AAPS Journal最新文献

{"title":"Investigating the Impact of Food Induced Fluid Viscosity on Disintegration and Dissolution of Immediate Release Midodrine HCl Tablet.","authors":"Fathima T Doole, Ranganath Wahalathantrige Don, Ishwor Poudel, Timothy Lex, Yi-Hsien Cheng, Fang Wu, Wei-Jhe Sun, Lei Zhang, Peter Langguth, Wenlei Jiang, Zongming Gao","doi":"10.1208/s12248-026-01291-2","DOIUrl":"10.1208/s12248-026-01291-2","url":null,"abstract":"<p><p>The prediction of bioavailability (BA) and bioequivalence (BE) for immediate-release (IR) solid oral dosage forms is critical during development and post-approval phases of drug products. ICH M13A provides the option of using in vitro tests, such as disintegration and dissolution in biorelevant media, pilot studies, and modeling to justify not conducting in vivo fed BE studies. The gastrointestinal (GI) tract environment changes significantly after food intake, including variations in pH, enzyme activity, and fluid viscosity that influence drug dissolution and absorption. Existing biorelevant dissolution media (FeSSIF, FeSSGF etc.) simulate human GI fluid composition but do not account for food-induced viscosity changes. This study explored impacts of food-induced fluid viscosity (pH 1.2 buffer containing hydroxypropyl methylcellulose (HPMC)) on disintegration and dissolution profiles of midodrine HCl tablets. Using USP Apparatus II and disintegration testing, we evaluated dissolution and disintegration of five approved generic midodrine HCl tablets with demonstrated BE. High-viscosity media significantly delayed tablet disintegration and drug dissolution compared to low-viscosity fasting conditions. We modified dissolution methods to closely simulate fed state GI conditions by varying agitation speed, prolonging dissolution time, adding medium stagewise to simulate dilution of gastric fluid, and adding water to mimic co-administered drinks. Results showed increased dissolution with higher agitation speeds and continued dissolution in viscous media over extended time. Stagewise dissolution in medium with reduced viscosity to mimic gastric secretion did not accelerate drug release compared to viscous media. In contrast, co-administered water enabled tablet swelling and disintegration, leading to complete drug release within 15 min, which is more consistent with the in vivo PK data under fed conditions. These findings may help refine in vitro dissolution conditions to better mimic fed-state.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"28 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148914296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic Differential Equations (SDEs) in NONMEM for Probing Population Pharmacokinetic Model Misspecification: Diagnostic Utility, Practical Considerations, and Future Directions.","authors":"Ping Chen, Robert J Bauer, Yan Li","doi":"10.1208/s12248-026-01302-2","DOIUrl":"10.1208/s12248-026-01302-2","url":null,"abstract":"<p><p>Population pharmacokinetic (popPK) models are commonly developed using ordinary differential equations (ODEs) to describe deterministic concentration-time profiles, with unexplained variability typically attributed to interindividual variability or residual error. When model misspecification is present, system-level deviations may be absorbed into these conventional variability terms, making the source and magnitude of model inadequacy difficult to assess quantitatively. Stochastic differential equations (SDEs) provide an alternative framework by introducing an explicit system-noise component into the structural model, allowing model-data mismatch to be evaluated more directly. However, historical implementation of SDE-based models in NONMEM has been technically challenging. The availability of the Fortran plug-in subroutine SDE.f90 substantially lowers this barrier and enables more practical implementation. In this work, SDE-based nonlinear mixed-effects models were evaluated as a quantitative diagnostic framework for probing popPK model misspecification. The SDE.f90 implementation was first verified using simulated one-compartment intravenous bolus datasets with stochastic process noise. Additional simulation-estimation scenarios were then conducted under intentionally misspecified structural or stochastic assumptions, including time-varying elimination, compartmental misspecification, and residual error misspecification. Across these scenarios, the estimated system-noise parameter was generally sensitive to misspecification, with larger values usually associated with greater structural or stochastic mismatch. SDE-based modeling also helped partially separate system-level variability from residual variability and, in selected settings, supported localization of misspecification to specific model components, thereby helping guide model refinement. Overall, SDE-based popPK modeling is a useful addition to the pharmacometric diagnostic toolbox, with system-noise estimates best interpreted alongside structural model evaluation, residual diagnostics, parameter behavior, and pharmacologic plausibility.