the individual retinal layers, and the microvasculature within those layers, respectively. In these modalities, imaging-derived biomarkers can present due to CVD and have been linked to the presence, progression, or risk of developing a range of CVD, including hypertension, carotid artery disease, valvular heart disease, cerebral infarction, atrial fibrillation, and heart failure. Promising artificial intelligence (AI) models have been developed to complement existing risk-prediction tools, but standardization and clinical trials are needed for clinical adoption. Beyond risk estimation, there is growing interest in assessing real-time cardiovascular status to track vascular changes following pharmacotherapy, surgery, or acute decompensation. This review offers an up-to-date assessment of the cardiac-oculomics literature and aims to raise awareness among cardiologists and encourage interdepartmental collaboration. Full article

Diabetic kidney disease (DKD), a well-characterized microvascular complication associated with the progression of diabetes mellitus, has been identified as the leading etiological factor contributing to the global burden of end-stage kidney disease (ESKD). Historically, DKD research has predominantly centered on glomerular mechanisms; however, recent studies have increasingly emphasized the critical role of tubular dysfunction. Extensive evidence has elucidated the key pathological drivers of tubular injury in DKD, encompassing metabolic dysregulation, pro-inflammatory signaling pathways, diverse cellular stress responses, and epithelial–mesenchymal transition (EMT). Furthermore, emerging mechanistic studies reveal that autophagic flux impairment and epigenetic memory formation collaboratively drive cellular senescence in DKD. Regarding the treatment of DKD, various hypoglycemic drugs, as well as hypotensive drugs, and microcirculatory improvers have garnered significant attention. Recently, stem cell-based interventions and precision gene editing techniques have unveiled novel therapeutic paradigms for DKD, fundamentally expanding the treatment arsenal beyond conventional pharmacotherapy. This review synthesizes updated insights into the pathogenesis of tubular injury in DKD and highlights promising therapeutic strategies for managing this condition. Full article

Emerging evidence highlights the gut microbiota as a pivotal determinant of pharmacological efficacy. While Enterococcus faecalis (E. faecalis)-derived tyrosine decarboxylases (tyrDCs) are known to decarboxylate levodopa (L-dopa), compromising systemic bioavailability, the causal mechanisms underlying microbiota-mediated pharmacodynamic variability remain unresolved. In our study, we employed antibiotic-induced microbiota depletion and fecal microbiota transplantation (FMT) to interrogate microbiota-L-dopa interactions in MPTP-induced Parkinson’s disease (PD) mice. The study demonstrated that antibiotic-mediated microbiota depletion enhances L-dopa bioavailability and striatal dopamine (DA) level, correlating with improved motor function. To dissect clinical heterogeneity in the L-dopa response, PD patients were stratified into moderate responders and good responders following standardized L-dopa challenges. In vitro bioconversion assays revealed greater L-dopa-to-DA conversion in fecal samples from moderate responders versus good responders. FMT experiments confirmed mice receiving good-responder microbiota exhibited enhanced L-dopa bioavailability, higher striatal DA concentrations, and a heightened therapeutic effect of L-dopa relative to moderate-responder recipients. Collectively, our study provided evidence that the gut microbiota directly modulates L-dopa metabolism and microbial composition determines interindividual therapeutic heterogeneity. Targeted microbial modulation—through precision antibiotics or donor-matched FMT—is a viable strategy to optimize PD pharmacotherapy, supporting the potential for microbiota-targeted adjuvant therapies in PD management. Full article

