Clinical development runs on knowledge — protocols, regulatory requirements, data standards, device specifications, and decades of institutional expertise distributed across organizations, systems, and jurisdictions. When that knowledge is inconsistent, incomplete, or impossible to trace, the consequences are measurable.
Clinical trial protocol deviations are rarely caused by a single mistake. More often, they emerge when definitions, protocols, systems, and regulatory requirements drift out of alignment over time. The resulting inconsistencies are difficult to detect, costly to correct, and often discovered only after work has already been completed.
Reasonics helps prevent that drift by providing a formal knowledge foundation that keeps organizational expertise consistent, traceable, and executable across the systems that depend on it, without replacing validated systems or requiring costly re-engineering.
No organization in clinical development carries a heavier consistency burden than a CRO.
At any given time, a CRO is managing multiple sponsors, therapeutic areas, trial phases, and regulatory jurisdictions, each with its own data standards, protocol requirements, and compliance expectations. The same data element gets defined differently across systems. The same regulatory requirement gets interpreted differently across sites. The same protocol term means something slightly different depending on which sponsor's conventions are in play.
The cost of that inconsistency isn't abstract. It shows up as protocol deviations, delayed submissions, audit findings, and re-engineering cycles that consume resources every time a regulation updates or a protocol changes.
Reasonics gives CROs a formal knowledge foundation that makes consistency a structural property of their systems and not an ongoing operational burden. Clinical data ontologies — built on BFO 2020 / ISO/IEC 21838-2, the international standard for formal ontological foundations — ensure that a term defined at the protocol level means the same thing at every trial site, in every sponsor's data environment, and in every regulatory submission that depends on it. When knowledge changes, a protocol is amended, a regulatory requirement updates, the system propagates those changes automatically, no manual re-engineering.
The compliance officer who needs submission-ready data coherence, the VP Clinical who needs protocol deviations to stop accumulating, and the regulatory affairs team that needs to show its work in an audit — Reasonics is built for the CRO problems they carry every day.
One definition, held identical across every stage, organization, and jurisdiction in the chain.
Imagine a clinical development chain in which a term defined at the protocol level means exactly the same thing at every trial site, across every sponsor's data environment, and in every regulatory jurisdiction simultaneously. Where device-generated data, from wearables, implantables and diagnostic equipment, maps directly to the sponsor's data standards without manual reconciliation. Where a regulatory requirement changes, it propagates automatically across every system that depends on it. Where the CRO, the sponsor, the device manufacturer, and the regulatory submission are all reasoning from the same formally defined knowledge.
This is the problem that Reasonics was built to solve and what our formal knowledge foundation makes possible.
Without that foundation, each handoff in the chain is a point where meaning can drift. A data element that means one thing at the CRO means something slightly different at the sponsor. A device data standard that doesn't align with the trial's data model introduces inconsistencies that surface later, in a protocol deviation, a submission query, or an audit finding. The $1.3 billion annual cost of protocol violations is what that drift looks like at scale.
Reasonics closes that gap across every organization, system, and jurisdiction in the chain, without replacing the validated CRO systems already in place.
Each one a CRO problem that stops compounding. Expand any to see what changes.
Protocol deviations don't begin at the site. They begin when the same concept means something different in different systems. Reasonics establishes a formally defined knowledge layer across every trial site, sponsor data environment, and jurisdiction simultaneously, so CROs catch inconsistencies at the knowledge level before they become deviations in the record.
When regulations change or protocols are updated, organizations using conventional systems face an expensive, time-consuming, and error-prone engineering cycle. Reasonics separates formal knowledge from the code it governs. When requirements change, the knowledge layer updates, and the software regenerates automatically. CRO systems reflect the current regulatory state without manual intervention.
Regulators and auditors don't just need a correct-looking output. They need a traceable chain of reasoning from formal knowledge to conclusion. Reasonics derives conclusions from explicitly defined rules and formally verified logic, built on BFO 2020 / ISO/IEC 21838-2 and OBO Foundry biomedical ontologies. The reasoning is as auditable as the result. For CRO regulatory submissions and audit responses, that distinction is not minor.
Medical devices — wearables, implantables, diagnostic equipment — generate data that becomes clinical evidence. When device data standards don't align with the trial's data model or the sponsor's submission requirements, the misalignment becomes manual reconciliation work, inconsistencies in the trial record, and submission queries. Reasonics maps device-generated data correctly to the trial record and the regulatory framework governing the submission — consistently, without manual intervention, and in time to accelerate FDA / EMA review for CROs.
EDC platforms, CTMS, regulatory submission tools. These don't get replaced. They get a coherent knowledge foundation along with a self-checking reasoning system. Reasonics operates as a foundational layer alongside current infrastructure, without triggering revalidation or re-engineering of the systems already in place for CROs.
Bring us a single definition, an endpoint, an inclusion criterion, an adverse-event rule. That your protocol, EDC, and submission systems each hold differently. We will walk through what it takes to define it once and have every downstream system inherit it, alongside the validated systems you already run.
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