Exploring Python to Prepare CDISC-Compliant Analysis Datasets for Pharmacometric Analyses

461 Background: TIVO is an oral vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitor (TKI) approved in the US for treatment of patients with RCC following ≥2 prior systemic therapies. The approved TIVO monotherapy starting dose is 1.34 mg once daily on days (D) 1-21 Q28D, with allowable dose modifications to manage adverse events. In the randomized TiNivo-2 trial, the addition of NIVO 480 mg to TIVO 0.89 mg D1-21 Q28D (lower dose of TIVO was studied given assumed risk of hypertension [HTN]) did not improve outcomes compared with TIVO 1.34 mg D1-21 Q28D. There was a trend toward worse progression-free survival (PFS) in the combination arm. Methods: Using a predeveloped population pharmacokinetic (PK) model, existing ER models based on Tivo-1 and Tivo-3 studies were augmented to characterize the relationship between TIVO at clinically relevant exposures and central reviewer–based PFS, tumor size (TS) reduction, and safety endpoints. TiNivo-2 trial results were integrated to update the PK and ER models for PFS (Cox proportional hazard), TS (sum of longest diameters longitudinal model), and HTN (logistic regression) and to simulate the ER-based risk/benefit profile of TIVO. Results: The visual predictive check of the PK model on TiNivo-2 PK data confirmed that the dose-proportional TIVO PK is unaffected by concurrent NIVO. The PFS range of 5.6-9.7 months and TS reduction models, with a range of −7.02% to −23.8%, showed a significant relationship with TIVO exposure (Table). Concurrent NIVO did not add discernible benefit to TIVO at the dose of 0.89 mg. An ER modeling analysis between maximum concentration and HTN showed that the predicted HTN incidence was similar between TIVO 1.34 mg and TIVO 0.89 mg (41.3% vs 38.8% for any-grade HTN; 23.8% vs 21.5% for grade ≥3 HTN). An effect term for NIVO in the ER model for HTN was nonsignificant. Conclusions: The efficacy ER models predicted that TIVO 1.34 mg would provide greater antitumor activity than the 0.89-mg dose, while the predicted HTN incidence (any grade and grade ≥3) was comparable at the 0.89- and 1.34-mg doses. The TIVO monotherapy dose selection of 1.34 mg is important, based on the ER analysis and its safety profile. The results from the TiNivo-2 data set further confirmed that re-challenge with immunotherapy does not add benefit and optimal dosing of TKI provides the highest clinical benefit. Clinical trial information: NCT04987203 . Efficacy endpoint TIVO average concentration, ng/mL n Observed value,combined studies (range) PFS 13.9-38.4 192 5.6 months PFS 38.4-47.9 191 7.3 months PFS 47.9-62.0 191 9.1 months PFS 62.0-177 191 9.7 months CFB TS 13.9-38.4 176 −7.02% (−16% to 1.93%) CFB TS 38.4-47.9 173 −11.7% (−21.3% to −2.05%) CFB TS 47.9-62.0 185 −17.3% (−26.4% to −8.27%) CFB TS 62.0-177 183 −23.8% (−33.5% to −14.1%) CFB, change from baseline.

