ABSTRACT
Industry worldwide is facing new challenges, particularly the implementation of new technologies, climate change and currently the pandemic of the disease caused by the new coronavirus COVID-19. For the industry to be competitive, it must make technological changes. These changes are based on the concept of Industry 4.0. The changes brought about by implementing the Industry 4.0 concept and the related digitization of the economy have implications for the functioning of markets, industries, and other sectors. Significant impacts can be expected on the labor market when the demand for specific professions changes and new competencies will be required for employees. The fundamental question is how specifically these requirements can be implemented in current education conditions, specifically in the university environment. As part of practical training, it is unrealistic to demonstrate new ways of operation management on an extensive product line. It is very effective to use various forms of small-scale models. These models behave practically the same as in actual operation, and students can try out different production states, problem-solving and subsequent optimization. This article describes how we solve this problem in our university.
ABSTRACT
Industry worldwide is facing new challenges, particularly the implementation of new technologies, climate change and currently the pandemic of the disease caused by the new coronavirus COVID-19. For the industry to be competitive, it must make technological changes. These changes are based on the concept of Industry 4.0. The changes brought about by implementing the Industry 4.0 concept and the related digitization of the economy have implications for the functioning of markets, industries, and other sectors. Significant impacts can be expected on the labor market when the demand for specific professions changes and new competencies will be required for employees. The fundamental question is how specifically these requirements can be implemented in current education conditions, specifically in the university environment. As part of practical training, it is unrealistic to demonstrate new ways of operation management on an extensive product line. It is very effective to use various forms of small-scale models. These models behave practically the same as in actual operation, and students can try out different production states, problem-solving and subsequent optimization. This article describes how we solve this problem in our university. © 2022 IEEE.
ABSTRACT
Background: The Phase III PROpel (NCT03732820) trial demonstrated at interim analysis a statistically significant clinical benefit from combining ola + abi in the first-line (1L) mCRPC setting vs placebo (pbo) + abi. Benefit was seen irrespective of a pt's homologous recombination repair mutation (HRRm) status;median radiographic progression-free survival (rPFS) 24.8 for ola + abi vs 16.6 months for pbo + abi (hazard ratio [HR] 0.66, 95% confidence interval [CI] 0.54-0.81;P<0.0001). The safety profile of ola + abi was shown to be consistent with that for the individual drugs. We report additional interim safety analysis from PROpel. Methods: Eligible pts were ≥18 years with mCRPC, had received no prior chemotherapy or next-generation hormonal agent treatment at mCRPC stage, and were unselected by HRRm status. Pts were randomized 1:1 to abi (1000 mg qd) plus prednisone/prednisolone with either ola (300 mg bid) or pbo. Primary endpoint was investigator-assessed rPFS. Safety was assessed in all pts receiving ≥1 dose of study treatment by adverse event (AE) reporting (CTCAE v4.03). Results: 398 pts received ola + abi and 396 pbo + abi (safety analysis set). At data cut-off (July 30, 2021), median total duration of exposure for ola was 17.5 vs 15.7 months for pbo, and for abi 18.2 months in the ola + abi arm and 15.7 in the pbo + abi arm. Anemia (n=183) was the most common AE in the ola + abi arm, and 34% of these 183 events were managed by dose interruption, 23% by dose reduction, and 8% resulted in treatment discontinuation. Anemia and pulmonary embolism (PE) were the only Grade ≥3 AEs in ≥5% of pts (anemia: ola + abi, 15.1% vs pbo + abi, 3.3%;PE: 6.5% vs 1.8%, respectively). Most PEs were detected incidentally on radiographic imaging (69.2% and 71.4% in the ola + abi and pbo + abi arms, respectively) and no pts discontinued. More pts in the ola + abi arm experienced venous thromboembolism (Table). Arterial thromboembolism and cardiac failure AEs were balanced between the treatment arms. No AE of myelodysplastic syndrome/acute myeloid leukemia was reported in either treatment arm. COVID-19 was reported more frequently with ola + abi (8.3% vs 4.5%). Conclusions: PROpel demonstrated a predictable safety profile for ola + abi given in combination to pts with 1L mCRPC unselected by HRRm status. AEs of cardiac failure and arterial thromboembolism were reported at similar frequency in both treatment arms. The majority of PEs were asymptomatic. The safety profile of abiraterone was not adversely impacted by its combination with olaparib.