Procurement Summary
Country: Canada
Summary: Development of a Risk of Bias Tool for Population-Adjusted Indirect Comparisons
Deadline: 22 Jul 2026
Posting Date: 30 Jun 2026
Other Information
Notice Type: Tender
TOT Ref.No.: 144241374
Document Ref. No.: C-262701520
Competition: ICB
Financier: Self Financed
Purchaser Ownership: Public
Tender Value: Refer Document
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Indirect treatment comparisons (ITCs) play a critical role in informing decision-making within health technology assessments (HTAs), particularly when direct head-to-head evidence is unavailable. Drug sponsors commonly submit a range of ITC methodologies, including network meta-analyses (NMAs) and population-adjusted indirect comparisons (PAICs). PAIC methods such as matching-adjusted indirect comparisons (MAICs), simulated treatment comparisons (STCs), and multilevel network meta-regression (ML-NMR) are increasingly used to compare new therapies with relevant comparators.However, their validity depends on methodological choices, data availability, and assumptions that can introduce substantial bias and uncertainty. CDA-AMC seeks to engage an external vendor with expertise in evidence synthesis, indirect treatment comparisons, and methodological tool development to design a comprehensive, practical, and reproducible Risk of Bias Tool for PAICs. For more information, see the RFP Main Document.
Solicitation Type : RFP - Request for Proposal (Formal) Reference Number : 0000325932 Location : Canada, All of Canada, All of Canada Delivery Point : [email protected] Description : Indirect treatment comparisons (ITCs) play a critical role in informing decision-making within health technology assessments (HTAs), particularly when direct head-to-head evidence is unavailable. Drug sponsors commonly submit a range of ITC methodologies, including network meta-analyses (NMAs) and population-adjusted indirect comparisons (PAICs). PAIC methods such as matching-adjusted indirect comparisons (MAICs), simulated treatment comparisons (STCs), and multilevel network meta-regression (ML-NMR) are increasingly used to compare new therapies with relevant comparators.However, their validity depends on methodological choices, data availability, and assumptions that can introduce substantial bias and uncertainty. CDA-AMC seeks to engage an external vendor with expertise in evidence synthesis, indirect treatment comparisons, and methodological tool development to design a comprehensive, practical, and reproducible Risk of Bias Tool for PAICs. For more information, see the RFP Main Document.
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