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"28 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148892905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Betting on Biology: Rethinking Probability as the Currency of Risk in Biotechnology Portfolios.","authors":"Rajesh Krishna","doi":"10.1208/s12248-026-01290-3","DOIUrl":"10.1208/s12248-026-01290-3","url":null,"abstract":"<p><p>Uncertainty is an integral facet to the biotechnology and life sciences industry. From early target drug discovery to regulatory approval and commercialization, investment decisions are made under conditions of incomplete knowledge and asymmetric information. Indices of probability, particularly probability of technical and regulatory success, probability of clinical success, and risk-adjusted net present value, have become foundational tools for structuring these uncertainties within portfolio decision-making frameworks. However, their interpretation and application often lack conceptual precision and contextual nuance. This commentary examines the use of probability indices in describing and managing portfolio risk in biotechnology and life sciences. It reflects on their role in assigning risk to new drug targets, novel therapeutic modalities, and stage-specific development programs.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"28 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148892854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Importance of Single Global Regulatory Standards for the Assessment of Generic and Biosimilar Medicines to Advance Patient Access.","authors":"Antonela Rodriguez, Vishalakshi Krishnan, James E Polli, Anna Schwendeman","doi":"10.1208/s12248-026-01272-5","DOIUrl":"10.1208/s12248-026-01272-5","url":null,"abstract":"<p><p>Generic and biosimilar medicines are foundational to sustainable healthcare, enabling broader patient access globally through high-quality, cost-effective alternatives. However, their market access is hindered by regulatory fragmentation across major authorities, where regulatory expectations are not always clearly aligned across jurisdictions or transparently justified, introducing additional complexity and potential delays in development and approval. This study integrates structured interviews with representatives from generic and biosimilar companies, alongside comprehensive literature and regulatory database reviews, to assess the impact of these regulatory inconsistencies. Analysis of 52 pharmaceutical products across four categories identified several key challenges including duplicated clinical studies across jurisdictions, inconsistent reference product (RP) requirements, and divergent manufacturing standards, potentially contributing to increased development costs and delayed market entry. These challenges disproportionately affect complex generics and orphan drugs, affecting global patient access to critical medicines. Despite promising international harmonization initiatives, substantial obstacles remain. The findings highlight key areas for greater regulatory alignment, including acceptance of foreign RPs, harmonization of technical standards, streamlined development pathways, and enhanced collaboration among regulatory agencies. Such measures are critical to facilitate global development of generic and biosimilar medicines, ensuring timely patient access without compromising safety or efficacy.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"28 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148888589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Industry Perspective on Translational and Clinical Pharmacology Aspects of Viral-based Gene Therapies and Vaccines-Key Considerations and Learnings From Approved Products.","authors":"Hardik Mody, Jatin Narula, Prathap Nagaraja Shastri, Dale Miles, Yun Liu, Vittal Shivva, Jimit Raghav, Gillie Roth, Anshul Gupta, Bahru Habtemariam, Salvatore Iovino, Steven Louie, Nagendra Venkata Chemuturi","doi":"10.1208/s12248-026-01267-2","DOIUrl":"10.1208/s12248-026-01267-2","url":null,"abstract":"<p><p>Viral-based gene therapies and vaccines represent a rapidly evolving modality for treating a wide range of diseases. However, these novel modalities pose novel and complex challenges for translational PK/PD scientists and clinical pharmacologists during preclinical and clinical development. To support accelerated development of these transformative therapies, experts in the field formed a working group under the umbrella of AAPS and through this review provide a comprehensive overview of translational and clinical pharmacology considerations for viral vector-based gene therapies, including adeno-associated virus (AAV), oncolytic virus, adenovirus (AdV) and herpes simplex virus (HSV), and viral-vector based vaccines; with the help of robust discussion of the literature and learnings from the currently approved products. We discuss key developmental challenges, such as preclinical characterization, including dose-response evaluations and biodistribution assessments. The manuscript highlights how preclinical data, particularly the minimum effective dose (MED) and maximum tolerated dose (MTD) in relevant animal models, inform the selection of the First-in-Human (FIH) dose. We explore the challenges and strategies for clinical study design, including use of open-label, dose-escalation trials and the importance of monitoring for immunogenicity. The text also reviews clinical pharmacology considerations, such as vector shedding and tissue biodistribution, which are critical for determining product safety and efficacy. Finally, we discuss the emerging role of modeling and simulation approaches to improve preclinical-to-clinical dose translation and clinical dose optimization. By synthesizing lessons from approved products, this review aims to provide a valuable framework for navigating the complex translational and clinical pharmacology landscape of viral vector-based gene therapies and vaccines.