Liver cirrhosis continues to be a major global health issue, contributing to high morbidity and mortality due to its progressive nature and associated complications. This review explores recent advancements in the diagnosis and treatment of liver cirrhosis and its related syndromes. Non-invasive diagnostic tools, such as elastography and serum biomarkers, have significantly improved early detection, reducing the need for liver biopsies. Advanced imaging techniques, including MRI and CT, further enhance diagnostic accuracy. In parallel, molecular and genomic research is providing new insights into the pathogenesis of the disease, paving the way for precision medicine. On the treatment front, pharmacological innovations, such as antifibrotic agents and targeted therapies, show promise in slowing disease progression. Endoscopic interventions like variceal banding are improving the management of complications, while advancements in liver transplantation and artificial liver support systems offer life-saving alternatives. Regenerative medicine, particularly stem cell therapy and tissue engineering, is emerging as a promising strategy for liver repair. Managing cirrhosis-related syndromes, including portal hypertension, ascites, hepatic encephalopathy, and hepatorenal syndrome, now involves evolving therapeutic approaches such as transjugular intrahepatic portosystemic shunt (TIPS) and novel pharmacotherapies. Prognostic scoring systems like the MELD and Child–Pugh are being refined with new biomarkers for better risk stratification. The future of cirrhosis care will likely involve the integration of artificial intelligence and machine learning for early diagnosis and personalized treatments, alongside emerging therapies currently under investigation. Despite these advancements, challenges such as costs, accessibility, and healthcare disparities remain barriers to widespread adoption. This review highlights the importance of incorporating innovative diagnostic and therapeutic strategies into clinical practice to improve the outcomes for patients with liver cirrhosis and its complications. Full article

Background: The primary treatment of schizophrenia is pharmacotherapy with antipsychotic agents, such as risperidone and paliperidone. Population pharmacokinetic (PopPK) modelling plays a crucial role in optimising therapy by predicting of plasma concentrations, therapeutic efficacy, and the risk of adverse effects using model informed precision dosing. Objectives: This systematic review examined the PopPK models of risperidone and paliperidone in patients diagnosed with schizophrenia based on the available scientific evidence. Methods: A systematic review of the health science databases was conducted. The inclusion criteria were original articles published in peer-reviewed journals, studies focusing on the development of original PopPK models of risperidone and paliperidone, and clinical studies. The exclusion criteria were full-text articles that could not be retrieved; studies not including subjects diagnosed with schizophrenia or schizoaffective disorders; and studies that did not investigate risperidone or paliperidone. Results: A total of 19 studies developing PopPK models were analysed, including one- or two-compartment PopPK model structures. Interindividual variability in the pharmacokinetic parameters was shown to be influenced by factors such as CYP2D6 activity, renal function, body mass index, and sex. Parameter estimation revealed high variability in clearance and volume of distribution. Conclusion: Numerous PopPK models for risperidone and paliperidone have been published with a detailed characterisation of absorption, metabolism, and elimination. Therefore, future research should focus on the external validation of these models to facilitate their integration into clinical practice and optimise individualised dosing, ultimately improving treatment efficacy and safety across diverse patient populations. Full article

Dronedarone (DRO) is an antiarrhythmic drug that should be used under close supervision, and therapeutic drug monitoring (TDM) may be one of the tools supporting pharmacotherapy. The aim of our study was to develop an economical HPLC method for determining DRO and its active metabolite debutyldronedarone (DBD) in human plasma. An HPLC isocratic system with a manual injector was applied. The separation was performed on a Supelcosil LC-CN column (150 × 4.6 mm, 5 µm) at an ambient temperature. The mobile phase was a mixture of CH₃OH:CH₃CN:H₂O:0.5 M KH₂PO₄ (170:85:237.2:7.8 (v/v)) + 0.1 mL 85% H₃PO₄ pumped at a flow rate of 1.8 mL/min. The UV detection was set at λ = 290 nm. A methyl tert-butyl ether was used for the extraction from a 0.4 mL alkalized plasma sample. The analytes were eluted at retention times of 4.0 min, 5.2 min and 6.0 min for DBD, internal standard bepridil and DRO, respectively. The method was calibrated in the range of 10–1000 ng/mL for both DRO and DBD. The adequate specificity, accuracy and precision were demonstrated in accordance with EMA guidelines, i.e., ≤15% (≤20% for the LLOQ), which ensures the reliability of the measurements. This method can be recommended for laboratories with basic HPLC equipment for TDM, adherence assessments and even in PK studies during chronic DRO therapy. Full article

