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公开(公告)号:EP4450649A1
公开(公告)日:2024-10-23
申请号:EP24153686.1
申请日:2024-01-24
发明人: NAGPAL, SUNIL , HAQUE, MOHAMMED MONZOORUL , MANDE, SHARMILA SHEKHAR , MERCHANT, MITALI , CHENNAREDDY, VENKATA SIVA KUMAR REDDY
摘要: This disclosure relates more particularly to risk assessment of autism spectrum disorder (ASD) present in the subject and designing a personalized recommendation for the same. Current diagnostic tools and procedures, though abundant in numbers, are all based on psychiatric or behavioral evaluations, checklists and associated statistical inferences, which highlight the inherent limitation in making a reliable and early diagnosis. The present disclosure makes use of oral microbial samples of both saliva and dental plaque. The present disclosure involves a paired extraction and quantification of site-specific unique microbial sequences pertaining to the oral microbial samples of an ASD subject and subsequent classification of the subject under the ASD risk category using a metric based on a predefined ensemble of mathematical formulas. Further, a guided development of personalized microbial cocktail(s) is then designed based on the most relevant formula-set for the subject.
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公开(公告)号:EP4451285A1
公开(公告)日:2024-10-23
申请号:EP24153673.9
申请日:2024-01-24
发明人: HAQUE, MOHAMMED MONZOORUL , SINGH, RASHMI , MERCHANT, MITALI , MANDE, SHARMILA SHEKHAR , CHENNAREDDY, VENKATA SIVA KUMAR REDDY , NAGPAL, SUNIL , DUTTA, ANIRBAN
摘要: The present disclosure is related to method and system for identifying and utilizing frugal markers for classification of biological sample. Discovering an optimal and/ or frugal set of features/ biomarkers form a large set of features measured through high-throughput screening techniques, which can characterize a disease/ anomaly with sufficient accuracy, still remains a challenge. According to the present disclosure, given a set of measurements of multiple features characterizing biological samples obtained from disease cases and healthy controls, a classification model combining the measured values of a small subset of the features is computed. The classification model is then used for classifying between disease cases and healthy controls.
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公开(公告)号:EP4450647A3
公开(公告)日:2024-10-30
申请号:EP24153672.1
申请日:2024-01-24
发明人: MERCHANT, MITALI , NAGPAL, SUNIL , HAQUE, MOHAMMED MONZOORUL , MANDE, SHARMILA SHEKHAR , PINNA, NISHAL KUMAR
IPC分类号: C12Q1/6883 , C12Q1/689 , G16B20/00
摘要: This disclosure relates more particularly to risk assessment of preterm delivery (PTD) in the subject and designing a personalized recommendation for the same. Conventional techniques for PTD risk assessment are either invasive or minimally invasive and leaves little time for subjects to take precautionary or corrective medical advice or procedures to reduce or obviate the risk. The present disclosure provides the risk assessment of the PTD, by quantifying a microbial abundance in oral or gut microbiome for a pregnant woman, identifying a certain combination of microbial biomarkers using an ensemble of models for accurate risk assessment of the PTD and subsequently suggesting a personalized recommendation for at risk subject. The present assessment technique is completely non-invasive and further helps in characterizing the risk of the PTD.
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公开(公告)号:EP4450647A2
公开(公告)日:2024-10-23
申请号:EP24153672.1
申请日:2024-01-24
发明人: MERCHANT, MITALI , NAGPAL, SUNIL , HAQUE, MOHAMMED MONZOORUL , MANDE, SHARMILA SHEKHAR , PINNA, NISHAL KUMAR
IPC分类号: C12Q1/6883 , C12Q1/689 , G16B20/00
摘要: This disclosure relates more particularly to risk assessment of preterm delivery (PTD) in the subject and designing a personalized recommendation for the same. Conventional techniques for PTD risk assessment are either invasive or minimally invasive and leaves little time for subjects to take precautionary or corrective medical advice or procedures to reduce or obviate the risk. The present disclosure provides the risk assessment of the PTD, by quantifying a microbial abundance in oral or gut microbiome for a pregnant woman, identifying a certain combination of microbial biomarkers using an ensemble of models for accurate risk assessment of the PTD and subsequently suggesting a personalized recommendation for at risk subject. The present assessment technique is completely non-invasive and further helps in characterizing the risk of the PTD.
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