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"28 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Machine Learning Platform for Imputing Missing Critical Quality Attributes in Pharmaceutical Development.","authors":"Yusuf Ali Mohammed, Chrystalla Protopapa, Angeliki Siamidi, Marilena Vlachou, Simon Gaisford, Moe Elbadawi","doi":"10.1208/s12248-026-01271-6","DOIUrl":"10.1208/s12248-026-01271-6","url":null,"abstract":"<p><p>Quality control is fundamental to drug development, with critical quality attributes (CQAs) serving as key indicators of product performance. However, missing or incomplete CQA data remains a persistent challenge throughout pharmaceutical research and manufacturing. In this study, we evaluated the utility of machine learning techniques (MLT) for CQA imputation across five pharmaceutical datasets comprising 14 CQAs. Five MLT were benchmarked against conventional imputation methods to assess their imputation performance. In several datasets and CQAs, MLT achieved imputation accuracies exceeding R² = 0.80, including under conditions of up to 30% simulated missingness. Nevertheless, performance varied substantially across CQAs and datasets, highlighting the critical influence of data quality, feature informativeness and source heterogeneity on imputation outcomes. Overall, ML-based methods outperformed several traditional approaches in the majority of evaluated scenarios, although reduced performance was observed for selected complex or weakly informative CQAs. To facilitate practical adoption, we developed a web-based software platform enabling users to apply and evaluate ML-based imputation workflows on their own datasets. These findings indicate that ML-based imputation methods can complement conventional techniques for managing incomplete CQA data and may enhance data integrity when applied under appropriate conditions. Collectively, this work supports the potential of ML-assisted imputation as a component of data-driven decision-making frameworks in pharmaceutical development.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"28 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design, Optimization and Evaluation of Taste-Masked Acemetacin Formulations Using Purolite A430MR.","authors":"Xinyi Shi, Yanfei Wang, Zhaohua Li, Sining Han, Jirun Jia, Yibo Li, Qiang Fu","doi":"10.1208/s12248-026-01276-1","DOIUrl":"10.1208/s12248-026-01276-1","url":null,"abstract":"<p><p>A favorable taste is highly desirable for oral formulations, as an unpleasant bitter taste can severely compromise patient compliance. Acemetacin (ACM) is a bitter and poorly soluble drug, posing a significant challenge for oral administration. In this study, Purolite A430MR (A430MR) was employed to mask the bitterness of ACM via a precipitation method, forming ACM-A430MR resin composites (ARCs). A 1:1 weight ratio of ACM to A430MR was identified as the optimized formulation, achieving favorable drug loading and process yield. The ARCs_1:1 was characterized by SEM-EDS, PXRD, DSC, FTIR, and molecular docking to investigate their structural and physicochemical properties and were further evaluated by in vitro release and human sensory testing. The formulation exhibited a drug load of 0.95 mg/mg and a process yield of 65.8%. Characterization revealed that ACM was uniformly dispersed within the resin matrix in an amorphous state, mediated by a salt bridge interaction between the quaternary ammonium group of A430MR and the carboxyl group of ACMs. In vitro release testing showed only 6.04% of ACM was released from ARCs in simulated salivary fluid within 5 min, falling below the 10% threshold generally accepted for effective taste-masking. Human sensory evaluation confirmed a marked reduction in bitterness score from 4.83 (pure ACM) to 1.16 (p < 0.0001). In summary, complexation with Purolite A430MR via ion exchange represents a highly effective taste masking strategy, with strong potential to improve patient compliance.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"28 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An In Vitro Quantitative Systems Pharmacology Platform for Characterizing CD3-Bispecific Antibody-Mediated T-Cell Activation and Tumor Cell Cytotoxicity.","authors":"Xuanzhen Yuan, Craig Thalhauser, Nasrin Afzal, Kristel Kemper, Guohua An, Tommy Li","doi":"10.1208/s12248-026-01259-2","DOIUrl":"10.1208/s12248-026-01259-2","url":null,"abstract":"<p><p>CD3-bispecific antibodies (CD3-BsAbs) represent an emerging modality with promising anticancer potential. Despite increasing regulatory approvals, the development of CD3-BsAbs remains challenging. CD3-BsAb candidates are routinely assessed and compared via in vitro workflows. However, protocol heterogeneity across experimental laboratories constrains cross-study potency comparisons. To address this, we developed an in vitro Quantitative System Pharmacology (QSP) model that mechanistically characterizes key processes underlying CD3-BsAb activity. The aim was to establish a framework adaptable to diverse in vitro conditions. The current framework comprises (a) single-cell trimer formation sub-model, (b) trimer-mediated