The ARPA-H PRECISE-AI Program Solicitation (ARPA-H-SOL-25-113) outlines requirements for submissions related to a proposal under the program. Proposers must utilize a specific template detailing technical and management strategies with concise descriptions of their project goals, methodologies, and anticipated impacts. Key components include a project summary that answers various critical questions regarding innovation and technical challenges, as well as a Technical Plan outlining milestones and schedules. The document emphasizes a structured format where specific sections such as the Proposal Summary, Goals and Impact, Technical Plan, and Management Plan must adhere to strict page limits and formatting guidelines. Proposers must provide a description of team capabilities, identifying key personnel and their roles, with resumes included for evaluation. A bibliography with relevant references is also required, aiding the context of the proposed work. The solicitation aims to foster high-risk, high-reward projects that advance the capabilities of artificial intelligence in healthcare. Ultimately, successful proposals are expected to significantly impact public health outcomes while maintaining adherence to innovation, feasibility, and clarity of presentation.

The ARPA-H PRECISE-AI Program Solicitation outlines the requirements for proposal submissions under solicitation number ARPA-H-SOL-25-113. Proposers must adhere to specific formatting guidelines and page limits, ensuring all proposals maintain clarity and conciseness. The document emphasizes the need for detailed descriptions of goals, innovative approaches, technical challenges, and the project's expected impact. Additionally, it requires a technical plan that outlines measurable milestones and the roles of key personnel. Proposal components include a proposal summary, an innovative claims table, goals and impact analysis, a technical plan, a capabilities/management plan, a bibliography, and resumes of key personnel. Each section must provide clear and objective content, with a focus on how the proposed work advances the current state of the art in AI technology. The solicitation aims to solicit innovative research that addresses significant technical challenges, fostering advancements that can potentially reshape existing methodologies and contribute positively to AI applications. Overall, it reflects the government’s commitment to support high-risk, high-reward projects with a clear framework for evaluation and accountability.

The ARPA-H PRECISE-AI Program Solicitation outlines a detailed framework for proposals aimed at advancing precise artificial intelligence in health. The document mandates the submission of a Task Description Document (TDD) that aligns with specified program milestones. Each proposal should include a comprehensive breakdown of tasks and subtasks within defined phases, detailing objectives, methodologies, and responsible organizations. Additionally, it identifies whether human or animal research is involved, along with measurable milestones that track progress. Deliverables must be clearly outlined, including data, software, or reports, while maintaining standards for intellectual property rights. Overall, the solicitation emphasizes the importance of structured and measurable approaches to achieve advancements in AI applications within the healthcare sector.

The ARPA-H Cost Proposal Spreadsheet outlines the financial components of a federal solicitation under Solicitation No. ARPA-H-SOL-25-113. It includes sections for proposer information, labor costs, subcontractor expenses, materials, equipment, travel, other direct costs, indirect costs, fees, and total pricing, along with provisions for cost-sharing and detailed categorizations of proposed expenditures for various phases of the project. Each phase is categorized by tasks (TA) and subtasks, displaying anticipated hours, rates, and total amounts. This structured approach allows for clear categorization of costs associated with each technical area over multiple years, addressing components crucial for funding and accountability in government grants. The document serves as a comprehensive financial plan to support the project, detailing cost proposals necessary for government review, compliance, and fiscal responsibility under the agency's guidelines.

This document outlines a sample Other Transaction Agreement (OTA) used by the Advanced Research Projects Agency for Health (ARPA-H). It establishes terms for collaboration between the U.S. Government and a selected Performer for research and development projects, aimed at advancing public health technologies. Key sections include the scope of the agreement, project management responsibilities, funding obligations, and dispute resolution mechanisms. The agreement details payment structures linked to milestone completions, while emphasizing the importance of reporting requirements, intellectual property rights, and data rights. It mandates that Performers disclose inventions and submit periodic reports to the government. Terms also specify how the government may access and utilize developed intellectual property and data. Security provisions and compliance with Federal laws are stressed, along with restrictions on international transfers of intellectual property to protect national interests. The document serves as a comprehensive framework for effective collaboration in federally funded health research initiatives, ensuring accountability and clarity in the roles and responsibilities of all parties involved.

The Administrative and National Policy Requirements document outlines essential compliance requirements for proposals submitted to ARPA-H as part of government RFPs. It details formatting stipulations, including acceptable formats, page layout, and page limits. Key sections include Team Member Identification, which necessitates listing all team members and their affiliations, highlighting any non-U.S. entities. Organizational Conflict of Interest (OCI) disclosures are required, asking proposers to affirm whether team members have past or current engagements with ARPA-H. The document also outlines parameters for research security, intellectual property assertions, and human and animal subjects research. Proposers must declare any use of patented inventions and their IP restrictions, while ensuring adherence to cybersecurity standards and addressing previous financial or legal liabilities. Each section provides a format for required disclosures, ensuring accountability and integrity in the submission process. Central to the document's purpose is the emphasis on transparency, compliance, and proper handling of sensitive information, aligning with federal mandates for research programs. This structured approach helps maintain national security during government-funded research initiatives.

