Prognos

Prognos, founded in 2010, emerged as a healthcare analytics company focused on leveraging data to improve patient outcomes.

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Prognos uses data science to predict disease progression and improve healthcare outcomes.

Prognos, founded in 2010, emerged as a healthcare analytics company focused on leveraging data to improve patient outcomes. Initially concentrating on predictive analytics for healthcare providers, Prognos expanded its scope to include pharmaceutical companies, payers, and diagnostic labs. The company’s core mission revolves around using advanced data science to identify patterns in healthcare data, enabling earlier disease detection and more personalized treatment plans.

Prognos has raised significant funding over the years, including a $20.5 million Series B round in 2018 led by Safeguard Scientifics, which has been a consistent investor. The company’s revenue trajectory has been upward, though specific figures remain undisclosed. Prognos operates in a competitive landscape, facing rivals like Flatiron Health and Tempus, but has carved out a niche with its proprietary algorithms and partnerships with major healthcare entities.

Recently, Prognos has been integrating AI more deeply into its analytics platforms, aiming to enhance predictive accuracy and scalability. The company’s headcount is estimated to be between 200-400 employees, with a strong focus on data scientists and healthcare experts. Prognos continues to innovate, recently launching new tools aimed at real-time data processing and integration with electronic health records (EHRs).

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Who buys this

  • Pharmaceutical companies
  • Healthcare providers
  • Diagnostic labs
  • Insurance payers
  • Research institutions

Strengths and what to watch

Strengths

  • Proprietary algorithms for predictive analytics
  • Strong partnerships with major healthcare entities
  • Deep integration with electronic health records (EHRs)

Watch for

  • Intense competition from established players like Flatiron Health
  • Regulatory challenges in healthcare data usage
  • Potential scalability issues with real-time data processing

Key Information

Founded
2010

Frequently Asked Questions

What does Prognos do in healthcare?

Prognos applies data science to predict disease progression and improve treatment outcomes. Founded in 2010, it analyzes healthcare data patterns to enable earlier detection and personalized care plans for providers, pharma companies, and insurers through proprietary algorithms and EHR integrations.

How does Prognos predict disease progression?

Prognos uses advanced data science and AI to identify patterns in healthcare data. Its proprietary algorithms analyze historical and real-time patient data from EHRs and diagnostic labs to forecast disease trajectories, helping clinicians intervene earlier with personalized treatment strategies.

Who uses Prognos analytics services?

Prognos serves pharmaceutical companies developing targeted therapies, healthcare providers optimizing treatment plans, diagnostic labs improving test accuracy, insurance payers assessing risk, and research institutions studying disease patterns. Its solutions integrate across these sectors through data partnerships.

How does Prognos compare to Flatiron Health?

While both specialize in healthcare analytics, Prognos focuses on predictive disease modeling across broader sectors including diagnostics and payers. Flatiron concentrates more on oncology-specific EHR data. Prognos differentiates with proprietary algorithms and real-time processing tools for diverse healthcare stakeholders.

What funding has Prognos received?

Prognos raised $20.5 million in a 2018 Series B round led by Safeguard Scientifics, building on earlier investments. While revenue figures are undisclosed, the company shows upward growth with 200-400 employees, primarily data scientists and healthcare specialists driving its analytics platforms.

Can Prognos integrate with electronic health records?

Yes, Prognos emphasizes deep EHR integration as a core strength. Its platforms connect with major electronic health record systems to enable real-time data processing, supporting clinical decision-making and predictive analytics for healthcare providers and research institutions.

Sources

  1. www.reuters.com — AI reshaping workforce
  2. www.sec.gov — Financial disclosures
  3. www.sec.gov — Financial disclosures
  4. www.reuters.com — Economic impact of regional instability