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Repligen Corporation to Present at Upcoming June Investor Conferences

WALTHAM, Mass., May 22, 2024 -- Repligen Corporation , a life sciences company focused on bioprocessing technology leadership, today announced that it will be presenting at the following June...

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INX International invests in Oden Technologies

INX International invests in Oden Technologies
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Process analytics for the new era of continuous RNA manufacturing

Process analytics for the new era of continuous RNA manufacturing
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Biopharmaceutical Processing Equipment Consumables Market

“Biopharmaceutical Processing Equipment Consumables Market” from 2024-2034 with covered segments (Biopharmaceutical Processing Equipment Consumables...

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Repligen Reports Fourth Quarter and Full Year 2023 Financial Results

Reports fourth quarter revenue of $156 million and full year revenue of $639 millionContinued strength in orders with fourth quarter book-to-bill ratio of 1.03

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A new name in gas and liquid sampling

The new JCT Group brings forward innovative and well-engineered solutions to a broad range of industries. Click to read more...

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"A computational framework for Data-Driven Decision Support and Knowled" by Asjad Khan

Process Mining techniques have traditionally focused on post-mortem analysis to optimize business processes, leveraging event logs to identify bottlenecks and inefficiencies. These methods aim to optimize process performance by mining process behavior, identifying bottlenecks, and pinpointing other sources of inefficiencies and defects. Complementing this, Process Analytics extends the analytical framework to support the practice of Business Process Management (BPM). This is achieved by leveraging process-related data to extract knowledge, enhance process performance, and facilitate managerial decision-making across the organization. Although considerable attention has recently been devoted to the development of process mining techniques for interpreting process behavior from event logs, the task of leveraging these logs to provide decision support for achieving optimal process outcomes remains an open challenge. Existing techniques have severe shortcomings, especially in the settings of unstructured, knowledge-intensive processes. Moreover, current methods struggle to provide value to organizations in real-world settings where event logs are geographically dispersed, noisy, and incomplete. The first part of this thesis addresses these challenges by demonstrating how process data can be employed to prescribe tasks in order to achieve optimal outcomes (in both structured and unstructured knowledge-intensive processes where context plays a crucial role). The second part of the thesis contributes to the field of process mining by specifically tackling the challenges associated with understanding process behavior from real-world, geographically dispersed logs that are often noisy and incomplete. To evaluate the effectiveness of the proposed methods, the research methodology employed in this thesis comprises quantitative experiments using real-world data. Data are collected from archived event logs generated by business process management systems and from publicly available datasets, all in strict adherence to ethical guidelines.

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Repligen to Report Fourth Quarter and Full Year 2023 Financial Results

Repligen to Report Fourth Quarter and Full Year 2023 Financial Results
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Transcript : Repligen Corporation Presents at J.P. Morgan 42nd Annual Healthcare Conference 2024, Jan-09-2024 02 -January 09, 2024 at 05:15 pm EST

Presenter SpeechRachel Vatnsdal Olson Perfect. Good afternoon, everyone. This is Rachel Vatnsdal with the Life Science Tools and Diagnostics team. I'm joined today by Tony Hunt CEO of Repligen. So...

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