Cts-Clinical and Translational Science最新文献

Natural AAV serotypes often lack specificity and efficiency, leading to off-target effects and a low therapeutic index. To overcome these limitations of naturally occurring serotypes, there has been a keen interest in the field to engineer novel capsids to enhance tissue and cell-specific targeting, resulting in a high number of published literature reports over the past few years. To ensure a systematic review and illustrate advances in engineered capsids that enhance specificity and efficiency, we used Natural Language Processing with Linguamatics i2E to identify neurotropic and ocular AAV capsids tested in non-human primates. By querying PubMed abstracts for specific mentions of AAVs, administration routes, and organ/tissue/species, we obtained 5907 hits, refined through an optimized process to 36 relevant and unique abstracts. Notable findings include numerous novel capsids summarized by route of administration: (1) systemic administration, targeting the central nervous system (e.g., AAV-PHP.eB, AAV X1.1, and AAV.PAL2), (2) direct central nervous system injection (e.g., AAV2.Retro, Olig001, and AAV2.1A), and (3) ocular administration (e.g., AAV.44.9 (E531D), rAAV2tYF, and Anc80L65). Such engineered capsids exhibit enhanced tissue specificity, improved pharmacokinetics and pharmacodynamics, or reduced off-target effects compared to the parent serotypes. Our study provides insight into state-of-the-art translational and drug-development considerations for engineered neurotropic and ocular capsids. We also highlight the effectiveness of Natural Language Processing and Large Language Models as tools in identifying and characterizing engineered neurotropic and ocular AAV capsids to summarize this rapidly growing class of drugs and area of therapeutics.

Pharmacogenomic (PGx) testing using multi-gene panels (mgPGx) is documented to improve clinical outcomes; however, real-world data on its economic impact remain limited. This study aimed to evaluate the utility and economic value of mgPGx testing among Medicare patients within a community-based health system. We identified Medicare Advantage patients within the primary care setting of a community-based health system hospital who were taking ≥ 1 PGx-guided medication using a stratification algorithm. In total, 1042 patients participated in mgPGx testing. We evaluated the prevalence of PGx medications, polypharmacy involving PGx medications, and actionable results (i.e., a phenotype with PGx guidance and a relevant PGx medication). A Total Cost of Care (TCOC) analysis was performed for a subset of patients (n = 548) who underwent PGx testing and were matched to a control group that did not undergo PGx testing using propensity score matching. Total medical expenses over 12 months, both before and after testing, were compared. Forty-four percent (n = 454/1042) of patients were ≥ 3 PGx-guided medications. Over one-third of patients who were on ≥ 3 PGx medications had ≥ 2 actionable results (35.5%, n = 161/454). The TCOC analysis demonstrated a trend toward a net cost savings of $1827 per member per year (PMPY), with $1582 in medical savings and $245 in pharmacy savings. Polypharmacy with PGx medications is prevalent, and mgPGx led to cost savings. Further research with a larger sample size is needed to replicate the results and assess the long-term impact on healthcare utilization and costs.

The onset of the global COVID-19 pandemic created an urgent need for therapeutic monoclonal antibody (mAb) development, while the rapid mutation of the SARS-CoV-2 virus and emergence of new variants presented a moving target for validation of efficacy. Since it is virtually impossible to conduct randomized controlled trials in the context of a continually evolving variant landscape, other sources of data can inform ongoing effectiveness and appropriate dosing of existing treatments against new variants. This may include data from in vitro neutralization testing, real-world studies, and clinical pharmacology studies. There are various clinical pharmacology approaches available to aid in dose selection of COVID-19 mAbs, and the approach used for initial dose selection may differ from that used to justify dose modifications in light of new variants. At present, there is no universally accepted approach that has been shown to work in all circumstances, and most of the available methods lack validation against clinical data. Here, we provide an overview of the different pharmacological approaches available for mAb dose selection or dose adjustments, outlining advantages and limitations of each as well as assumptions, data requirements, and key learnings for each method based on experiences with COVID-19 mAb development over the last 4 years. Future mAb development programs for COVID-19 or other viral infections with pandemic potential should take into consideration lessons learned from the COVID-19 pandemic and devise clinical development programs that generate data to help address new emerging variants of concern in a rapidly evolving virus landscape.

