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Visualizing the Biotech Landscape: Launching Mindgram Clinical Edge

  • Shrey Verma
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  • Jan 24, 2022
    /
  • 4 MIN READ

We are at a unique moment in history where the speed of new innovation and breakthrough discoveries in biotech is accelerating in a non-linear fashion. In 2021, biotech companies raised north of $60 billion from investors and equity markets, marking the year as the biggest of all time. 

With money pouring into the sector, and a plethora of new pipeline assets and companies coming online (aided by scientists and PhDs jumping into the entrepreneurial fray), the speed and scale at which the industry is generating new data is unprecedented and is going to surpass anything that we have seen previously. In this ocean of data, it’s more critical than ever to surface the most valuable insights in order to make the best investment and business decisions.

We spoke to a wide range of stakeholders in the industry - academics, scientists, investors and business development executives - in the last year. One key insight stuck with us: researchers lack real-time visibility into scientific, regulatory and financial activity across thousands of biotech companies. From scientific milestones to regulatory catalysts, partnership deals to funding activity, keeping track of and interrogating the most relevant data points across companies and disease areas is a painstaking process often requiring hours of human research and data collection efforts.

We think, with the right tools, this challenge can be overcome in minutes. And that’s why we built Mindgram, an AI platform geared towards investors and corporations in the life sciences sector. Mindgram transforms unstructured textual information into structured data points and visual maps that researchers and business decision-makers can leverage to search, analyze and mine for new insights. 

The Product

We’ve built a high quality dataset by mining through millions of documents including scientific publications, news articles, financial filings, and posters and presentations. 

We leveraged AI and machine learning to automatically extract, normalize and link entities from unstructured data, and built a powerful content management system to add a human review layer on top of that. The latter ensures data integrity and accuracy of the most critical relationships in our knowledge graph. 

Today, the dataset has over 1.2 million canonical entities and relationships extracted from over 3 million documents. These entities cover drug products, diseases, companies, protein and gene targets, epidemiological data points, financial metrics, clinical trial data and news labels among others.

Mindgram’s engine has been trained to understand semantic relationships in scientific text and form logical connections that, in turn, powers all the analytics and search functionalities on the platform.

For example, consider clinical trial data. It is not only hard to gather, but even harder to organize. Valuable information is buried in scientific publications, press releases, posters, and presentations.

Leveraging AI, Mindgram has identified clinical trial results and data readouts for drug products across companies and disease areas in one place. We organized this information chronologically, making it easier for researchers to track progress and dive deeper into the science underpinning biotech assets. 

Identifying Concepts Embedded in Complex Documents

Linking Financial Numbers to Scientific Concepts

Understanding Semantic Logic

Our knowledge graph is continuously expanding. There are hundreds of new relationships and concepts being added to the system as you read this. We believe the connected world of biotech data we’re building will help advance research and business development, and direct capital and talent to the most promising assets and companies across the landscape.

To that end, we’ve designed Mindgram's Clinical Edge product to serve the biotech community in two ways: 1) a web application with powerful interactive components and search tools; and 2) a robust API service that can connect to existing systems and workflows, and significantly augment research capabilities.

The Road Ahead

We are entering an unprecedented phase in biotech where we will witness an onslaught of new companies pursuing a range of new scientific modalities and technology platforms to treat some of the most intractable diseases.

In this new world of much greater scale and complexity, there is an opportunity for a data-driven company like Mindgram to succeed. Our web-based platform will dramatically reduce the research burden for investors, business development teams and academic researchers, who must navigate the complex maze of science, capital and regulations impacting medicine.

To learn more about our product and how we can help accelerate your research workflow, schedule a demo with us.

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