The ARPA-H PRECISE-AI Program Solicitation outlines a framework for submitting proposals related to advanced AI applications in healthcare. The document details the structure of task descriptions to be provided by applicants, including the outline of specific objectives, approaches for task execution, and identification of responsible organizations. Each task is to be broken down into subtasks, encompassing the needs for potential human or animal research where applicable. Clear deliverables, associated intellectual property rights, and measurable milestones are crucial components of the proposals. The overall goal is to foster innovative AI solutions that advance healthcare outcomes, with defined steps for evaluation and tracking progress throughout the program phases. This solicitation serves to engage stakeholders in developing impactful healthcare AI initiatives, emphasizing collaboration and thorough documentation.

The ARPA-H PRECISE-AI Program Solicitation (ARPA-H-SOL-25-113) outlines the requirements for submitting proposals aimed at advancing artificial intelligence technologies in health. Proposers must adhere to specific formatting and content guidelines, ensuring submissions are concise and relevant to the program's evaluation criteria. The document mandates a structured proposal composed of sections such as the Proposal Summary, Goals and Impact, Technical Plan, and Capabilities/Management Plan, with strict page limits. The proposal should clearly describe the project's objectives, existing limitations, innovative methodologies, technical challenges, and potential impacts if successful. A section for an Innovative Claims Table is also included to link technical goals with proposed innovations. The Technical Plan must demonstrate a feasible, milestone-driven approach to project execution, while the Capabilities/Management Plan should highlight the team's expertise and organization. Overall, this solicitation emphasizes innovation, measurable outcomes, and collaboration among diverse organizations, aiming to solve significant health challenges through advanced AI solutions.

The ARPA-H Cost Proposal Spreadsheet serves as a structured template for proposing costs related to the ARPA-H solicitation (Solicitation No. ARPA-H-SOL-25-113). It is organized by various technical areas and is segmented into multiple phases: I, II, and III, with detailed breakdowns for direct labor costs, subcontractor costs, materials, equipment, travel expenses, and other direct costs, alongside indirect costs and profit margins. Key sections include the cost proposal for each phase, which outlines hours worked, rates, and total expenses over specific timeframes, as well as requirements for providing a cost share. The proposal encourages clarity in itemizing each cost component, including a subsection for subcontractor and equipment cost details. Additional details include a description of materials and travel plans, detailing the purpose and locations, ensuring comprehensive budgeting for all project aspects. This document's main purpose is to facilitate the effective submission of financial proposals in alignment with government grants and RFPs, ensuring that all potential expenses are captured and presented clearly for evaluation. The structure is designed to support transparency and enable the government to assess bid proposals efficiently, reflecting compliance with federal funding criteria.

This document outlines an Other Transaction Agreement (OTA) between the Advanced Research Projects Agency for Health (ARPA-H) and a performer aimed at researching AI's performance and usability for healthcare applications. It details the contractual framework, including the agreement's scope, term, management processes, payment structures, and the intellectual property rights associated with the developed technology. Key sections include definitions of terms, a comprehensive management plan, and specific obligations related to research milestones. The document emphasizes continuous government involvement, requiring the performer to submit regular reports and adhere to guidelines for financial accountability. Intellectual property developed under the agreement is owned by the performer but grants the government certain rights for its use. The agreement also includes provisions for dispute resolution, compliance with federal regulations concerning telecommunications and surveillance services, and stipulations regarding data rights and foreign access to technology. The structure aims to ensure effective collaboration, accountability, and the successful commercialization of innovative healthcare technologies, while safeguarding government interests in the research and development process.

The ARPA-H PRECISE-AI document outlines essential administrative and national policy requirements for proposal submissions associated with solicitation number ARPA-H-SOL-25-113. The document emphasizes specific formatting and submission guidelines, mandating that the Administrative and National Policy Requirements be completed fully and included in the volume 1 proposal. Key sections focus on team member identification, organizational conflict of interest disclosures, research security, and potential foreign participation. It details requirements regarding intellectual property claims, human subjects and animal research approval, and representations concerning unpaid debt or felonies. Applicants must also outline their management plans for Controlled Unclassified Information (CUI) and Controlled Technical Information (CTI). The document serves as a comprehensive checklist for entities seeking federal grants, ensuring transparency and compliance with national security protocols. The guidelines aim to mitigate conflicts of interest and secure integrity in research funded by the government.