From the Editor’s Desk…

e21552 Background: Immune checkpoint inhibitors (ICIs) and targeted therapies have significantly improved clinical outcomes in advanced melanoma. However, resistance to ICIs lead to relapse in a substantial proportion of patients, creating a critical need for effective treatment strategies after ICI failure. Tumor-infiltrating lymphocyte (TIL) therapy and oncolytic virus therapies like Talimogenelaherparepvec (TVEC), have emerged as promising approaches alongside other systemic therapies. This study systematically evaluates the efficacy and safety of systemic therapies after ICI failure to guide sequencing new treatment modalities in relapsed advanced melanoma. Methods: A systematic search of PubMed, Cochrane, and Ovid databases from January 2012 to December 2024 was conducted to identify studies on systemic therapies for advanced melanoma following ICI failure. Data were extracted on study design, treatment sequences, progression-free survival (PFS), overall survival (OS), and response rates (RR), including complete response (CR) and partial response (PR) rates that collectively contribute to the objective response rate (ORR). The data were summarized descriptively to capture treatment efficacy and safety outcomes across different therapeutic approaches. Results: From 145 studies identified, 31 (n = 3,462) met inclusion criteria. OS data were available on 2,407 patients, and PFS for 2,342 patients. For ICI/PD-1 retreatment (anti-CTLA-4 with nivolumab or pembrolizumab), the ORR ranged from 11% to 34%, with a median PFS of 2.5 to 8.5 months and OS of 14.3 months. In BRAF positive patients, MEK/BRAF inhibitors post-ICI therapy showed similar results (ORR 32%, PFS 7.5 months, OS 12.8 months). Sequential anti-CTLA-4/anti-PD-1 or anti-PD-1/anti-LAG-3 therapies yielded lower ORRs (8% to 14%) and shorter PFS (2.8 months). TIL/HD IL2 therapy achieved the highest efficacy, with an ORR of 37.5% and OS not reached among responders. TVEC therapy showed promising results (ORR 55%, PFS 37 months). Chemotherapy exhibited the lowest efficacy (ORR 11%, PFS 2.5 months). Grade 3-4 immune-mediated adverse events were noted in 5-57% of patients, with cytopenia affecting up to 100% of TIL therapy recipients. Conclusions: Therapeutic options for advanced melanoma after PD-1 failure are expanding, with TIL therapy, anti-LAG-3 inhibitors, TVEC, and targeted agents. Heterogeneity of study designs, response rates, and toxicity profiles complicate direct comparisons. Given the high efficacy, TIL therapy and TVEC should be considered as second line treatment options. Further research to establish optimal treatment algorithms and combination strategies with acceptable toxicity profile is warranted in relapsed melanoma.

PurposeIn the phase 3 CheckMate 9ER trial, intravenous nivolumab (240 mg every 2 weeks) plus oral cabozantinib (40 mg/day) improved progression-free survival (PFS) versus sunitinib as first-line therapy for advanced renal cell carcinoma (RCC). To support cabozantinib dosing with the combination, this exposure–response analysis characterized the relationship of cabozantinib exposure with clinical endpoints.MethodsDose modification was allowed with cabozantinib (holds and reductions) to manage adverse events (AEs). The population pharmacokinetics analysis was updated and used to generate individual predicted cabozantinib exposure measures. Kaplan–Meier plots and time-to-event Cox proportional hazard (CPH) exposure–response models characterized the relationship of cabozantinib exposure with PFS, dose modifications, and selected AEs.ResultsKaplan–Meier plots showed no clear difference in PFS across cabozantinib exposure quartiles. Cabozantinib exposure did not significantly affect the hazard of PFS in the CPH base model nor in the final model. In contrast, baseline albumin and nivolumab clearance had a significant effect on PFS. There was no significant relationship between cabozantinib clearance and risk of dose modification, but a significant relationship was identified between cabozantinib exposure and Grade ≥ 1 palmar-plantar-erythrodysesthesia and Grade ≥ 3 diarrhea in the exposure–response analysis.ConclusionTo optimize individual cabozantinib exposure, these data support the dose modification strategies in CheckMate 9ER for cabozantinib in patients with advanced RCC when combined with nivolumab.

