Large-scale language models (LLMs) trained on large datasets are increasingly being rebuilt Biomedical research and medical innovation. These advanced systems can accelerate Genomics research, improving clinical documentation, enhancing real-time diagnostics, supporting clinical decision making, and even speeding up drug discovery.
However, despite its potential, LLM faces significant limitations. Healthcare systems rely heavily on structured data sets, AI models often struggle with edge cases such as rare diseases or unusual medical conditionswhen reliable and representative data are lacking.
To address this challenge, New York-based Mantis Biotech We are developing a platform designed to bridge this Critical data gaps in healthcare and biomedical research.
Building a digital twin of the human body
Mantis Biotech aims to solve the problem of data scarcity. Synthetic datasets powering the “digital twin” of the human body. These digital twins are Physics-based predictive model something that reproduces humans anatomy, physiology, behavior.
Integrated into the company’s platform are: Multiple disparate data sources and convert them into high-fidelity simulations. These simulations allow researchers and clinicians to: Analyze human performance, simulate medical scenarios, and test treatments without relying solely on real patient data..
As a result, digital twins can become powerful tools that: Data aggregation, predictive analytics, and medical innovation.
Applications in healthcare, sports, and medical research
Mantis Biotech is positioning its digital twin technology for several applications across medicine and research. These include:
- Research and testing new medical procedures
- Training a surgical robot using a simulated human model
- Prediction of medical conditions and behavioral patterns
- Strengthening clinical research and experiments
For example, the platform Injury risks specific to athletes. According to Georgia Witchell, Founder and CEO of Mantis Biotechthe system can analyze various factors such as: Training intensity, diet, physical performance, activity history.
Sports teams can use these inputs to estimate the likelihood that an athlete will develop injuries such as: achilles tendon injurypreventive measures are possible.
How the digital twin platform works
To build accurate digital twins, the platform collects information from a wide range of sources, including:
- medical textbook
- motion capture camera
- biometric sensor
- training log
- medical image data
As reported by techcrunch, the system then LLM-based pipeline Route, validate, and synthesize these data streams. After processing the information, the platform physics enginegenerates a realistic model of human anatomy and movement.
These models can be used to: Train predictive algorithms and simulate real-world biological behavior.
“We can take these disparate data sources and turn them into predictive models of human performance. Our technology is extremely valuable whenever we want to predict how humans will perform,” Witchell explained.
Physics engine improves synthetic data accuracy
Key innovations in the platform include: physics engine layerThis ensures that synthetic datasets remain based on realistic biological mechanics.
By modeling, Physical characteristics of human body structureallows the system to create accurate simulations even in the absence of real-world data.
For example, Witchell explained: Estimating the hand pose of a person who has lost a finger This is difficult because the publicly available datasets for such cases are very limited.
However, digital twin systems can easily generate such data by: Modify physics-based anatomical models and recreate lost structureswhich creates a new training dataset for the AI system.
Addressing data gaps in rare diseases
One of the biggest opportunities for this platform is rare disease or abnormal medical conditionwhen data availability is very limited.
In many cases, Patient Privacy Laws, Ethical Considerations, and Regulatory Restrictions It makes it difficult to collect and share real-world datasets. As a result, AI models have a hard time learning from these situations.
Digital twins provide a solution by allowing you to: Experiments and simulations using virtual human body models in place of real patient data.
Witchell believes this approach will help researchers explore new medical scenarios. Protect patient privacy and prevent misuse of personal health data.
Early introduction to professional sports
Although this technology has broader biomedical potential, Professional sports teams are early adopters. of the platform. According to Witchell, one of Mantis Biotech’s major customers is nba team.
created by the system Detailed digital representation of an athletetrack changes in physical performance over time.
For example, the platform can analyze an athlete’s performance. Jump performance is evolving day by dayWhile comparing elements such as Sleep patterns, training intensity, and arm movement frequency. These insights will help your team Optimize your training and reduce your risk of injury.
Funding and expansion plans
To accelerate development, Mantis Biotech recently raised $7.4 million in seed funding. This funding round was led by db VCwith participation from Y Combinator, Liquid 2, and several angel investors.
The company plans to use the funds to: Grow your team, strengthen your marketing efforts, and accelerate your go-to-market strategy.
Future focus: Preventive medicine and drug research
Looking to the future, Mantis Biotech aims to: Extending technology beyond sports analytics to preventative medicine and pharmaceutical research..
The company plans to make the platform accessible to everyone Pharmaceutical laboratories and researchers involved in FDA clinical trials. Digital twins could help scientists by simulating how patients respond to treatments Predict treatment outcomes and optimize drug development processes.
Ultimately, the company realized that its technology Safer experiments, faster medical discoveries, more personalized medical solutions.
Digital twins could shape the future of biomedical innovation
As dependence on medical care increases AI, predictive analytics and advanced simulationdigital twin technology could play an important role in the following areas: Closing data gaps and enabling new forms of biomedical research.
By combining LLM, synthetic data generation, physically based modelingMantis Biotech aims to transform the way researchers study the human body and create a platform that enables the development of new medical advances.
