ConnectedLife and Ocean Protocol Partner to Deliver Personalized Parkinson’s Disease Therapies Using AI and Blockchain

VCBeat (WeChat Official Account: vcbeat) has learned that ConnectedLife, a medical artificial intelligence company headquartered in Singapore, announced on March 20 a partnership with the Singapore-based non-profit Ocean Protocol Foundation. The collaboration aims to jointly advance the diagnosis and treatment of Parkinson’s disease by enabling the secure sharing of patient-generated data.

ConnectedLife was founded in Singapore in 2013. With a precision medicine team based in Munich, Germany, and an engineering team in Hyderabad, India, the company integrates smart living and smart health solutions. As an expert in connected devices, cloud systems, data analytics, and artificial intelligence applications, ConnectedLife’s unique technology portfolio provides a highly modular and cost-effective Internet of Things (IoT) platform for the global smart living and precision medicine industries.

Ocean Protocol is a decentralized data exchange protocol and AI services network that leverages blockchain technology and cryptocurrencies to enable users to share and sell data in a secure and transparent manner, while ensuring traceability and information transparency for all stakeholders. By integrating decentralized blockchain technology, a data-sharing framework, and an ecosystem encompassing the data economy and related services, Ocean Protocol aims to launch a data economy network that reaches every individual and company, empowering people to derive value from data. The network provides a tokenized service layer that exposes data, storage, computing resources, and algorithms, and offers a set of deterministic proofs as verifiable service agreements.

Worldwide, more than 10 million people are living with Parkinson’s disease, and there is no known cure. Currently, the dopamine precursor levodopa remains the gold-standard treatment, yet it primarily addresses only the most prominent symptom of bradykinesia (loss of spontaneous movement). However, long-term therapy often leads to motor fluctuations, a problem that has not been adequately resolved by non-personalized medication regimens and strict dosing schedules. Parkinson’s disease continues to be a major focus of numerous digital health initiatives.

ConnectedLife leverages the integration of Internet of Things (IoT) and deep learning technologies to continuously collect movement data, enabling objective monitoring of motor symptoms in patients with Parkinson’s disease. In clinical trials conducted with the National Neuroscience Institute of Singapore and other research partners, the company has amassed tens of thousands of minutes of free-living movement data from Parkinson’s patients. Over time, ConnectedLife continuously processes this movement data to develop predictive models for the objective detection of motor symptoms associated with Parkinson’s disease.

In this collaboration, ConnectedLife’s high-resolution motion and biomedical data provided objective symptom measurements, while Ocean Protocol supplied the technology to share patient-generated data in a privacy-preserving and secure manner via blockchain. The two parties collaborated to develop personalized therapies that keep patients within their optimal therapeutic range, thereby preventing unnecessary side effects and symptom fluctuations and significantly improving their quality of life.

Dr. Franz MJ Pfister, Chief Medical Officer at ConnectedLife, stated, “We are passionate about leveraging AI to address major challenges in healthcare. However, health data remains locked and unavailable for sharing due to societal concerns over privacy and security control. Removing these barriers could enable billions of patients with chronic conditions to receive effective treatment through AI-driven prevention, early diagnosis, and personalized therapies.”

Regarding this collaboration, Trent McConaghy, co-founder of Ocean Protocol, stated, “Ocean will enable algorithms and models to be transmitted across data networks without exposing the underlying data. This helps unlock more data to advance the diagnosis and treatment of Parkinson’s disease.”

(Compiled by Li Chengping)