Chronic kidney disease is a progressive condition with limited therapeutic options in its advanced stages. Adipose-derived stem cell therapy has shown potential in preclinical studies for renal repair. This study evaluated the short-term stability of renal function in patients with moderate to severe chronic kidney disease who received adipose-derived stem cell therapy, using a matched control group derived from real-world clinical data for comparison. A total of 34 treated patients were matched in a one-to-five ratio with 170 control patients based on key clinical characteristics. The primary outcomes included the mean percentage change in estimated glomerular filtration rate and the incidence of renal function decline exceeding defined thresholds. To enhance the robustness of treatment effect estimation, real-world data were utilized to construct an external control group that closely resembled the clinical trial population. This approach allowed indirect treatment comparisons and strengthened the internal validity of findings in the absence of randomization. Results demonstrated that the treated group exhibited a more stable renal function trajectory and a significantly lower risk of deterioration compared to the control group, particularly in patients with more advanced disease. Among dose groups, the low-dose group showed the greatest stability in renal function. These findings support the feasibility of using real-world data to construct external comparators and suggest that stem cell therapy may offer a short-term stabilizing effect on renal function. Further research is needed to validate these findings and explore their long-term clinical implications.

Trial Registration: ClinicalTrials.gov identifier: NCT02933827 (registered October 13, 2016. https://clinicaltrials.gov/study/NCT02933827)

Janus kinase inhibitors (JAKIs) are immunomodulatory drugs used for autoimmune and inflammatory conditions. Their potential impact on pregnancy and fetal development remains a concern due to placental transfer and potential disruption of cytokine and growth factor signaling, with limited human data. This study analyzed VigiBase, the World Health Organization global pharmacovigilance database of individual case safety reports (ICSRs), to assess signals of disproportionate reporting (SDRs) for pregnancy-related adverse drug reactions (ADRs) reported with systemic JAKIs, including abrocitinib, baricitinib, deucravacitinib, fedratinib, filgotinib, itacitinib, momelotinib, pacritinib, peficitinib, ritlecitinib, ruxolitinib, tofacitinib, and upadacitinib. As of May 26, 2024, 163 ICSRs met inclusion criteria, mainly from North America (41.7%) and Europe (39.3%). The most frequently reported JAKIs were tofacitinib (44.8%) and upadacitinib (34.4%), primarily indicated for rheumatoid arthritis (29.4%). Among 213 pregnancy-related ADRs, spontaneous abortion was the most frequently reported event (47.9%) without representing an SDR compared with other drugs in the database (reporting odds ratio [ROR] 0.37, 95% confidence interval [CI] 0.30–0.46). Congenital anomalies were reported in 16.0% of ICSRs (43 events), but no specific organ-related patterns were identified. Prematurity occurred in 9.2% of ICSRs, without SDR compared to the full database (ROR 0.07, 95% CI 0.04–0.11). Current pharmacovigilance data from VigiBase do not indicate SDRs for spontaneous abortion or prematurity following JAKI exposure during pregnancy. Findings should be interpreted cautiously given the limitations of spontaneous reporting systems and the exploratory nature of the analysis. Further studies are needed to better characterize the JAKI safety in pregnancy.

We assessed the predictive value of MAdCAM-1 expression on response to vedolizumab in patients with inflammatory bowel disease. This was a retrospective, single-center, cohort study including 109 patients with pretreatment inflammation who completed at least three doses of vedolizumab. We described clinical and endoscopic outcomes of patients based on MAdCAM-1 expression. There was no significant difference in MAdCAM-1 expression when stratified by histology. Patients in clinical remission at 14 weeks had significantly lower median baseline MAdCAM-1 expression (37425.3 vs. 46278.9, p < 0.015). There was no difference in pretreatment MAdCAM-1 expression among patients who later achieved endoscopic or biologic response. In the posttreatment cohort, lower MAdCAM-1 expression was associated with an increased likelihood of endoscopic or biologic response (36719.5 vs. 44229.9, p < 0.038). However, posttreatment MAdCAM-1 expression did not significantly differ when stratified for clinical remission at 14 weeks. Ultimately, MAdCAM-1 immunohistochemistry has limited utility as a predictive biomarker but may provide insights into vedolizumab-associated bowel healing.

