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#106, Precision Medicine for Neurodegenerative Diseases, with Brian Pepin from Rune Labs
Manage episode 447519802 series 3291628
Rune Labs is pioneering the use of real-world data to revolutionize therapy development for neurodegenerative diseases like Parkinson's. In this episode, Mike Tarselli, Specialist Leader - HCLS Data & AI at AWS, talks to Brian Pepin, CEO of Rune Labs, about the company's innovative approach to digital biomarkers and how they're working to make a difference in the lives of patients.
- What is Rune Labs' approach to decoding neurodegenerative diseases?
- Rune Labs uses real-world data to accelerate therapeutic development for neurodegenerative diseases like Parkinson's, providing access to engaged clinicians, patients, and longitudinal datasets. As precision medicine gains traction, companies like Rune Labs are well-positioned to drive innovation in this space.
- How are digital biomarkers revolutionizing disease tracking?
- Rune Labs aims to quantify subjective clinical assessments using standardized sensing and data formats, offering a more objective, repeatable, and scalable way to track disease progression and medication effects compared to traditional rating scales. This approach holds promise for neurology, which lacks quantitative biomarkers.
- What is StrivePD, and how does it reimagine dopamine management?
- StrivePD, Rune Labs' flagship product, is a dopamine care management system that automatically detects and classifies Parkinson's symptoms using the Apple Watch, providing insights to patients and clinicians for better disease management. This innovative solution reduces cognitive burden and improves access to care.
- How is Rune Labs empowering precision clinical trials?
- By leveraging data and their network, Rune Labs aims to shift the economics of phase 3 clinical trials, enabling more precise measurements and identifying better responders for promising Parkinson's drugs. Their approach could make economically viable trials for disease-modifying therapies a reality.
- How is Rune Labs harnessing AI for personalized care?
- Rune Labs utilizes machine learning on dense time series data and large language models to identify patterns predictive of medication responses, progression events, and risk factors, enabling contextualized feedback and virtual patient coaching. This multimodal approach exemplifies the potential of AI in healthcare.
- What advice does Brian Pepin, Rune Labs' CEO, have for founders?
- Brian Pepin advises founders to clearly identify and focus on one major risk at a time (scientific, clinical, or business model) and ensure early team and investors are committed to the long-term vision in healthcare, which often spans 10+ years.
To learn more about Rune Labs and their innovative approach to neurodegenerative diseases, visit their website or learn more about their Parkinson’s patient app, StrivePD, by visiting www.strivepd.com.
Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation.
Please take a moment and let us know what you think of the podcast, access our feedback survey here.
116 قسمت
Manage episode 447519802 series 3291628
Rune Labs is pioneering the use of real-world data to revolutionize therapy development for neurodegenerative diseases like Parkinson's. In this episode, Mike Tarselli, Specialist Leader - HCLS Data & AI at AWS, talks to Brian Pepin, CEO of Rune Labs, about the company's innovative approach to digital biomarkers and how they're working to make a difference in the lives of patients.
- What is Rune Labs' approach to decoding neurodegenerative diseases?
- Rune Labs uses real-world data to accelerate therapeutic development for neurodegenerative diseases like Parkinson's, providing access to engaged clinicians, patients, and longitudinal datasets. As precision medicine gains traction, companies like Rune Labs are well-positioned to drive innovation in this space.
- How are digital biomarkers revolutionizing disease tracking?
- Rune Labs aims to quantify subjective clinical assessments using standardized sensing and data formats, offering a more objective, repeatable, and scalable way to track disease progression and medication effects compared to traditional rating scales. This approach holds promise for neurology, which lacks quantitative biomarkers.
- What is StrivePD, and how does it reimagine dopamine management?
- StrivePD, Rune Labs' flagship product, is a dopamine care management system that automatically detects and classifies Parkinson's symptoms using the Apple Watch, providing insights to patients and clinicians for better disease management. This innovative solution reduces cognitive burden and improves access to care.
- How is Rune Labs empowering precision clinical trials?
- By leveraging data and their network, Rune Labs aims to shift the economics of phase 3 clinical trials, enabling more precise measurements and identifying better responders for promising Parkinson's drugs. Their approach could make economically viable trials for disease-modifying therapies a reality.
- How is Rune Labs harnessing AI for personalized care?
- Rune Labs utilizes machine learning on dense time series data and large language models to identify patterns predictive of medication responses, progression events, and risk factors, enabling contextualized feedback and virtual patient coaching. This multimodal approach exemplifies the potential of AI in healthcare.
- What advice does Brian Pepin, Rune Labs' CEO, have for founders?
- Brian Pepin advises founders to clearly identify and focus on one major risk at a time (scientific, clinical, or business model) and ensure early team and investors are committed to the long-term vision in healthcare, which often spans 10+ years.
To learn more about Rune Labs and their innovative approach to neurodegenerative diseases, visit their website or learn more about their Parkinson’s patient app, StrivePD, by visiting www.strivepd.com.
Get in touch with AWS here to learn how we can help your organization accelerate healthcare innovation.
Please take a moment and let us know what you think of the podcast, access our feedback survey here.
116 قسمت
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