Background/Objectives: Lung cancer has a high mortality rate worldwide, with non-small cell lung cancer (NSCLC) being the most prevalent. Carboplatin and paclitaxel are key treatments for NSCLC; however, adverse drug reactions (ADRs) pose significant challenges. This study examined the impact of genetic variations in ABCB1 and ABCC2 genes on the incidence of ADRs and survival in NSCLC patients treated with carboplatin and paclitaxel. Methods: Variants were identified using RT-PCR, and ADRs classified according to the Common Toxicity Criteria for Adverse Events, Version 4.03. Results: The ABCB1 rs1128503 (c.1236C>T) CC genotype was associated with a higher chance of nausea (OR: 3.5, 95% CI 1.367–9.250, p = 0.0093), vomiting (OR: 13.553, 95% CI 1.705–107.723, p = 0.0137), and a higher risk of death in CT or TT genotypes (HR: 1.725, 95% CI 1.036–2.871, p = 0.0361). The ABCC2 rs717620 (c.-24C>T) TT genotype was associated with increased ALP levels (OR: 14.6, 95% CI 1.234–174.236, p = 0.0335). The ABCB1 rs2032582 non-CC genotypes (TT+AA+TA+CA+CT) were associated with an increased risk of death (HR: 1.922, 95% CI 1.093–3.377, p = 0.0232). Patients with hypocalcemia (HR: 2.317, 95% IC 1.353–3.967, p = 0.022), vomiting (HR: 3.047, 95% IC 1.548–5.997, p = 0.0013), and diarrhea (HR: 2.974, 95% IC 1.590–5.562, p = 0.0006) were associated with lower overall survival. Conclusions: The data suggest that ABCB1 variants may influence gastrointestinal ADRs and patient survival, highlighting the importance of pharmacogenomics in predicting ADRs and drug resistance. This approach offers more precise pharmacotherapy, reduces ADRs, and enhances the patients’ quality of life and survival. Full article

Lennox–Gastaut syndrome (LGS) is a severe childhood-onset developmental and epileptic encephalopathy characterized by multiple drug-resistant seizure types, cognitive impairment, and distinctive electroencephalographic patterns. Current treatments primarily focus on symptom management through antiseizure medications (ASMs), dietary therapy, epilepsy surgery, and neuromodulation, but often fail to address the underlying pathophysiology or improve cognitive outcomes. As genetic causes are identified in 30–40% of LGS cases, precision therapeutics targeting specific molecular mechanisms are emerging as promising disease-modifying approaches. This narrative review explores precision therapeutic strategies for LGS based on molecular pathophysiology, including channelopathies (SCN2A, SCN8A, KCNQ2, KCNA2, KCNT1, CACNA1A), receptor and ligand dysfunction (GABA/glutamate systems), cell signaling abnormalities (mTOR pathway), synaptopathies (STXBP1, IQSEC2, DNM1), epigenetic dysregulation (CHD2), and CDKL5 deficiency disorder. Treatment modalities discussed include traditional ASMs, dietary therapy, targeted pharmacotherapy, antisense oligonucleotides, gene therapy, and the repurposing of existing medications with mechanism-specific effects. Early intervention with precision therapeutics may not only improve seizure control but could also potentially prevent progression to LGS in susceptible populations. Future directions include developing computable phenotypes for accurate diagnosis, refining molecular subgrouping, enhancing drug development, advancing gene-based therapies, personalizing neuromodulation, implementing adaptive clinical trial designs, and ensuring equitable access to precision therapeutic approaches. While significant challenges remain, integrating biological insights with innovative clinical strategies offers new hope for transforming LGS treatment from symptomatic management to targeted disease modification. Full article