Malnutrition implies a decline in the systemic status and organ function, which is closely related to sarcopenia, frailty, osteoporosis, and prognosis. Diabetes medications work in a multifaceted manner on various tissues, such as the pancreas, muscle, liver, and adipose tissue; these medications affect metabolism, which in turn affects nutritional status. This study aimed to determine the effect of diabetes medications on the scores of the Geriatric Nutrition Risk Index (GNRI) and Controlling Nutritional Status (CONUT) nutritional indices, both cross-sectionally and longitudinally. This cross-sectional study included 2146 individuals who were prescribed diabetes medications. Multivariate analysis showed that both GNRI and CONUT scores tended to be improved in patients using sodium-glucose cotransporter 2 inhibitors (SGLT2i), dipeptidyl peptidase 4 inhibitors (DPP4i), or biguanide (BG). Additionally, propensity score matching of nutrition-related laboratory values was performed to assess the variation in nutritional indices over time, which resulted in less deterioration of the GNRI in the SGLT2i and BG groups. In conclusion, this study suggests that SGLT2i and BG prevent the progression of malnutrition and may help in selecting drugs that consider the nutritional status of patients.

Physiologically-based pharmacokinetic (PBPK) modeling has become a major tool in drug discovery and development. Here, we describe the bottom-up PBPK modeling approaches employed at AbbVie using Simcyp Simulator and evaluate the impact of three system parameters, GI physiology, P-gp Relative Expression Factor (REF), and recombinant CYP enzyme (rCYP) intersystem extrapolation factor (ISEF), independently and in combination, on PBPK prediction performance through retrospective analysis of 8 clinical assets. Overall, the application of New GI physiology resulted in a considerable improvement in the prediction of oral absorption for most compounds compared to the Original GI physiology (C_max: 76% vs. 43% within 3-fold) when using the default P-gp REF (1.5) and adjusted ISEF. Decreasing P-gp REF to 0.5 resulted in additional improvement in the predictions of C_max for P-gp substrates (86% within 3-fold). The observed plasma exposure-time profiles and AUC_INF are better predicted using the default rCYP ISEF values instead of individually adjusted values (48% vs. 43% within 3-fold) when using the Original GI and default P-gp REF (1.5). The combination of optimized parameters (New GI physiology, P-gp REF of 0.5 and rCYP default ISEF) predicted the plasma exposures (AUC_INF and C_max) within 3-fold for 81% and 86% of the tested simulations, respectively. In conclusion, the present study proposes an optimized strategy for bottom-up PBPK model development in Simcyp Simulator. Retrospective comparison with observed clinical PK data is vital for model verification as well as further improvement in prospective predictions for future drug candidates.

This study assessed the potential risk of QT prolongation associated with the dual enhancer of zeste homolog 1/2 inhibitor valemetostat. An evaluation of the relationship between plasma valemetostat concentration and heart-rate-corrected QT (QTc) interval was performed. Time-matched plasma concentration and 12-lead electrocardiogram data were collected from the phase I studies DS3201-A-J101, in patients with relapsed/refractory B-/T-cell non-Hodgkin lymphomas (NCT02732275), and DS3201-A-U102, in patients with relapsed/refractory acute myeloid leukemia and acute lymphoblastic leukemia (NCT03110354). A prespecified linear mixed-effects model was used to assess the effect of valemetostat on change in QTc corrected by the Fridericia method (ΔQTcF). A population-specific method (ΔQTcP) was also used to remove the heart rate interval (RR) dependence. The final dataset contained 769 electrocardiogram measurements from 100 patients. Linear mixed-effects modeling found no significant demographic or clinical covariate effects. The slope versus concentration was significant (95% confidence interval [CI] of the coefficient excluded 0) in the final models for ΔQTcF, but not ΔQTcP, while the relative standard error of the slope was > 50% for both models. Baseline QTc had a negative effect on ΔQTc in all models. At the steady-state geometric mean maximum concentrations in the dose range of 100–700 mg tested in the DS3201-A-J101 and DS3201-A-U102 studies, the 90% CI upper bounds for model-predicted ΔQTcF and ΔQTcP were 1.52–8.38 ms, all of which were below the clinically significant threshold of 10 ms. The analysis supports a lack of a clinically meaningful effect on the QTc interval for valemetostat.