The catalyst projects current call is closed. Please check back for future calls.
Princess Margaret (PM) Data Science Program’s mission is to improve patient outcomes and optimize the delivery of value-based healthcare and cancer research. We will achieve this goal by building informatics resources and developing innovative data science methods.
Data science promises to not only collect and connect health-related data but also develop integrative computational analytical approaches to extract patterns and associations that could be leveraged to better monitor and improve quality of care and open new avenues for research.
The success of the Program requires high engagement from both clinical and research teams.
To promote wider adoption of outcomes collection, we will offer:
• optimized workflows
• improved data capturing/documentation accuracy
• data to interact with patients
Engagement from the research teams will help to integrate large multimodal data including:
• large-scale imaging
• pharmacological profiles
• other phenotypes from patient samples or derived cancer models
The program will centralize cancer data in the UHN Data Lake; building high quality, comprehensive, integrated cancer data set. Our team is led by:
Alejandro Berlin MD, MSc (Clinical Lead)
Benjamen Haibe-Kains, Ph.D (Scientific Lead)
David Jaffray, Ph.D (Architecture Lead)
Tran Truong (Program Director)
Our team consists of data analysts, project managers and software developers that have expertise in different data domains to support data science projects.
In addition to our team, we are working towards an infrastructure that supports the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles of data management and resources to support large datasets and computational requirements. The PM Community will be able to leverage the team expertise, resources, and infrastructure of the Data Science program.
Application for Support
The PM Data Science Program is looking to support at least two Catalyst Projects per year. The catalyst projects are expected to foster engagement from the broader PM community. The projects will help inform and prioritize the development of the PM Data Science framework. Catalyst projects must show the potential for large-scale data integration and computational analysis. A balance of clinical, translational and basic research projects will be selected.
The PM Community is invited to complete and submit the LOI template. The PM Data Science leadership team will select projects based on the review criteria and contact the applicant to schedule a meeting. The meeting will allow teams to discuss the details, resourcing, and feasibility of the project. After the meeting, the leadership team will determine if the applicant should submit a full proposal. The full proposal will be reviewed by the PM Data Science Program Steering and Oversight Committees for a final decision.
Please note the following important dates
|Letter of Intent (LOI) Due Date||July 15, 2019|
|LOI Selection||Aug 1, 2019|
|Meeting with PM Data Science Team||Aug 1, 2019 – Sep 1, 2019|
|Full Proposal Due Date||Oct 1, 2019|
|Results Announcement||Nov 1, 2019|
All submissions will be reviewed based on the following criteria:
- What value does this project provide for the clinical and/or research setting?
- How does this project foster engagement from the PM community?
- How does this project contribute to building a data science framework?
- How does this project help the development of expertise within the PM Data Science Program?
- Is the data needed for the project available or does it need to be collected?
- What expertise is required to support the project?
- Describe the phases, deliverables & timelines, success metrics, and end-user involvement.
- Can the project be completed within a stated timeframe?
- What is the defined translational plan into clinical and/or research setting?
Letter of Intent (LOI)
A successful LOI should describe the value provided for clinical and/or research, the rationale behind the project, project deliverables and the data to be curated.
The LOI should be structured as follows:
- Participant Information
- Proposal Information (title, abstract)
- The goal of the project (expected outcomes, translation)
- Feasibility of the project (rationale, methodology, data source, timeline, funding)
- References and Appendices (i.e. scientific literature)
The deadline for receipt of LOIs is 11:59 EST July 15th, 2019. LOIs should be submitted as a single PDF file attachment in an e-mail message addressed to PM Data Science Program at email@example.com.