The ARPA-H-SOL-25-113 document outlines the requirements for submitting a Solution Summary to the ARPA-H PRECISE-AI solicitation. It emphasizes the necessity of a preliminary submission prior to a full proposal, with specific formatting and length guidelines: a maximum of three pages for a single technical area (TA) submission and six pages for multiple TAs. The Solution Summary must adhere to a structured outline, comprising a summary of the concept, the innovation and impact of the proposed approach, a description of the proposed work including deliverables and milestones, and an overview of team organization and capabilities. Each section should detail how the proposed solutions address technical challenges, include quantitative metrics for comparison with existing technologies, and evaluate the technical risks involved. Additionally, a Basis of Estimate (BOE) is required, outlining the federal funds requested and a comprehensive cost breakdown. This submission serves to evaluate the potential effectiveness and resource needs of proposed technological innovations in the ARPA-H PRECISE-AI program, ensuring clarity and thoroughness in the proposals submitted for consideration.

The Advanced Research Projects Agency for Health (ARPA-H) has issued a DRAFT Program Solicitation titled Performance and Reliability Evaluation for Continuous Modifications and Usability of AI (PRECISE-AI). The program seeks to develop self-correction techniques for AI decision support tools (AI-DSTs) in healthcare to ensure ongoing efficacy and safety, as current methods largely depend on pre-market evaluations. The solicitation highlights the need for continuous AI monitoring and adaptability to operational changes, emphasizing the significance of automated ground truth extraction, performance degradation detection, root cause analysis, and effective communication with clinicians. PRECISE-AI will comprise five technical areas focusing on automated label extraction, degradation detection and correction, uncertainty quantification, core data infrastructure, and independent validation. It aims to create an open-source repository of monitoring tools, enhancing AI tool interpretability and clinical outcomes through real-world testing. Selected proposals will address specific use cases within priority clinical tracks, with a robust framework for data sharing and collaboration across diverse healthcare systems. The anticipated outcomes include improved AI tool performance, enhanced clinical decision-making, and risk reduction for patient care. The solicitation is aimed at fostering innovative approaches that ensure AI tools are effective, trustworthy, and transparently integrated into clinical settings.

The Advanced Research Projects Agency for Health (ARPA-H) has released a Draft Innovative Solutions Opening (ISO) titled "Performance and Reliability Evaluation for Continuous modifications and Usability of AI" (PRECISE-AI). This initiative aims to address the challenges related to the ongoing safety and efficacy of AI technologies in healthcare, particularly in AI Decision Support Tools (AI-DSTs). The program seeks proposals to develop self-correction techniques that can sustain optimal performance of AI models in diverse clinical settings post-deployment. Key areas of focus include automated extraction of surrogate ground truth labels, continuous monitoring for performance degradation, root cause analysis, and enhanced communication with clinicians. Multiple awards are anticipated under this program, structured in three phases over four years, culminating in tools that could either transition to commercial use or obtain FDA clearance. The document details eligibility requirements, technical areas, evaluation processes, and necessary proposal guidelines, anticipating a due date for submissions on January 15, 2025. Overall, PRECISE-AI aims to ensure that AI technologies continuously improve and maintain effectiveness in real-world healthcare environments, addressing a critical need as AI integration in medical devices expands.

The Advanced Research Projects Agency for Health (ARPA-H) has launched the Innovative Solutions Opening (ISO) for the Performance and Reliability Evaluation for Continuous modifications and Usability of AI (PRECISE-AI). This initiative addresses the lack of ongoing safety and efficacy monitoring for artificial intelligence (AI) systems in healthcare, particularly as their deployment has surged, with over 850 FDA-approved medical devices now utilizing AI. The PRECISE-AI program aims to implement self-correction techniques that ensure peak performance of AI Decision Support Tools (AI-DSTs) in dynamic clinical environments, enhancing clinician decision-making through robust continuous monitoring, degradation detection, root cause analysis, and seamless communication. Key objectives include the automated extraction of ground truth labels, detection of performance degradation, and self-correction capabilities. The program will unfold in three phases over four years, encouraging collaboration across multiple clinical settings to validate advancements. Success depends on developing novel technologies for real-world applications, thereby guaranteeing the reliability of AI outputs and improving patient outcomes. This ISO anticipates multiple individual awards under specific legal frameworks, emphasizing innovation and practical applicability in the evolving landscape of healthcare AI technology.

The PRECISE-AI Program, led by ARPA-H, is designed to enhance the performance and reliability of AI-enabled medical devices. The agenda for the Proposers Day details a series of discussions and presentations, including insights from notable experts on AI's applications in abdominal radiology and the FDA's regulatory approach. The increasing reliance on clinical decision support systems highlights a critical need for continuous monitoring and updating of AI models, which often degrade over time due to shifts in clinical environments. The PRECISE-AI initiative aims to develop tools for automatic detection and correction of model performance issues by utilizing a robust core data infrastructure. Key components include extracting surrogate ground truth labels for ongoing assessment and implementing automated self-correction mechanisms. The program emphasizes bi-directional communication between AI systems and clinicians, fostering trust through transparency regarding data integrity and model uncertainty. A structured timeline outlines milestones for program deliverables and methodologies for independent verification and validation. Proposals for participation are due by January 2025, stressing the importance of meeting specific guidelines to advance this innovative approach to managing AI in healthcare effectively.