Periodic Reporting for period 1 - BInno2scalek01 (Scale Business and Technology to Impact on Disease Research by with Lossless and Efficient Data Analysis)
Reporting period: 2022-07-01 to 2023-06-30
In the highly dynamic field of health and disease research, data volume and variety present a significant business and process challenge. Especially the data variety – driven by the complexity of biology itself and the large variety of novel measurement technologies - has results in an overwhelming and fragmented landscape with considerable unexplored potential for insight generation. At knowing01, we are addressing this major bioinformatic challenge by developing a technology that explores the relationships between individual biodata types. This initiative sets the stage for more robust day-to-day research as well as unlocking novel high-demand data science strategies, with the ultimate goal of advancing disease research by unlocking biodata across varieties at scale. Our vision is fueled by an imperative to scale, reinforced by our ongoing efforts in validating our product-market-fit in the European market and establishing a business model ready to scale.
Our objectives for the Women TechEU project were three-fold. First, we aimed to unlock reseller opportunities by attracting a pivotal key partner through strategic market research and business model upgrade (O1). Second, we intended to future-proof our infrastructure and database technologies by incorporating expert knowledge and adapting to data privacy needs (O2). Lastly, we wanted to gain public visibility to entice strategic investors for our upcoming capital raises, building confidence in contract negotiations (O3). These objectives aligned with our dual ambition to scale in both the business and technology dimensions. With a seminal partnership from Women TechEU, our vision is set to become the go-to provider for biomedical data use, drastically scaling up our user base and directly impacting disease research. The expected results include increased research quality, decreased data loss, and enhanced accessibility to public data, thus improving the overall research cost-to-outcome ratio.
Our objectives for the Women TechEU project were three-fold. First, we aimed to unlock reseller opportunities by attracting a pivotal key partner through strategic market research and business model upgrade (O1). Second, we intended to future-proof our infrastructure and database technologies by incorporating expert knowledge and adapting to data privacy needs (O2). Lastly, we wanted to gain public visibility to entice strategic investors for our upcoming capital raises, building confidence in contract negotiations (O3). These objectives aligned with our dual ambition to scale in both the business and technology dimensions. With a seminal partnership from Women TechEU, our vision is set to become the go-to provider for biomedical data use, drastically scaling up our user base and directly impacting disease research. The expected results include increased research quality, decreased data loss, and enhanced accessibility to public data, thus improving the overall research cost-to-outcome ratio.
In addressing our objectives, substantial work was performed, resulting in significant achievements in three main areas:
1. Market Research and Communication Material: Market research was conducted, focusing on the differentiation between biotech and academic segments and pinpointing small to mid-size biotechs as our target clients. This research helped us recognize the changing landscape, and refine our value position within the context of the quickly evolving AI context and continued ROI pressure in disease research. Consequently, a white paper was derived, along with sales and marketing material that was tested positively in the biotech market at two industry fairs. These insights are now integrated into our sales process.
2. Customer Validation and Business Model Development: Leveraging insights and material from market research, we secured our first biotech clients as paying clients, marking a proof point beyond the academic sector. Our business model has been tuned to incorporate new learnings and the overall economic situation, including a cooling investment climate within the biotech industry.
3. Technical Assessment and Developments - Data Security and Privacy Concept: We addressed limitations of our graph algorithms in context of the rising demands of our clients’ data, by future-proofing our underlying tech-stack, moving towards a high-performance computing infrastructure. This shift enabled us to refine and accelerate data adaptor, integration, and analysis algorithms. Furthermore, we successfully tested and finalized the integration of distributed noSQL databases and upgraded to a Big Data analytics engine for high-demand data science processing. Measures to increase data security and IT security were also implemented.
4. Activity Lead, Management, and Integration: The WLP program was instrumental in enabling us to work on multi-dimensional objective assessment of our readiness levels. We have adopted this objective tool in our strategic and tactical planning cycles to ensure sustainable growth across all dimensions.
These combined efforts have led to key advances in our understanding of the biotech market, the refinement of our business model, the enhancement of our technical infrastructure, and the development of strategic management tools. These achievements set a firm foundation for the future growth and scalability of our offerings and technologies.
1. Market Research and Communication Material: Market research was conducted, focusing on the differentiation between biotech and academic segments and pinpointing small to mid-size biotechs as our target clients. This research helped us recognize the changing landscape, and refine our value position within the context of the quickly evolving AI context and continued ROI pressure in disease research. Consequently, a white paper was derived, along with sales and marketing material that was tested positively in the biotech market at two industry fairs. These insights are now integrated into our sales process.
2. Customer Validation and Business Model Development: Leveraging insights and material from market research, we secured our first biotech clients as paying clients, marking a proof point beyond the academic sector. Our business model has been tuned to incorporate new learnings and the overall economic situation, including a cooling investment climate within the biotech industry.
3. Technical Assessment and Developments - Data Security and Privacy Concept: We addressed limitations of our graph algorithms in context of the rising demands of our clients’ data, by future-proofing our underlying tech-stack, moving towards a high-performance computing infrastructure. This shift enabled us to refine and accelerate data adaptor, integration, and analysis algorithms. Furthermore, we successfully tested and finalized the integration of distributed noSQL databases and upgraded to a Big Data analytics engine for high-demand data science processing. Measures to increase data security and IT security were also implemented.
4. Activity Lead, Management, and Integration: The WLP program was instrumental in enabling us to work on multi-dimensional objective assessment of our readiness levels. We have adopted this objective tool in our strategic and tactical planning cycles to ensure sustainable growth across all dimensions.
These combined efforts have led to key advances in our understanding of the biotech market, the refinement of our business model, the enhancement of our technical infrastructure, and the development of strategic management tools. These achievements set a firm foundation for the future growth and scalability of our offerings and technologies.
Our project has achieved results that go beyond the current state of the art in biomedical data management and utilization. By further developing our cutting-edge algorithms, infrastructure, and analytics engines, we have unlocked unparalleled capabilities in data exploration and relationship mapping within disease research, already deployed for our inaugural clients beyond the academic market sector: SME biotechs. The integration of distributed noSQL databases with high-performance computing infrastructure represents a significant leap in handling complex, varied biomedical data. These advancements have not only established a foundation that benefits our clients but also paved the way for future innovations in the field. Moreover, they have enabled us to maintain pilot project timelines that are markedly shorter than those achievable without our next generation software solution.
However, to ensure further uptake and success, key needs such as continuous research, demonstration, commercialization, access to markets and financing, internationalization, and a supportive regulatory and standardization framework must be addressed. These elements will be essential in capitalizing on our achievements, leveraging our unique position in the market, and advancing data usage in disease research.
However, to ensure further uptake and success, key needs such as continuous research, demonstration, commercialization, access to markets and financing, internationalization, and a supportive regulatory and standardization framework must be addressed. These elements will be essential in capitalizing on our achievements, leveraging our unique position in the market, and advancing data usage in disease research.