5 Top Clinical Algorithm Solutions Impacting Healthcare

We analyzed 250 Clinical Algorithm Solutions. Inflammatix, Holmusk, Optellum, SIME CLINICAL AI, and Dianovator develop 5 top solutions to watch out for. Learn more in our Global Startup Heat Map!

Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups working on solutions for the healthcare industry. As there is a large number of startups working on a wide variety of solutions, we decided to share our insights with you. This time, we are taking a look at 5 promising clinical algorithm solutions.

Heat Map: 5 Top Clinical Algorithm Solutions

For our 5 top picks, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 5 interesting examples out of 250 relevant solutions. Depending on your specific needs, your top picks might look entirely different.


Click to enlarge

Which startups develop the other 245 solutions?


Inflammatix – Acute Infections & Sepsis Diagnostics

In the worst cases, sepsis leads to a life-threatening condition called “septic shock” that can quickly lead to the lungs, kidneys, and liver failure. Faster diagnosis of acute infections and sepsis enables faster treatment and better patient outcomes. Clinical algorithms for the diagnosis of the above-mentioned diseases help determine the presence, type, and severity of infection to make smarter antibiotic prescribing and admission decisions.

US-based Inflammatix’s solution measures a patient’s immune response using proprietary algorithms to generate clinically actionable results in less than 30 minutes. The solution is clinically validated in numerous independent cohorts involving thousands of patients – results that were already published in medical journals.

Holmusk – Clinical Decision Support for Psychiatry

Nowadays, mental health disorders remain the highest unmet medical need, surpassing cardiovascular disease, diabetes and cancer with cumulative economic burden exceeding 16 Trillion USD in direct and indirect costs. Specialty EHR and data analytics platforms that work on real-world data help to satisfy the above-mentioned need by recognizing disease progression and recommendation of personalized treatment strategies.

Singaporean startup Holmusk works to create a specialty EHR system and database built exclusively for neuroscience disorders to advance data-driven, decision-making in mental health practice and research. The company also develops proprietary technology for analysis of real-world data across other chronic metabolic diseases including diabetes, cardiovascular disease, chronic kidney disease, etc. Integrating the analytics on metabolic diseases with mental health platforms enables the generation of deeper health insights.

Optellum – Lung Cancer Diagnostics

Lung cancer is the leading cause of cancer death among both men and women. Early diagnosis and choice of right treatment are crucial for patient survival. In response to this challenge, startups are creating clinical decision support software for lung cancer diagnosis & treatment.

Based in the UK, Optellum develops a clinical decision support tool for personalized early diagnosis & treatment of lung cancer. This system is based on Artificial Intelligence (AI) and machine learning algorithms applied to the world’s largest clinical dataset.

SIME CLINICAL AI – Neonatal Risk Prediction

Respiratory Distress Syndrome (RDS) is the leading cause of mortality in premature babies. That’s why technologies and algorithms that enable fast and accurate diagnostic of RDS are literally life-saving.

One of such technologies is an AI-powered neonatal Lung Maturity Test test, developed by the UK-based company SIME CLINICAL AI. The test is proven to predict RDS with high sensitivity in two clinical trials. SIME’s Data Engine generates unique data from biological samples at the point of care. This data is then analyzed by the platform’s proprietary AI algorithms to predict diseases.

Dianovator – Patient-Specific Insulin Therapy Management

In order to improve glucose control in insulin-treated diabetes, and take into account patient-specific characteristics, startups are developing insulin management tools for personalized glycemic control. These algorithm-based platforms allow patients and their doctors to gain insights on how to adjust insulin management for a particular patient.

The Swedish startup Dianovator develops Diact Pro, a solution that consists of a cloud platform with a web-based tool in which a patient’s individual data is analyzed in order to determine the optimal dosage of insulin. Clinicians can see the results of the analysis via Diact Pro’s portal as well. This platform is CE marked as a medical device.

What About The Other 245 Clinical Algorithm Solutions?

While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence for your Proof of Concept (PoC), partnership, or investment targets. The 5 startups showcased above are promising examples out of 250 we analyzed for this article. To identify the most relevant solutions based on your specific criteria and collaboration strategy, get in touch.

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