Protocol issues, enrolment issues,
and skewed trial results go undetected without timely access to clinical trial data.
the problems we solve
01
manual processing
the vast majority of clinical trial data is processed manually
02
realtime data unavailable
few researchers and data managers have access to realtime clinical trial data
03
regulatory compliance
inaccurate or incomplete data poses a major risk to trial outcomes and complicates regulatory compliance
04
workflow
trial activity is complex, spans both expert disciplines and lay populations; however, major stakeholders are not connected in any meaningful way
05
existing tools
project stakeholders contend with tools designed for another era, before mobile computing and ubiquitous connectivity
06
rising cost
massive inefficiencies encoded in the current paradigm contribute to costs that double every 3 years
Certainty resolves the enormous challenges facing the contemporary medical research community
and the donors who fund them.
This is reflected in our approach to
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patient enrolments
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data sharing and personal privacy
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trial methodology
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rising costs
In so doing, we are solving multiple underlying problems (detailed below) in data management, team communication, and project workflow.
manual data processing
As presently constructed, the clinical trials process presents several operational challenges from a data management perspective.
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Manual intervention is required to aggregate, clean, and transform trial data for
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completeness
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quality
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cleaning, and
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resolving inconsistencies
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realtime data unavailable
Clinical trials generate troves of data internally (via the research team, patients, et al) and through external sources (laboratories, suppliers, clinicians, et al). But almost none of the data is available to the project team, the sponsor or principle investigator in realtime. Depending on the source, access to trial data can range from a few days to a few months.
The absence of realtime data accounts for the systemic latency in all trials. Latency compounds the impact of routine protocol issues and complicates error correction, often skewing trial outcomes and contributing to costly delays.
regulatory compliance
Data governance now presents the most critical challenge in meeting regulatory compliance. Manual processing and systemic latency means research teams devote costly resources to data cleaning rather than analysis.
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As the volume of data increases, confidence in its quality and completeness declines. According to a recent survey of trial professionals, the top 3 issues are:
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inconsistent / duplicate data
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traceability
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access to realtime data
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workflow
(click on the image above to enlarge)
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The clinical trial lifecycle is a complex workflow involving domain experts from many disciplines, government regulators, as well as a lay population (the patients).
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Trials are managed by a principal investigator (or PI) who is ultimately responsible for all deliverables and contractual relationships. Since centralised data repositories and automated messaging facilities are applied ad hoc if at all, the PI must often design project workflow from scratch.
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existing tools
(click on the image above to enlarge)
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From executing basic contracts and budgets to exchanging data among stratified team members, project stakeholders work with tools from another era.
rising cost
The cost of conducting a clinical trial rises every year, in part because (1) administration is expensive; (2) trial delays lead to (3) patient withdrawals; (4) privacy laws and (5) regulatory compliance impose new costs.
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Certainty helps contain the rising cost of clinical trials.
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