What is Oncoshot?

Oncoshot provides a federated AI data system focused on enhancing the landscape of cancer clinical trials. It aims to bridge the gap between cancer patients seeking treatment options, hospitals conducting research, and industry partners, including pharmaceutical companies, CROs, and biotech firms, developing new therapies. The platform leverages real-time insights derived from its AI system to streamline processes and improve outcomes within the oncology sector.

The system offers distinct advantages for its users. For industry partners, Oncoshot helps shorten clinical trial enrolment periods, mitigate costly delays, and increase the success rate of site-level feasibility studies. Hospitals benefit from increased visibility and opportunities to engage with a wider network of global partners, thereby improving clinical trial access for their specific patient populations. Patients and their caregivers can utilize a complimentary self-service tool to explore and get matched with suitable clinical trials, providing potential new treatment avenues throughout their cancer journey. Oncoshot operates globally, with established partnerships in regions like Australia, India, and Singapore.

Features

Federated AI Data System: Utilizes AI across distributed data sources for insights.
Clinical Trial Matching: Connects patients with suitable clinical trials.
Site Feasibility Assessment: Helps industry partners evaluate potential trial sites.
Enrolment Acceleration: Aims to shorten the time needed to enrol patients in trials.
Ecosystem Connectivity: Links hospitals, industry, and patients within a network.
Self-Service Patient Tool: Offers a complimentary tool for patients/caregivers to find trials.

Use Cases

Accelerating patient enrolment in cancer clinical trials.
Improving the success rate of site-level feasibility studies for new cancer therapies.
Increasing hospital visibility to global pharmaceutical and biotech partners for trial collaboration.
Providing patients and caregivers with options for innovative cancer treatments through trial matching.
Facilitating data-driven decision-making for oncology research and development.
Supporting national-level oncology clinical trial ecosystems.