Background: Although allogeneic stem cell transplantation (allo-SCT) and programmed cell death 1 (PD-1) blockade have separately shown efficacy in some lymphoid malignancies, the safety of allo-SCT after anti–PD-1 therapy in these patients remains a high clinical interest. Aims: We present data from an analysis from 4 KEYNOTE phase 1-3 studies to describe predetermined complications in patients who received allo-SCT following pembrolizumab therapy. Methods: The analysis included patients from the KEYNOTE-013 (NCT01953692, n=20), KEYNOTE-087 (NCT02453594, n=31), KEYNOTE-170 (NCT02576990, n=5), and KEYNOTE-204 (NCT02684292, n=14) trials who have a known allo-SCT transplantation date received within 2 years of the last dose of study pembrolizumab. Descriptive statistics were used for predefined post–allo-SCT complications of interest. The cumulative incidence of acute grade 2-4 graft-versus-host disease (GVHD), acute grade 3-4 GVHD, and chronic GVHD was estimated. The corresponding competing risk events were death without acute grade 2-4 GVHD, death without acute grade 3-4 GVHD, and death without chronic GVHD, respectively. The cumulative incidence of post–allo-SCT transplant-related mortality (TRM) was estimated with relapse as a competing risk. Progression-free survival (PFS) and overall survival (OS) were estimated by the Kaplan-Meier method. Results: Seventy patients were included in the analysis. Median age was 30 y (range, 18-65), 57 (81.4%) had classical Hodgkin lymphoma (cHL), and the rest had non-Hodgkin lymphoma. 69 of 70 (98.6%) patients received pembrolizumab monotherapy; 1 patient received pembrolizumab + lenalidomide. Median duration on study treatment was 5.3 months (range, 0.7-29.6) and median time from last pembrolizumab dose to first allo-SCT was 4.6 months (range, 1-20). Before transplantation, 49 patients (70.0%) had intervening anticancer regimen; 34 (48.6%) had active disease, 31 patients (44.3%) were in remission at time of transplant, and 5 patients (7.1%) had unknown disease status. Overall, 55 patients (78.6%) developed GVHD (acute, 38; chronic, 17). The estimated 6-month post–allo-SCT cumulative incidence was 0.41 (95% CI, 0.30-0.53) for grade II-IV acute GVHD and 0.20 (95% CI, 0.12-0.30) for grade III-IV acute GVHD; 1 year post–allo-SCT was 0.21 (95% CI, 0.12-0.31) for chronic GVHD. Other predetermined complications, including critical illness, immune-mediated adverse events, pulmonary complications, and veno-occlusive liver disease, occurred in 32 patients (45.7%). After a median follow-up (defined as the time from allo-SCT to data cutoff) of 40.1 months (range, 5.1-71.2), the post–allo-SCT median PFS was not reached (NR) (95% CI, 14.5-NR) and the 30-month post–allo-SCT PFS rate was 56.8% (95% CI, 42.9-68.5) (Figure A); median OS was NR (95% CI, NR-NR) and the OS rate at 12 months was 82.2% (Figure B). The estimated post–allo-SCT cumulative incidence for TRM at 6 months was 0.09 (95% CI, 0.03-0.17) and for relapse at 26 months was 0.27 (95% CI, 0.16-0.38). PFS and OS outcomes were comparable in the subgroup of patients with cHL. Image:Summary/Conclusion: The incidence of GVHD in this population is comparable to historical data (40%-80% and 30%-70%, respectively). The incidence of severe acute GVHD may be higher than a typical modern allo-SCT series, although TRM was low. The observed PFS and OS outcomes compare favorably to historical benchmarks (2-year PFS ranging from 45%-48%; 1-year OS >80%). Altogether, this analysis lends confidence that allo-SCT is feasible for patients with lymphoid malignancies after PD-1 blockade.

The phase III SKYSCRAPER-02 study determined whether the benefits of atezolizumab plus carboplatin and etoposide (CE) could be enhanced by the addition of tiragolumab in untreated extensive-stage small-cell lung cancer (ES-SCLC). We report final progression-free survival (PFS) and overall survival (OS) analyses. Patients received tiragolumab 600 mg/placebo, plus atezolizumab 1,200 mg and CE (four cycles), then maintenance tiragolumab/placebo plus atezolizumab. Primary end points were investigator-assessed PFS and OS in patients without history/presence of brain metastases (primary analysis set [PAS]). Additional end points included PFS and OS in all patients regardless of brain metastases status (full analysis set [FAS]), response, and safety. Four hundred ninety patients were randomly assigned (FAS): 243 to tiragolumab arm and 247 to control arm. At the cutoff date (February 6, 2022; median duration of follow-up, 14.3 months [PAS] and 13.9 months [FAS]), final analysis of PFS in the PAS (n = 397) did not reach statistical significance (stratified hazard ratio [HR], 1.11; P = .3504; median, 5.4 months tiragolumab v 5.6 months control). At the cutoff date (September 6, 2022; median duration of follow-up, 21.2 months [FAS]), median OS in the PAS at final OS analysis was 13.1 months in both arms (stratified HR, 1.14; P = .2859). Median PFS and OS in the FAS were consistent with the PAS. The proportion of patients with immune-mediated adverse events (AEs) in the tiragolumab and control arms was 54.4% and 49.2%, respectively (grade 3/4: 7.9% and 7.7%). AEs leading to treatment withdrawal occurred in 8.4% and 9.3% of tiragolumab- and control-treated patients, respectively. Tiragolumab did not provide additional benefit over atezolizumab and CE in untreated ES-SCLC. The combination was well tolerated with no new safety signals.