T-cell activation and differentiation sub-model, (c) effector T-cell mediated tumor cell killing sub-model. We evaluated the framework using DuoBody-CD3x5T4 (CD3 equilibrium dissociation constant (K_D) = 683 nM) data from 14 solid tumor cell lines spanning 5T4 expression of 9,447-61,686 molecules/cell and drug concentrations of 1.76E-05-42.8 nM. For a subset of cell lines, we also included additional data comparing DuoBody-CD3x5T4 with bsIgG1-CD3x5T4 (CD3 K_D = 16 nM) and assessing effector-to-target (E:T) ratios of 1:1-8:1. All in vitro data were pooled into a single modeling dataset. A joint fit of T-cell activation and tumor cell cytotoxicity across the interconnected sub-models accurately captured the data and demonstrated mechanistic consistency. The model yielded mechanistically meaningful parameters, such as the per-T cell trimer count required to achieve half-maximal T-cell activation (EC50_act, estimated to be 2.12-4.6 trimers/T cell). The model's mechanistic structure and versatility suggest its potential to serve as a platform to predict drug effects across diverse assay conditions, quantify assay-dependent effects, and guide candidate selection.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"28 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148609557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of Sorbitol as a Pharmaceutical Excipient in Oral Liquid Pediatric Formulations Submitted to the U.S. FDA.","authors":"Gelareh A Abulwerdi, Brianna Cote, Susan Abdel-Rahman, Elimika Pfuma Fletcher, Gilbert J Burckart","doi":"10.1208/s12248-026-01265-4","DOIUrl":"10.1208/s12248-026-01265-4","url":null,"abstract":"<p><p>Sorbitol is a commonly used excipient in pediatric oral liquid formulations. Previous research revealed that sorbitol as an excipient can diminish the bioavailability of concomitant drugs. The reported cases and amount of sorbitol in pediatric formulations has not been explored, thus the aims of this study were to (1) examine the number of reports of sorbitol as an excipient in orally administered drugs with liquid formulations used in pediatrics, and (2) estimate the maximum amount of sorbitol that may be consumed per day for each drug. A compilation of drug products containing sorbitol as an excipient was retrieved from the Interagency Agreement between the National Institute of Child Health and Human Development (NICHD) and the Food and Drug Administration (FDA), and products with oral liquid formulations were selected. Maximum daily sorbitol amount was categorized into level 0 (< 3,200 mg), level 1 (3,200 mg to < 10,200 mg), level 2 (10,200 mg to < 13,400 mg), and level 3 (≥ 13,400 mg). Results indicated that sorbitol amount ranged between 0.06% and 45.7% weight to volume (w/v) across several therapeutic areas with the most prevalent being drugs intended for nervous system disorders. Corticosteroid drug products had the highest daily exposures to sorbitol, with amounts surpassing 45 grams. Percentages of products at levels 3, 2, 1 and 0 were 11.5%, 7.1%, 39.3%, and 42%, respectively. The potential impact of sorbitol content in pediatric formulations and the best practices for its use in pediatric polypharmacy needs to be further investigated.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"28 5","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148609559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Calculating Receptor Occupancy using TMDD Models - What has to be Considered?","authors":"Yu Fu, Liang Yang, Hong Su, Ye Yao, Yu Li, Peiming Ma","doi":"10.1208/s12248-026-01269-0","DOIUrl":"10.1208/s12248-026-01269-0","url":null,"abstract":"<p><p>Target-mediated drug disposition (TMDD) models are often used to describe drug-receptor interactions and help derive receptor occupancy (RO), i.e., the ratio of drug-receptor complex to total receptors, which is important for understanding drug responses especially in early clinical development. A full TMDD model can be complex, and data may not always be sufficient for fitting the model. In such cases, approximations of the full TMDD model (e.g., Michaelis-Menten, rapid-binding or quasi-steady-state models) are used, and RO is calculated often using the Michaelis-Menten constant ( <math><mrow><mspace></mspace> <msub><mtext>K</mtext> <mrow><mspace></mspace> <mtext>M</mtext></mrow> </msub> </mrow> </math> ) derived from these models. In this simulation study, we conduct analyses using models with parameter values sourced from literature to show that RO derived from <math><mrow><mspace></mspace> <msub><mtext>K</mtext> <mrow><mspace></mspace> <mtext>M</mtext></mrow> </msub> </mrow> </math> may not reflect the true RO. When data available for model-fitting consists only of drug concentrations, the accuracy and precision of the model parameters such as <math><mrow><mspace></mspace> <msub><mtext>K</mtext> <mrow><mspace></mspace> <mtext>M</mtext></mrow> </msub> </mrow> </math> depend on the selected approximate models and their model assumptions, e.g., where binding takes place. We hope these analyses provide insights in performing model-derived RO predictions and dose optimization-which often depends on RO-in clinical drug development.</p>","PeriodicalId":50934,"journal":{"name":"AAPS Journal","volume":"28 4","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148550973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}