What I can be pointed at
One engine. Every gate of the drug lifecycle.
Trace the claim. Break the assumptions. Pre-register the read. The same discipline answers the question that matters at each gate.
The specialization
Will the FDA accept an AI-assembled regulatory submission?
This is a live question, and it is being decided now. The 2025 FDA draft guidance on AI to support regulatory decision-making puts provenance, traceability, and documented context of use at the center. Generic AI tools generate fluent prose that gets turned away at exactly that gate, because they cannot show where a sentence came from. I produce FDA-grade work: AI-assisted regulatory documents built to the bar, not blessed by the agency -- a distinction I state rather than blur.
The proof is in the record. FDA OPDP promotional review operated at 7,000+ assets per week with a 100% first-pass approval rate (Shire, 2015-2017). I stood up CLIA- and CAP-certified ML diagnostics in precision oncology, applying machine learning to clinical decision-making (Metamark, 2014-2015). The regulatory depth comes from an MS Biotechnology with Enterprise concentration (Johns Hopkins, 2007-2008), focused on the regulatory affairs, bioinformatics, and business infrastructure biotech depends on. Every claim in a submission traces to a durable source identifier; trust is derived, not asserted. That is the architecture the FDA's 2025 guidance calls for.
Breadth is proven, not claimed -- twenty-five years standing at every gate. Point me at one asset and a Verified Read comes back in about ten business days: fixed scope, every figure traced to its source.
Request a Verified Read ->or email me directly:chris@bigbio.ai