Efficacy of durvalumab plus tremelimumab treatment for unresectable hepatocellular carcinoma in immunotherapy era clinical practice.

Background:For patients with advanced non-small-cell lung cancer (NSCLC) and high (⩾50%) programmed cell death-ligand 1 (PD-L1) expression, effective first-line immune-oncology monotherapies with significant survival benefits are approved, cemiplimab being the most recent. In a phase III trial, cemiplimab demonstrated significantly improved overall survival (OS) and progression-free survival (PFS) versus chemotherapy in patients with advanced NSCLC and PD-L1 ⩾50%. A systematic literature review and network meta-analysis (NMA) was conducted to identify/compare the efficacy/safety of cemiplimab versus pembrolizumab or other immune-oncology monotherapies from randomized-controlled trials (RCTs) published in November 2010–2020.Methods:Relevant RCTs were identified by searching databases and conference proceedings as per ISPOR, NICE, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. NMA with time-varying hazard ratios (HRs) was performed for OS and PFS. Analyses were conducted for objective response rate (ORR) and safety/tolerability. Fixed-effect models were used due to limited evidence. Various sensitivity analyses were conducted to validate the base case analyses.Results:The feasibility assessment determined that EMPOWER-Lung 1, KEYNOTE-024, and KEYNOTE-042 trials were eligible. IMpower110 was excluded because an incompatible PD-L1 assay (SP142) was used for patient selection. For first-line advanced NSCLC with PD-L1 ⩾50%, cemiplimab was associated with statistically significant improvements in PFS [HR (95% credible interval [CrI]): 0.65 (0.50–0.86), 1–12 months] and ORR [odds ratio (OR) (95% CrI): 1.64 (1.04–2.62)], and comparable OS [HR (95% CrI): 0.77 (0.54–1.10), 1–12 months] versus pembrolizumab. There was no evidence of differences between cemiplimab and pembrolizumab for Grade 3–5 adverse events (AEs) [OR (95% CrI): 1.47 (0.83–2.60)], immune-mediated AEs [1.75 (0.33–7.49)], and all-cause discontinuation due to AEs [1.21 (0.58–2.61)].Conclusions:Considering the limitations of indirect treatment comparisons, in patients with advanced NSCLC and PD-L1 ⩾50%, cemiplimab monotherapy demonstrated significant improvements in PFS and ORR, comparable OS, and no evidence of differences in safety/tolerability versus pembrolizumab.

