Peer AI Expands Submission Risk Prediction with Live Agency Monitoring
Traditional prediction engines learn from historical filings and past agency decisions. But regulatory priorities change. New guidance can resolve questions that were once open, agency focus can shift, and emerging modalities may have little or no filing history to draw on. Peer AI's Anticipate capabilities now combine historical precedent with intelligence on what regulatory agencies are working on in the present, giving submission teams a more current view of the issues most likely to matter during review.
That changes three things for a submission team. 1. Predictions can rise and fall with changes in agency focus, and be retired when new guidance has settled the question. 2. Every prediction is linked to a citable current source, allowing regulatory teams to verify the evidence behind it rather than take the prediction on trust. 3. For novel modalities, where historical precedent may be limited, current regulatory activity can provide a signal where filing history cannot.
Peer AI's agentic platform now monitors more than 150 authoritative sources across six regulatory regions, covering FDA, EMA, MHRA, Health Canada, TGA and PMDA, alongside sources such as the Federal Register, ClinicalTrials.gov and FAERS. Every signal links back to its original source. Sources can be turned on, turned off, and weighted based on the context of use. By continuously monitoring a defined set of authoritative sources and retaining each signal with its source, Anticipate turns regulatory monitoring into a traceable body of evidence. The goal is not simply to produce an answer, but to show the evidence behind it.
Peer AI today also announced the appointment of
"In regulatory strategy, the challenge isn't aligning with health authorities on innovative science. It's the midnight stress of assembling evidence, predicting agency questions, and defending your submission against a hard deadline. This high-stakes, data-heavy orchestration is tailor-made for the capabilities of agentic AI," said Christian.
"For most of my career I have been on the buying side of R&D, deciding which external partners justify the investment. Peer AI is targeting a specific and measurable cost inside the submission process rather than selling a general-purpose tool, and that is a meaningful difference. It brings enhanced value and speed to the table in a way other solutions are not meeting," said Burfoot.
"Regulatory judgment is the hardest thing to build into software, because most of it was never written down. Monitoring and weighting keep our predictions tied to what agencies are working on this week, not what they published three years ago. Mary and Mark bring what monitoring cannot: one built her career owning submissions inside biopharma, the other spent his deciding which technology a large sponsor should buy," said
About Peer AI
Peer AI is the AI regulatory submission engine for life sciences. The platform authors, orchestrates, and anticipates the full regulatory dossier, so biopharma teams can compress submission timelines without trading quality. Peer AI is in use at top 20 pharma, biotechnology, and CRO organizations, and has automated more than 15,000 pages of regulatory content and returned more than 20,000 medical writing hours to customer teams. Learn more at getpeer.ai.
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SOURCE Peer TechBio Inc.
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