Justification of Widened Dissolution Specifications of an Extended Release Product Using Physiologically Based Biopharmaceutics Modeling.

Drug product meeting the dissolution specifications is crucial in order to ensure consistent clinical performance. However, in certain cases wider dissolution specifications may be required based on product behavior. While justification of such wider specifications may be challenging from a regulatory context, approaches such as physiological based biopharmaceutics modeling (PBBM) can be utilized for this purpose.Product DRL is a fixed dose combination product consisting of an immediate (IR) and extended release (ER) portions. For the ER portion, the dissolution specifications consisted of four time points and a proposal was made to relax the specification at the 2h time point (from 50-70% to 45-67%) to reduce the batch failures at commercial scale.To support wider specification, a PBBM was developed and extensively validated with literature & in-house studies. Virtual bioequivalence was performed using the pivotal clinical study data.Virtual dissolution profiles for proposed wider specifications were generated using three different approaches. Incorporation of lower and upper dissolution profiles into the model indicated absence of impact on in vivo performance thereby justifying the specifications.Regulatory acceptance of proposed specifications with PBBM indicated the significance of using modeling approaches to reduce repeated testing thereby facilitating faster approvals.

A joint analysis proposal of nonlinear longitudinal and time-to-event right-, interval-censored data for modeling pregnancy miscarriage.

Pregnancy in-vitro fertilization (IVF) cases are associated with adverse first-trimester outcomes in comparison to spontaneously achieved pregnancies. Human chorionic gonadotrophin ß subunit (ß-HCG) is a well-known biomarker for the diagnosis and monitoring of pregnancy after IVF. Low levels of ß-HCG during this period are related to miscarriage, ectopic pregnancy, and IVF procedure failures. Longitudinal profiles of ß-HCG can be used to distinguish between normal and abnormal pregnancies and to assist and guide the clinician in better management and monitoring of post-IVF pregnancies. Therefore, assessing the association between longitudinally measured ß-HCG serum concentration and time to early miscarriage is of crucial interest to clinicians. A common joint modeling approach is to use the longitudinal ß-HCG trajectory to determine the risk of miscarriage. This work was motivated by a follow-up study with normal and abnormal pregnancies where ß-HCG serum concentrations were measured in 173 young women during a gestational age of 9-86 days in Santiago, Chile. Some women experienced a miscarriage event, and their exact event times were unknown, so we have interval-censored data, with the event occurring between the last time of the observed measurement and ten days later. However, for those women belonging to the normal pregnancy group; that is, carrying a pregnancy to a full-term event, right censoring data are observed. Estimation procedures are based on the Stochastic Approximation of the Expectation-Maximization (SAEM) algorithm.

A machine learning-guided modeling approach to the kinetics of α-tocopherol and myricetin synergism in bulk oil oxidation.

The shelf-life and quality of food products depend heavily on antioxidants, which protect lipids from free radical degradation. α-Tocopherol and myricetin, two potent antioxidants, synergistically enhance the prevention of oxidative rancidity in bulk oil systems. Understanding their degradation kinetics is essential for deepening our knowledge of their mechanisms and developing strategies to predict shelf-life before expiration. This paper introduces a generalized mathematical model to describe the degradation kinetics of α-tocopherol in the presence of myricetin. Using direct differential methods guided by a machine learning approach based on neural differential equations, we uncover two distinct phases of α-tocopherol degradation when coexisting with myricetin at varying concentration ratios. These findings inform the development of a mixed Weibull model that accurately captures the degradation process. Our study enhances the understanding of antioxidant interactions and provides a reliable method for predicting food system stability, offering valuable insights for optimizing natural antioxidants in food preservation.

Early diagnosis to avoid invasive treatment in cardiac migration of a ventriculoperitoneal catheter: a qualitative systematic review and Weibull analysis of case reports.