Background. In an era of breakthroughs in cancer immunotherapy, CheckMate 067 studies declared the combination of PD-1 and CTLA-4 inhibitors a new standard of care for patients with metastatic melanoma (MM). A significant limitation of the widespread use of the combination of ipilimumab and nivolumab in routine clinical practice is the high risk of severe immune-mediated adverse events. Prolgolimab and nurulimab are a combination of fixed doses of original monoclonal antibodies (manufactured by JSC "BIOCAD," Russia) to the PD-1 receptor (prolgolimab) and the CTLA-4 receptor (nurulimab) (3:1 ratio). This paper presents the results of an international, multicenter, double-blind, placebo-controlled, comparative, randomized, phase II OBERTON clinical study to investigate the efficacy and safety of nurulimab + prolgolimab combination therapy with continued prolgolimab therapy compared to prolgolimab alone as first-line therapy in patients with unresectable melanoma (uRM) or MM (NCT03913923). Materials and methods. The study included patients with uRM or MM who were not previously treated for metastatic disease. The patients were randomized into two groups (1:1). Patients in group 1 were treated with a nurulimab (1 mg/kg) and prolgolimab (3 mg/kg) combination at a dose of 0.2 mL/kg (equivalent to 1 mg/kg of nurulimab and 3 mg/kg of prolgolimab) once every 3 weeks during the first 4 blinded infusions. Patients in group 2 received prolgolimab monotherapy at a dose of 3 mg/kg once every 3 weeks during the first 4 blinded infusions. Starting from infusion 5, patients in both groups received open prolgolimab 1 mg/kg once every 2 weeks. The primary endpoint of the study was progression-free survival (PFS). The study is registered on ClinicalTrials.gov under the number NCT05732805 and is currently ongoing, but recruitment of new patients has been completed. Results. One hundred seventeen patients were randomized and received at least one dose of the study therapy. At a median follow-up of 16.79 months, the median PFS was 12.2 (4.9; not achieved) months in the nurulimab + prolgolimab group and 2.8 (1.5; 4.7) months in the prolgolimab monotherapy group (95% confidence interval 0.36-0.90, hazard ratio 0.57). PFS at 24 months was 41% in the nurulimab + prolgolimab group and 25.4% in the prolgolimab monotherapy group. In both groups, the therapy was well tolerated. Grade 3-4 immune-mediated adverse events were reported in 15.5% of patients who received nurulimab + prolgolimab, compared with 1.7% of those who received prolgolimab alone. The most frequent grade 3-4 treatment-related adverse events in both treatment groups were increased alanine aminotransferase and aspartate aminotransferase and asthenia. Overall, the safety profile was favorable, as expected for the class of immune checkpoint inhibitors, anti-CTLA-4, and anti-PD-1 monoclonal antibodies. Discussion. The results demonstrate a favorable safety profile in both the nurulimab + prolgolimab combination and prolgolimab monotherapy groups as the first-line treatment for uRM or MM. The assessment of the primary endpoint, PFS, showed the benefit of combination immunotherapy followed by switching to prolgolimab compared to prolgolimab alone. Conclusion. Combination immunotherapy with the CTLA-4 inhibitor nurulimab and the PD-1 inhibitor prolgolimab, available as a combination of solutions of two drugs in a single vial, with a further switch to monotherapy with prolgolimab, can fill an important niche in the treatment of patients with uRM or MM. Confirmation of the obtained data on the efficacy and safety of the combined regimen of nurulimab + prolgolimab in comparison with PD-1 inhibitor monotherapy is expected from the ongoing phase III BCD-217-2 OCTAVA study (NCT05732805).

BackgroundMetastatic RCC has a poor prognosis. Despite improvement in treatment outcomes with ICB and targeted therapy, many patients fail to respond to first line therapy and immune mediated adverse events(irAE) remains a major challenge, often leading to treatment discontinuation. Therefore, mitigating irAE without compromising antitumor immunity is a critical unmet need. Tryptophan microbial metabolic pathway is known to play a major role in immune homeostasis through its action on Aryl hydrocarbon receptor (AhR) balancing immune suppresser with immune effector responses. We hypothesize that microbial metabolism of tryptophan to indole metabolites may play a role in ICB resistance as well in irAE, identification of which may help us predict patients most likely to respond, without life threatening toxicity.MethodsWe prospectively collected paired stool and blood samples of treatment naïve metastatic RCC patients, treated with ICB +/- Tyrosine kinase inhibitors (TKI) at treatment initiation and at time of first response assessment (12+/-3 weeks). We evaluated stool metagenomics and untargeted stool and plasma metabolomics among responders (R) and non-responders (NR). We focused on kynurenine/tryptophan and indoles/tryptophan ratio to evaluate differential host and microbial metabolism of tryptophan. A responder was classified as progression free survival (PFS) greater than 6 months while patients with grade 3 or higher irAE was classified as serious IrAE.ResultsAmong 120 patients accrued, 49 were treated with combination ICB, while 71 patients were treated with ICB + TKI. Median follow up was 27 months. 28 patients (23%) had a Grade 3 or higher irAE. 3 patients died from complications attributable to irAE. The median duration to development of any irAE was 3.5 months.Using negative binomial regression model evaluating baseline relative abundance of microbial tryptophan metabolites that were associated both with response as well as serious irAE, we noted significant higher abundance of Indole acetic acid (IAA), indole acetonitrile(ACN), indole acetyl phenylalanine (IAAP)and IAA/kynurenine (Kyn) and lower abundance of tryptophol, indole 3 pyruvic (IPA), (coefficient of 6.4, 1.8, 7.15, 4.6, 0.04, 0.46, with adj p value < 0.05) with serious irAE as well as ICB resistance (Coefficient-5.42, 1.83, 6.15, 4.05, 0.03, 0.4, P < .05).ConclusionsThis is one of the first studies evaluating microbial metabolic pathways that may play a role in predicting patients who are more likely to respond with lower likelihood of serious irAE in RCC, thus helping to identify strategies to decouple tumor immunity from autoimmunity to improve ICB outcomes. Further the results can be extrapolated to many other solid tumor treated with immunotherapy, as tryptophan metabolism plays a immune homeostatic role across cancers.

