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The Center for Biologics Evaluation and Research (CBER) at the US Food and Drug Administration (FDA) regulates gene therapies, among other products. The approval of four gene therapy products since 2017 represents a significant milestone for a new class of treatments with the potential to treat or cure diseases, particularly rare diseases, that were previously considered incurable. Several factors have contributed to the recent rapid development of gene therapies including advances in genetics to facilitate target-detection, advances in vectors, and regulatory incentives such as breakthrough therapy designation, priority review and market exclusivity. The patient population affected by a rare disease is typically small, heterogeneous and geographically dispersed. As a result, clinical trials on a rare disease have unique features in terms of study design, subject enrollment, data analyses and interpretation of study results. Given that the patient population affected is small for rare diseases, providing substantial evidence of effectiveness and evidence of safety in trials for rare disease presents challenges. In this paper, we share our experiences in the statistical review of three gene therapy products that have been approved by FDA CBER. Our motivation in writing this paper is to encourage the use of appropriate analysis strategies for other similar small trials, with a focus on data visualization strategies. [ABSTRACT FROM AUTHOR]

In some of the processes used in data analysis, such as the recognition of pathologies and pathological subjects, the presence of anomalous instances in the dataset is an unfavorable situation that can lead to misleading results. This article presents a function that implements the identification of anomalies in dataset using the boxplot and standard deviation methods. Also was used the filling technique to treat these anomalies, in which the anomalous point value were substituted by a limit value determined by the boxplot or standard deviation methods. To improve the outliers methods some normalization processes based on the z-score, logarithmic and squared root methodologies were experimented. These outliers treatment were applied to the dataset used in the recognition of vocal pathologies (dysphonia, chronic laryngitis and vocal cords paralysis vs control), performed by a MLP and LSTM neural networks. After the experiments, both the standard deviation and the boxplot methods with z-score normalization showed very useful for pre-processing the dataset for voice pathologies recognition. The accuracy was improved between 3 and 13 points in percentage. [ABSTRACT FROM AUTHOR]

Abstract: Alteration zones (more commonly foot wall alteration zones) are related to volcanic-hosted massive sulfide (VMS) deposits and represent unique features that may be targeted during exploration. Of these, the chloritic foot wall alteration pipe is the most extensive and characteristic of VMS deposits. This feature is geochemically identified by a strong relative enrichment in aluminium and magnesium and a coupled depletion in calcium and sodium, giving rise to chloritic rocks in the primary environment of formation. During high grade regional metamorphism such chloritic precursor rock types are replaced by an unusual mineral paragenesis, typically containing magnesium rich cordierite, phlogopite, orthoamphiboles or orthopyroxenes and aluminium rich minerals such as sillimanite and corundum. This suggests that the unusual geochemical features of the alteration zone, retained during the deformation and metamorphism, should be recognisable in lithogeochemical exploration. The massive sulfide deposit in the eastern part of the metamorphic Namaqua Province, South Africa, at Areachap, Kantienpan and the defunct Prieska Cu–Zn Mine are hosted by a Mid-Proterozoic volcano sedimentary succession known as the Areachap Group. These deposits were affected by a complex deformation and metamorphic history and represent examples of upper amphibolite to granulite grade metamorphosed VMS deposits. The application of the known lithogeochemical methods is especially complicated where the geology is not well understood, due to the poor rock exposure of complexly deformed and metamorphosed areas, such as in the eastern part of the Namaqua Province. The box plot presents a more readily applicable lithogeochemical method to characterize and identify the alteration process, but it was designed for relatively un-metamorphosed environments. It is demonstrated here that the box plot may also be applied to high-grade metamorphic terrains and that the mineral phases used in defining the boxplot in low grade metamorphic environments may be replaced by their equivalents in high grade metamorphic terrains. The compositional trends of the metamorphic minerals themselves may be used in defining the boxplot for high grade metamorphic terrains. These include the transition of: annite to phlogopite; grossular to almandine or pyrope, augite to enstatite or clinoenstatite, and hornblende to gedrite or cummingtonite. Close to the ore zone, the relative Mg content of pyroxene, cordierite and biotite are higher than further away from this zone. It could be demonstrated that the changes in the mineral compositions are gradational when comparing unaffected rocks with progressively more altered wall rocks. Conclusions based on an application of the isocon method demonstrate that primary footwall alteration zones in the Areachap Group''s VMS deposits are characterized by elemental depletion of Na2O, CaO, Sr, Ni, V and La and enrichment of MgO, Fe2O3(total), S, Zn, SiO2, Co and F. It is shown that the whole rock compositions of rocks that were independently identified as the metamorphic equivalents of altered rocks, using the isocon method, plot in the correct place in the box plot for high grade regionally metamorphosed terrains. This establishes the box plot as an effective and practical tool for lithogeochemical exploration for VMS deposits in complexly deformed high grade metamorphosed terrains. [Copyright &y& Elsevier]

An experimental investigation is conducted in a novel gas-liquid separator called Two-stage Gas Liquid Cylindrical Cyclone (TGLCC) with gas-liquid ratio of 25–600, which enables flow pattern observation and separation efficiency/pressure drop measurement. The experimental results show that three inlet flow patterns are observed in the vertical pipe before the TGLCC inlet, which are continuous flow, intermittent flow and annular flow. The presence of vertical pipe before inlet can affect the evolution process of inlet flow patterns, and both intermittent flow and continuous flow have 3 forms of evolution process. Based on the experimental results, a statistical method called box plot is used to characterize the pressure drop fluctuation for different flow pattern evolutions, including the maximum, minimum, percentiles, mean and median. Based on pressure drop data analysis relating to corresponding flow patterns, a statistical method of predicting flow patterns is proposed using 5 criteria obtained from the box plot analysis. For all experimental data, the prediction accuracy is 98%. Then the separation efficiencies of gas riser and drain pipe are analyzed, which is found to be heavily affected by flow pattern evolutions. Therefore, the statistical method is further used to predict the separation efficiency of TGLCC with accuracy of 93.4%. • A novel separator called TGLCC has been proposed. • Inlet flow patterns are investigated considering the vertical pipe before the TGLCC inlet. • Box plot is used to characterize the pressure drop fluctuation for flow patterns. • A statistical method of predicting flow patterns is proposed. • A statistical method of predicting separation efficiency is proposed. [ABSTRACT FROM AUTHOR]