EA202191101A1 - AUTOMATIC CALIBRATION AND AUTOMATIC MAINTENANCE OF RAMAN SPECTROSCOPIC MODELS FOR REAL-TIME PREDICTIONS - Google Patents
AUTOMATIC CALIBRATION AND AUTOMATIC MAINTENANCE OF RAMAN SPECTROSCOPIC MODELS FOR REAL-TIME PREDICTIONSInfo
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- EA202191101A1 EA202191101A1 EA202191101A EA202191101A EA202191101A1 EA 202191101 A1 EA202191101 A1 EA 202191101A1 EA 202191101 A EA202191101 A EA 202191101A EA 202191101 A EA202191101 A EA 202191101A EA 202191101 A1 EA202191101 A1 EA 202191101A1
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- Eurasian Patent Office
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- observation
- biopharmaceutical
- automatic
- local model
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- Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
Abstract
Способ отслеживания биофармацевтического процесса и/или управления им включает определение точки запроса, связанной со сканированием процесса системой спектроскопии (например, системой рамановской спектроскопии), и запрос базы данных наблюдений, содержащей наборы данных наблюдений, связанные с прошлыми наблюдениями биофармацевтических процессов. Каждый из наборов данных наблюдений содержит спектральные данные и соответствующее фактическое аналитическое измерение. Запрос базы данных наблюдений включает выбор в качестве обучающих данных из наборов данных наблюдений тех наборов данных наблюдений, которые удовлетворяют одному или нескольким критериям релевантности относительно точки запроса. Способ также включает использование выбранных обучающих данных для калибровки локальной модели, характерной для биофармацевтического процесса. Локальная модель (например, модель на основе гауссовского процесса) обучается для предсказания аналитических измерений на основе входных спектральных данных. Способ также включает использование локальной модели для предсказания аналитического измерения биофармацевтического процесса.A method for tracking and / or managing a biopharmaceutical process includes determining a query point associated with scanning the process by a spectroscopy system (eg, a Raman spectroscopy system) and querying an observational database containing observational datasets associated with past observations of biopharmaceutical processes. Each of the observation datasets contains spectral data and the corresponding actual analytical measurement. An observation database query involves selecting, as training data, from the observation datasets, those observation datasets that meet one or more of the relevance criteria for the query point. The method also includes using the selected training data to calibrate a local model specific to the biopharmaceutical process. A local model (for example, a Gaussian process model) is trained to predict analytical measurements based on the input spectral data. The method also includes using a local model to predict an analytical measurement of a biopharmaceutical process.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
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US201962864565P | 2019-06-21 | 2019-06-21 | |
PCT/US2019/057513 WO2020086635A1 (en) | 2018-10-23 | 2019-10-23 | Automatic calibration and automatic maintenance of raman spectroscopic models for real-time predictions |
Publications (1)
Publication Number | Publication Date |
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EA202191101A1 true EA202191101A1 (en) | 2021-08-10 |
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Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
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EA202191101A EA202191101A1 (en) | 2019-06-21 | 2019-10-23 | AUTOMATIC CALIBRATION AND AUTOMATIC MAINTENANCE OF RAMAN SPECTROSCOPIC MODELS FOR REAL-TIME PREDICTIONS |
Country Status (1)
Country | Link |
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EA (1) | EA202191101A1 (en) |
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2019
- 2019-10-23 EA EA202191101A patent/EA202191101A1/en unknown
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