Artificial intelligence applications within the geosciences are becoming increasingly common, yet there are still many challenges involved in adapting established techniques to geoscience data sets. Applications in the realm of volcanic hazards assessment show great promise for addressing such challenges. Here, we describe a Jupyter Notebook we developed that ingests real-time Global Navigation Satellite System (GNSS) data streams from the EarthCube CHORDS (Cloud-Hosted Real-time Data Services for the geosciences) portal TZVOLCANO, applies unsupervised learning algorithms to perform automated data quality control (“noise reduction”), and explores autonomous detection of unusual volcanic activity using a neural network. The TZVOLCANO CHORDS portal streams real-time GNSS positioning data in 1[Formula: see text]s intervals from the TZVOLCANO network, which monitors the active volcano Ol Doinyo Lengai in Tanzania, through UNAVCO’s real-time GNSS data services. UNAVCO’s real-time data services provide near-real-time positions processed by the Trimble Pivot system. The positioning data (latitude, longitude and height) are imported into the Jupyter Notebook presented in this paper in user-defined time spans. The positioning data are then collected in sets by the Jupyter Notebook and processed to extract a useful calculated variable in preparation for the machine learning algorithms, of which we choose the vector magnitude for further processing. Unsupervised K-means and Gaussian Mixture machine learning algorithms are then utilized to locate and remove data points (“filter”) that are likely caused by noise and unrelated to volcanic signals. We find that both the K-means and Gaussian Mixture machine learning algorithms perform well at identifying regions of high noise within tested GNSS data sets. The filtered data are then used to train an artificial intelligence neural network that predicts volcanic deformation. Our Jupyter Notebook has promise to be used for detecting potentially hazardous volcanic activity in the form of rapid vertical or horizontal displacement of the Earth’s surface.

Copanlisib dose selection was established under the maximum tolerated dose paradigm, and no dedicated dose‐finding studies have investigated copanlisib dose selection when used in combination with rituximab. In CHRONOS‐3, copanlisib plus rituximab demonstrated significantly improved progression‐free survival versus placebo plus rituximab in patients with relapsed indolent non‐Hodgkin lymphoma (iNHL). We conducted a comprehensive investigation of copanlisib population pharmacokinetics (PopPK) from a pooled analysis of 712 patients across nine copanlisib phase I–III studies and exposure–response (ER) relationships for efficacy and safety from the 1‐year follow‐up of CHRONOS‐3. PopPK analyses examined the impact of demographic, laboratory, and comedication covariates on copanlisib between‐patient PK variability. Individual static and time‐varying exposure estimates were derived to investigate exposure–efficacy and exposure–safety relationships. Multivariate Cox proportional hazards and logistic regression analyses examined ER relationships with consideration of predefined potentially prognostic demographic‐, laboratory‐, and/or disease‐related baseline covariates. Copanlisib PK were best described by a three‐compartment model with first‐order elimination. Individual identified covariates had modest effects on copanlisib PK and were generally in line with known copanlisib disposition properties. In CHRONOS‐3, ER analyses showed a significant relationship between time‐varying exposure estimates and progression‐free survival, and no significant exposure–safety relationships. Thus, lower copanlisib doses may result in reduced efficacy but not necessarily improved safety or tolerability. These outcomes substantiate the current intermittent dosing regimen of copanlisib 60 mg on days 1, 8, and 15 of a 28‐day cycle and support the observed clinical results of copanlisib in combination with rituximab in the iNHL population.

