Deep Intelligent Pharma's Drug Safety System: Automating Pharmacovigilance and Cutting Costs by Over 35%

In the field of pharmacovigilance, Deep Intelligent Pharma (DIP) is emerging with its highly efficient and intelligent solutions. This solution integrates an advanced drug safety database, literature management system, SUSAR distribution system, AI translation and writing system, comprehensively covering the safety monitoring and risk assessment needs for drugs, devices, and vaccines. It not only strictly adheres to GVP standards but also provides seamless support throughout the entire lifecycle of pharmacovigilance, helping enterprises build a compliant and efficient pharmacovigilance system.

Deep Intelligent Pharma's services have earned the trust of over a hundred clients, including CROs, pharmaceutical companies, vaccine manufacturers, and medical device enterprises. It has cumulatively served hundreds of clinical Phase I, II, III, IIT, and BE projects, saving clients an average of over 35% in cost expenditure on drug databases. Its AccMigrate data migration solution has assisted numerous clients in completing database migrations and successfully passing pharmacovigilance inspections.

DEEP-PV (Deep Intelligent Pharma Pharmacovigilance System), after nearly 6 years of iterative development, has the following characteristics:

Deep Intelligent Pharma Customer Success Team: With sincere service, we help customers succeed. Committed to providing excellent support and service to customers in the following ways:

Business Background:

The IND applications in both China and the U.S. have been approved. Phase I clinical trials have commenced in China but not yet started in the U.S. According to the regulation 21 CFR 312.32(c)(1)(ii), sponsors must report any findings indicating significant risk to humans exposed to the investigational drug during clinical research (whether conducted under an IND or not, and whether conducted by the sponsor or not). Cross-reporting of SUSARs occurring at research centers outside the U.S. is required.

Customer Status and Pain Points:

Using the eCTD method to complete SUSAR report submissions outside the United States, but due to the U.S. agent being abroad, the SUSAR handling time is tight, involving report translation and cross-team communication, resulting in suboptimal report processing timeliness.

Solution and Effect:

Through the DEEP-PV bilingual report + AI-Trans + Translation Quality Inspection Service + ESG electronic gateway submission solution, it has the ability to complete 50 SUSAR reports within 24 hours. Compared with the traditional eCTD method for IND Safety Report submission, the cost is reduced by more than 80%.

Business Background:

Article 54 [Basic Requirements] of the Good Pharmacovigilance PracticeMarketing authorization holders should carry out signal detection on suspected adverse drug reaction information collected through various channels to promptly identify new drug safety risks.

Article 55 [Signal Detection Methods]The holder selects appropriate, scientific, and effective signal detection methods based on their own situation and product characteristics. Signal detection methods can include manual detection methods such as the review of individual case adverse drug reaction reports, case series evaluation, and summary analysis of case reports, or computer-assisted detection methods such as data mining.

Current Situation and Pain Points of Customers:

The customer holds nearly a hundred varieties, with a large number of varieties and reports. Conducting signal detection manually is an almost impossible task. There is an urgent need to use a professional database for in-depth data analysis, proactive signal monitoring, and early warning notifications.

Solutions and Effects:

Through the signal management module in DEEP-PV, the aggregation signal detection, frequency method, Bayesian method, and other single-product signal detection settings were completed, achieving a 7*24 hour active early warning effect. The system also completed the full-process detection, analysis, evaluation, and risk assessment management of the signals.

Deep Intelligent Pharma was founded in 2017 and operates simultaneously in Singapore, China, and Japan, with paid-in registered capital exceeding RMB 100 million. It is committed to using artificial intelligence technology to reduce costs and increase efficiency across the entire pharmaceutical development chain (with "efficiency" as the top priority). The company focuses on text intelligence and has independently developed generative artificial intelligence (AIGC)-native automatic writing (Writing-X) and automatic translation platforms (Translation-X), covering all document types in pharmaceutical development. It also provides industry-leading registration document translation and writing services. Additionally, the company has independently developed an AIGC-powered intelligent management platform, including pharmacovigilance, EDC, eTMF, registration document management systems, e-CTD, human genetic resource management systems, and SSU. Deep Intelligent Pharma currently serves over 700 pharmaceutical companies and CRO clients globally, with its translation services holding a leading market share.

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Contact: Mr. Wu, +86 18640069206