OBJECTIVE: The migration of distal catheter after ventriculoperitoneal shunt placement is a rare but significant complication. Especially in a case of cardiac migration, open-heart surgery or catheter intervention may be required. The authors encountered a case of cardiac migration that fortunately could be treated by withdrawal. A systematic review of cardiac migration was performed to clarify when and how migration was diagnosed and why invasive treatments were required. Based on the collected cases, a Weibull analysis of the latency until diagnosis was performed to examine whether cardiac migration is caused by an initial factor and to compare the result with the other migration sites such as gastrointestinal tract or urinary tract. METHODS: A qualitative systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. A database of case reports was created by searching PubMed and Scopus with the keywords "ventriculoperitoneal AND shunt AND migration" (last search date: April 2022). Whether the occurrence rate of migration is constant over time was examined by fitting a Weibull distribution. RESULTS: A total of 339 articles of all migration sites were identified. Among them, 36 articles reporting 38 cases of cardiac migration were considered eligible. A total of 39 cases including the authors' case were reviewed qualitatively. When classifying the cases by their latency to diagnosis, the rates of pulmonary thrombosis and of cardiac adhesion were higher in the delayed group (≥ 1 year) than in the early group (≤ 1 month). The rate of open chest surgery was higher in the delayed, intermediate, and early groups, in that order. In the Weibull analysis, the shape parameter (ß) was less than 1, indicating that the occurrence rate of cardiac migration was initially high, followed by a decline. The finding supports the hypothesis that migration results from an intraoperative vascular injury. Note that these findings are subject to bias given that they are derived from case reports. CONCLUSIONS: In light of the previous reports, the latency until diagnosis of cardiac migration was associated with the rate of thrombosis and adhesion, which resulted in escalation to invasive treatment. Early diagnosis will prevent invasive treatment because most cases are caused by initial factors, as the Weibull analysis showed.

A Network-Constrain Weibull AFT Model for Biomarkers Discovery.

We propose AFTNet, a novel network-constraint survival analysis method based on the Weibull accelerated failure time (AFT) model solved by a penalized likelihood approach for variable selection and estimation. When using the log-linear representation, the inference problem becomes a structured sparse regression problem for which we explicitly incorporate the correlation patterns among predictors using a double penalty that promotes both sparsity and grouping effect. Moreover, we establish the theoretical consistency for the AFTNet estimator and present an efficient iterative computational algorithm based on the proximal gradient descent method. Finally, we evaluate AFTNet performance both on synthetic and real data examples.

Bayesian parametric estimation based on left-truncated competing risks data under bivariate Clayton copula models.

In observational/field studies, competing risks and left-truncation may co-exist, yielding 'left-truncated competing risks' settings. Under the assumption of independent competing risks, parametric estimation methods were developed for left-truncated competing risks data. However, competing risks may be dependent in real applications. In this paper, we propose a Bayesian estimator for both independent competing risks and copula-based dependent competing risks models under left-truncation. The simulations show that the Bayesian estimator for the copula-based dependent risks model yields the desired performance when competing risks are dependent. We also comprehensively explore the choice of the prior distributions (Gamma, Inverse-Gamma, Uniform, half Normal and half Cauchy) and hyperparameters via simulations. Finally, two real datasets are analyzed to demonstrate the proposed estimators.

Experimental and Modeling Analysis of Polypropylene Fiber Reinforced Concrete Subjected to Alkali Attack and Freeze-Thaw Cycling Effect.

The durability of concrete materials in harsh environmental conditions, particularly in cold regions, has garnered significant attention in civil engineering research in recent years. Concrete structures in these areas are often damaged by the combined effects of alkali-silica reaction (ASR) and freeze-thaw cycles, leading to structural cracks and significant safety hazards. Numerous studies have demonstrated that polypropylene fiber concrete exhibits excellent crack resistance and durability, making it promising for applications in cold regions. This study elucidates the impact of alkali content on concrete durability by comparing the mechanical properties and durability of different alkali-aggregate concretes. The principal experimental methodologies employed include freeze-thaw cycle experiments, which examine patterns of mass loss; fluctuations in the dynamic modulus of elasticity; and changes in mechanical properties before and after freeze cycles. The findings indicate that increased alkali content in concrete reduces its strength and durability. At 100% alkali-aggregate content, compressive strength decreases by 35.5%, flexural strength by 32.9%, mass loss increases by 35.85%, relative dynamic elastic modulus by 39.4%, and residual strength by 97.28%, indicating higher alkali content leads to diminished durability. Additionally, this paper introduces a constitutive damage model, validated by a strong correlation with experimental stress-strain curves, to effectively depict the stress-strain relationship of concrete under varying alkali contents. This research contributes to a broader understanding of concrete durability in cold climates and guides the selection of materials for sustainable construction in such environments.

