Life science data can be highly disjointed and complex yet rich in potential insights. There are a variety of common insight-generation activities carried out with functional groups and through different channels; however, the findings are often disjointed and rarely connected.
Consequently, insights are frequently missed in all the information noise. This leads to the insights not being appropriately acted upon when they could help bring the right treatments to patients who need them.
Virtual Science AI provides AI-based solutions for immediate insights that are customisable to connect and combine various public and company data sets into one platform view. By doing this, we make sense of unstructured life science data and drive digital alignment to help teams better comprehend evolving disease areas in real time.
This solution is delivered through Virtual Science AI’s pharma-compliant first-in-class AI system, which ingests relevant data and concisely synthesises the information to support the identification of trends and themes. This well-organised information can then be efficiently shared across the enterprise, enabling teams to have a more positive impact on the product/disease area.
The team at Virtual Science AI is committed to helping improve the life science industry’s engagement with its external stakeholders and insight management teams. Headquartered in London and with operations in Europe, North America, Asia Pacific, and Latin America, Virtual Science AI creates cutting-edge software as a service (SaaS) and Artificial Intelligence solutions in the life-science and healthcare sectors. Notably, Virtual Science AI is trusted by 12 of the top 20 pharmaceutical companies and numerous leading biotechnology companies.
Tom Hughes, the CEO of Virtual Science AI, outlines the impact that the therapeutic area landscape analysis solution is already having:
“We have built a game-changing solution for therapeutic area landscape analysis. It frees up teams from highly manual analysis tasks, allowing them to spend more time responding to trends to have a positive effect faster.
“The therapeutic area analysis solution has already been deployed and validated by numerous leading pharmaceutical companies across different functions, and the feedback is very positive on the advantages gained.”
Chin Han Chen, Chief Technology Officer of Virtual Science AI and leading expert in the field of AI, added:
“We have developed a modular approach to AI models that is pharma-compliant, enabling us to seamlessly scale with new AI models and features. The models become more accurate to best serve different life science company therapeutic area landscape use cases.
“AI-driven insight-generation outperforms human-generated insights due to its reduced bias, resulting in superior accuracy.”
SOURCE: GlobeNewswire
