Periodic Reporting for period 1 - AIIPDD (AI-driven IP Intelligence Engine for Drug Discovery)
Période du rapport: 2023-07-01 au 2024-04-30
Today, new drug development on average costs up to $2.6 billion and takes 10-14 years. The global health emergency caused by the spread of the deadly new coronavirus has become a crucial real-life test case for the industry, aiming to dramatically reduce the time it takes to create new vaccines and drugs to combat emerging pandemics. While AI technologies help identify thousands of new molecules that could potentially be turned into medicines, it's crucial to quickly establish the novelty of the most promising candidates. Currently, more than 135 million patents are published, creating a vast corpus of information that needs to be searched to determine, for example, the novelty of a compound or the variety of components within complex compositions. The exploding data volume and increasing complexity of patents make searches a very time-consuming process. Additionally, professional patent search tools in biochemistry are expensive and not accessible to small and medium-sized industry players. Semantic Intelligence is on a mission to solve these challenges by building an AI-driven IP Intelligence Engine to help accelerate R&D processes in pharma. The main objective of this project was to plan and execute a potential customer outreach campaign to identify potential customers for our API and conduct testing sessions.
The Women TechEU grant enabled Semantic Intelligence to carry out a comprehensive customer outreach campaign for our IP Intelligence Engine API. The project spanned from July 2023 to April 2024 and involved three main activities: campaign preparation and planning, campaign execution, and API testing with interested customers.
1) Campaign Preparation & Planning:
The team leveraged existing contacts and networked through conferences and social media to identify and target key customer segments: AI-driven drug discovery companies, small and mid-size pharma firms, and legal service providers for the pharma industry. In this stage, new detailed technical and marketing materials were created, and a list of over 2000 potential customers was compiled.
2) Campaign Execution:
During campaign execution, a multi-channel outreach strategy was implemented. The team conducted product demonstrations, discussing API capabilities and pilot testing terms, and engaged with R&D professionals to refine the API's next development tasks based on their feedback.
3) API Testing with Interested Customers:
We secured two customers for API testing, provided technical support for API integration, including virtual sessions and documentation, and collected valuable feedback.
The main achievements of the project were: the development of detailed technical documentation and marketing materials, building an initial list of over 2000 individual potential customers through effective networking, conducting successful multi-channel outreach and product demonstrations, achieving successful API integration and testing with customers.
During the project, the team gained valuable insights into R&D challenges for future API improvements and established a strong foundation for future development and market expansion.
1) Campaign Preparation & Planning:
The team leveraged existing contacts and networked through conferences and social media to identify and target key customer segments: AI-driven drug discovery companies, small and mid-size pharma firms, and legal service providers for the pharma industry. In this stage, new detailed technical and marketing materials were created, and a list of over 2000 potential customers was compiled.
2) Campaign Execution:
During campaign execution, a multi-channel outreach strategy was implemented. The team conducted product demonstrations, discussing API capabilities and pilot testing terms, and engaged with R&D professionals to refine the API's next development tasks based on their feedback.
3) API Testing with Interested Customers:
We secured two customers for API testing, provided technical support for API integration, including virtual sessions and documentation, and collected valuable feedback.
The main achievements of the project were: the development of detailed technical documentation and marketing materials, building an initial list of over 2000 individual potential customers through effective networking, conducting successful multi-channel outreach and product demonstrations, achieving successful API integration and testing with customers.
During the project, the team gained valuable insights into R&D challenges for future API improvements and established a strong foundation for future development and market expansion.
At the end of the project, Semantic Intelligence achieved the development of high-quality technical documentation and marketing materials, built a robust list of over 2000 potential customers, conducted successful outreach and demonstrations, and integrated the API with two customers. These outcomes provide a strong foundation for future growth, informed development, and broader market adoption. The key needs for further uptake and success include continuous improvement of the API based on customer feedback and emerging industry trends; securing additional funding to support scaling efforts and expanding market reach; enhancing commercialization strategies, expanding outreach efforts to international markets and ensuring compliance with industry regulations to facilitate market entry and acceptance.