Application of the Marshall-Olkin-Weibull logarithmic distribution to complete and censored data.

In contemporary statistical research, there has been a notable surge of interest surrounding a suggested extension of the Marshall-Olkin-G distributions. The present extension exhibits a higher degree of flexibility in comparison to its parent distributions. In a similar manner, we present in this context an expansion of the Marshall-Olkin-G distributions proposed by statistical scholars. This study utilizes a specific variant of the extension known as the Marshall-Olkin-Weibull Logarithmic model, which is applied to both complete and censored data sets. It is evident that the aforementioned model has strong competitiveness in accurately characterizing both complete and censored observations in lifetime reliability issues, when compared to other comparative models discussed in this research work.

Monitoring nonlinear large gradient subsidence in mining areas through SBAS-InSAR with PUNet and Weibull model fusion.

The subsidence of the earth's surface in mining areas is characterized by fast speed and large gradients. Conventional small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) monitoring can significantly underestimate results, making it challenging to capture the surface's temporal subsidence features. In this context, this paper proposes a method for monitoring subsidence in mining areas. It utilizes a phase unwrapping network (PUNet) and a fused Weibull model within the SBAS-InSAR framework to address nonlinear and large-gradient subsidence. The basic principle of this method is to first process the SAR images using the small baseline method to obtain the differential interferogram, utilizing the PUNet to obtain reliable large-gradient unwrapped phases. Next, the Weibull model parameters of each pixel are calculated based on the unwrapped phase, and the temporal subsidence of each point on the surface is determined using the calculated parameters. This method introduces a nonlinear model into the SBAS-InSAR solution, which is more consistent with the subsidence characteristics of mining areas. Through experimentation in a backfilled mining working face, the proposed method in this paper yields superior monitoring results compared to conventional approaches.

Investigation of mechanical and physico-chemical properties of new natural fiber extracted from Bassia indica plant for reinforcement of lightweight bio-composites.

In this investigation, novel cellulose fibers were acquired from the Bassia Indica plant to serve as a reinforcement source in composite materials. The morphological characteristics were studied using Scanning Electron Microscopy (SEM). The surface chemistry, crystallinity, and functional groups of Bassia Indica fibers were analyzed using X-ray Diffraction (XRD), Energy Dispersive X-ray (EDX) spectroscopy, and Attenuated Total Reflectance-Fourier Transform Infrared spectroscopy (ATR-FTIR), which assess the crystal structure, elemental composition, and surface functional groups, respectively. The thermal behavior of Bassia Indica fibers were assessed through Thermogravimetric Analysis (TGA). Anatomical techniques demonstrated the abundant presence of fibroblasts in the fibers. The presence of lignocellulosic fiber (lignin, cellulose and hemicellulose) was confirmed through ATR-FTIR analysis. The analysis of physical properties unveiled a fiber density of 1.065 ± 0.025 g/cm³ and a diameter of 145.58 ± 7.89 µm. The crystalline size of Bassia Indica fibers reached 2.23 nm, with a crystallinity index of 40.12 %, and an activation energy of 93.78 kJ/mol, TGA research revealed that Bassia Indica fibers are thermally stable up to 260.24 °C. Additionally, the fibers experienced maximum degradation at 321.23 °C. Weibull statistical analysis was performed using parameters 2 and 3 to calculate the observed dispersion in the experimental tensile results after analyzing the mechanical properties of the fibers possessing a tensile strength of 417.50 ± 7.08 MPa, Young's modulus of 17.46 ± 1.55 GPa, stress at failure of 1.17 ± 0.02 % and interfacial shear strength of 6.99 ± 1.10 MPa. The results were additionally compared to how they were stated in the relevant sources. Bassia Indica fibers can be considered a viable choice for reinforcing lightweight bio-composites.