Accenture Global Solutions Limited

Praveen Viswanathan

Dhruv Bajpai

Krithika Pattabiraman

Ashish Ambasta

Vighnesh Paramasivam

Prince Chaturvedi

Bharath Kumar

Aspects of the present disclosure provide methods, devices, and computer-readable storage media that support dynamic enforcement of access control policies in a standardized manner. An administrator console enables access control policies to be defined as classes that may be combined and leveraged to rapidly define access control policies for enforcement in a standardized manner. An interceptor operates to detect access requests and perform policy administration (e.g., determining to grant/deny access) for the access requests and where access is granted, initiate policy resolution (e.g., determine any restrictions on the granted access request). An enforcer provides functionality for enforcing policy resolution outcomes, such as restricting access to information stored in a database or disabling interactive elements of a user interface. The enforcer may control enforcement of the policy resolution outcomes by modifying information in received access requests, such as to rewrite a query to incorporate restrictions on access to a data source.

Policy based access control system with standardized enforcement layer

Implementations of the present disclosure include receiving a document including data representative of an adverse event, providing a case including a set of fields, each field being populated with a value, querying a safety system based on a query that includes values of the case, receiving a sparse matrix based on query results responsive to the query, the sparse matrix including two or more vectors, each vector of the two or more vectors representing a historical case score, for each historical case, determining a score based on a respective vector of the two or more vectors and an input vector representative of the case, each score representing a degree of duplicity between the case and a respective historical case, and providing historical cases for display to a user, the historical cases including the two or more historical cases in rank order based on respective scores.

Duplicate case recommendation engine for pharmacovigilance

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that leverage artificial intelligence and machine learning to screen candidate pharmaceutical molecules or compounds for pharmaceutical uses (e.g., treating diseases or conditions). The screening may be based on structural similarity between the candidate pharmaceutical molecules and various pharmaceutical targets (e.g., proteins, nucleic acids, etc.). In aspects, one or more machine learning (ML) models may be trained to assign a candidate pharmaceutical molecule to one of multiple clusters based on chemical/physical properties of the candidate pharmaceutical molecule and chemical/physical properties of pharmaceutical targets associated with the clusters. The pharmaceutical targets associated with the cluster may be scored based on comparisons between the candidate pharmaceutical molecule and the pharmaceutical target, and a subset of the pharmaceutical targets may be identified based on the scores. In some implementations, the subset may be ranked using conjoint analysis and machine learning.

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Jodhpur, India

Praveen Viswanathan