Background/Objectives: This review examines the role of pharmacogenomics in individual responses to the pharmacotherapy of various drugs of abuse, including alcohol, cocaine, and opioids, to identify genetic variants that contribute to variability in substance use disorder treatment outcomes. In addition, it explores the pharmacomicrobiomic aspects of substance use, highlighting the impact of the gut microbiome on bioavailability, drug metabolism, pharmacodynamics, and pharmacokinetics. Results: Research on pharmacogenetics has identified several promising genetic variants that may contribute to the individual variability in responses to existing pharmacotherapies for substance addiction. However, the interpretation of these findings remains limited. It is estimated that genetic factors may account for 20–95% of the variability in individual drug responses. Therefore, genetic factors alone cannot fully explain the differences in drug responses, and factors such as gut microbiome diversity may also play a significant role. Drug microbial biotransformation is produced by microbial exoenzymes that convert low molecular weight organic compounds into analogous compounds by oxidation, reduction, hydrolysis, condensation, isomerization, unsaturation, or by the introduction of heteroatoms. Despite significant advances in pharmacomicrobiomics, challenges persist including the lack of standardized methodologies, inter-individual variability, limited understanding of drug biotransformation mechanisms, and the need for large-scale validation studies to develop microbiota-based biomarkers for clinical use. Conclusions: Progress in the pharmacogenomics of substance use disorders has provided biological insights into the pharmacological needs associated with common genetic variants in drug-metabolizing enzymes. The gut microbiome and its metabolites play a pivotal role in various stages of drug addiction including seeking, reward, and biotransformation. Therefore, integrating pharmacogenomics with pharmacomicrobiomics will form a crucial foundation for significant advances in precision and personalized medicine. Full article

Insulin resistance (IR) is a significant factor in the development and progression of metabolic-related diseases like dyslipidemia, T2DM, hypertension, nonalcoholic fatty liver disease, cardiovascular and cerebrovascular disorders, and cancer. The pathogenesis of IR depends on multiple factors, including age, genetic predisposition, obesity, oxidative stress, among others. Abnormalities in the insulin-signaling cascade lead to IR in the host, including insulin receptor abnormalities, internal environment disturbances, and metabolic alterations in the muscle, liver, and cellular organelles. The complex and multifaceted characteristics of insulin signaling and insulin resistance envisage their thorough and comprehensive understanding at the cellular and molecular level. Therapeutic strategies for IR include exercise, dietary interventions, and pharmacotherapy. However, there are still gaps to be addressed, and more precise biomarkers for associated chronic diseases and lifestyle interventions are needed. Understanding these pathways is essential for developing effective treatments for IR, reducing healthcare costs, and improving quality of patient life. Full article

Introduction: The International Classification of Orofacial Pain (ICOP) recognizes orofacial migraine (OFM) and neurovascular orofacial pain (NVOP) as migraine-related entities affecting the facial and oral regions. The diagnostic features of OFM and NVOP indicate that there are many similarities between the two. However, we recently demonstrated that NVOP and OFM are two distinct diagnostic entities, confirming the ICOP classification. It was the aim of the present study to examine whether OFM and NVOP differ in response to pharmacotherapy. Materials and Methods: The cohort was made up of 40 patients attending a tertiary orofacial pain clinic. When implementing ICOP criteria, an OFM diagnosis was made in 23 and an NVOP diagnosis in 17. Results: No statistically significant differences between NVOP versus OFM were observed in the global response to standard abortive therapy such as triptans, or NSAIDs. Similarly, no statistically significant differences were found following prophylactic therapy that included beta-blockers, anti-epileptic drugs, and tricyclic antidepressants. Up to 80% of patients responded favorably with ≥50% pain reduction. Conclusions: NVOP and OFM differ in diagnostic characteristics, demonstrating unique features, and were confirmed as two diagnostic entities. However, NVOP and OFM did not differ in their response to abortive or prophylactic treatments. Study limitations include the lack of starting data precluding a more precise pharmacological analysis. The small sample size limits any far reaching conclusions. This is particularly true regarding individual drug efficacy. We were unable to analyze drug and dose responses separately due to data constraints. Full article

“Sundowning syndrome” refers to the evening decline in mental state among cognitively impaired patients. This phenomenon is well known, but it is not entirely understood. Its prevalence ranges from 1.6% to 66% of patients with dementia. Development of SS relies on neurodegeneration, the presence of sleep disorders, circadian rhythm of patients’ activities, and mood disorders. Therefore, patients with SS need very precise diagnostic workup aiming at defining the exact cause of the syndrome. Potential therapeutic modalities include behavioral and environmental interventions and pharmacological approaches. Pharmacotherapy with sedatives can by effective but is related to severe side effects. Behavioral interventions are more efficacious but require intense involvement of caregivers. This article discusses the biological processes that may underlie SS and proposes potential diagnostic procedures and therapeutic interventions. Full article