We're a small, Spain-registered data management consulting company.
We choose to be self-funded with no outside capital. This financial independence allows us to choose the kind of projects we work on.
Our team of experts crafts bespoke solutions to data management challenges faced by Life Sciences organizations.
We offer our clients a single point of accountability, with rapid decision‑making.
And our founder acts as each clients' dedicated success manager.
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We're a 100% remote company and we put family first. The quality of life of our team members is crucial to the success of the company.
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This paper presents a Python-based platform that generates Synthetic CDISC Clinical Trial Data at scale. The platform programmatically generates realistic synthetic persons (SynthPerson) that have a complete synthetic Personal Health Record (SynthPHR). Each SynthPerson lives in a series of geographically-accurate synthetic cities (SynthCity). Groups of SynthPerson are then randomly enrolled in a synthetic Clinical Trial (SynthTrial). Platform users define the parameters of each synthetic clinical trial and the platform generates all CDISC SDTM domains for the desired number of subjects.
Human BioGeography: predicting clinical trials outcome using a 3D human body simulation and a GIS framework
Diego Caso, TrialTwin and Rocio Matesanz, PhD Student
Due to the limited success rate in clinical trials, with less than 20% of drug candidates progressing through all phases for marketing approval, novel innovative approaches remain essential to improve these statistics. This paper proposes a novel system combining relevant databases from different Open Data sources with a Geographic Information System (GIS) that will contribute to confront this challenge. By integrating information from several biorepositories, including previous reports of drug development processes, into a 3D simulation of the human body our system aims to identify determinants restricting clinical trial success. We call this "Human BioGeography" and is based on a hierarchy of anatomy => disease => therapeutic target => drug => chemical structure. This approach provides crucial insights for drug developers, offering data on aspects that influence drug approval rates, such as potential adverse events and drug viability and metabolism. This system is expected to improve both trial design and development processes, revolutionizing the clinical trial landscape.
Sergio Alegria
Increasing Business Impact of Connected Standards with a Metadata-Driven Platform
Regulatory agencies require sponsors of drugs, devices, and veterinary products to comply with specific standards and terminologies for all submissions. There are multiple Standards Organizations that develop and curate multiple data standards. Standards are available in many sources and formats, creating a complex ecosystem in the communications between Regulatory Agencies, Standards Organization, sponsors and CROs. While standards are a central piece in an organization’s operations, the management of said standards is a complex task that impacts the process of bringing a new product to the market. TrialTwin’s Data Standards Governor is a system that allows organizations to manage their own standards and terminologies, having a baseline of pre-loaded standards and terminologies from Standards Organizations (CDISC, LOINC, ..). The system provides organizations with tools to define connectivity between standards and terminologies to enhance metadata usability throughout the organization.
Please contact us if your organization has a data management challenge you need assistance with.