&amp;lt;p&amp;gt;Earth Observation (EO) data availability is drastically increasing thanks to the Copernicus Sentinel missions. In 2014 Sentinel data volumes were approximately 200 TB (one operational mission) while in 2019 these volumes rose to 12 PB (nine operational missions) and will increase further with the planned launch of new Sentinel satellites. Dealing with this big data evolution has become an additional challenge in the development of downstream services next to algorithm development, product quality control, and data dissemination techniques.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The H2020 project &amp;amp;#8216;Data Cube Service for Copernicus (DCS4COP)&amp;amp;#8217; addresses the downstream challenges of big data integrating Copernicus services in a data cube system. A data cube is typically a four-dimensions object, with a parameter dimension and three shared dimensions (time, latitude, longitude). The traditional geographical map data is transformed into a data cube based with user-defined spatial and temporal resolutions using tools such as mathematical operations, sub-setting, resampling, or gap filling to obtain a set of consistent parameters.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This work describes how different EO datasets are integrated in a data cube system to monitor the water quality in the Belgian Continental Shelf (BCS) for a period from 2017 to 2019. The EO data sources are divided in four groups: 1) high resolution data with low temporal coverage (i.e. Sentinel-2), 2) medium resolution data with daily coverage (i.e. Sentinel-3), 3) low resolution geostationary data with high coverage frequency (i.e. MSG-SEVIRI), and 4) merged EO data with different spatial and temporal information acquired from CMEMS. Each EO dataset from group 1 to 3 has its own thematic processor that is responsible for the acquisition of Level 1 data, the application of atmospheric corrections and a first quality control (QC) resulting in a Level 2 quality-controlled remote sensing reflectance (Rrs) product. The Level 2 Rrs is the main product used to generate other ocean colour products such as chlorophyll-a and suspended particulate matter. Each product generated from the Rrs passed by a second QC related to its characteristic and improvements (when applied) and organized in a common data format and structure to facilitate the direct integration into a product and sensor specific. At the end of the process, these products are defined as quality-controlled analysis ready data (ARD) and are ingested in the data cube system enabling fast and easy access to these big data volumes of multi-scale water quality products for further analysis (i.e. downstream service). The data cube system grants a fast and easy straightforward access converting netCDF data to Zarr and placing it on the server. In Zarr datasets, the object is divided into chunks and compressed while the metadata are stored in light weight .json files. Zarr works well on both local filesystems and cloud-based object stores which makes it possible to use through a variety of tools such as an interactive data viewer or jupyter notebooks.&amp;lt;/p&amp;gt;

Interim PET-Adapted De-Escalation Chemotherapy Regimen for Advanced Stage Classical Hodgkin Lymphoma Using Brentuximab Vedotin, Pembrolizumab, Doxorubicin, and Dacarbazine: Phase 2 Safety and Efficacy Study

The use of program code as a data source is increasingly expanding among data scientists. The purpose of the usage varies from the semantic classification of code to the automatic generation of programs. However, the machine learning model application is somewhat limited without annotating the code snippets. To address the lack of annotated datasets, we present the Code4ML corpus. It contains code snippets, task summaries, competitions, and dataset descriptions publicly available from Kaggle—the leading platform for hosting data science competitions. The corpus consists of ~2.5 million snippets of ML code collected from ~100 thousand Jupyter notebooks. A representative fraction of the snippets is annotated by human assessors through a user-friendly interface specially designed for that purpose. Code4ML dataset can help address a number of software engineering or data science challenges through a data-driven approach. For example, it can be helpful for semantic code classification, code auto-completion, and code generation for an ML task specified in natural language.