Trustworthy data science and good clinical practice.

Good clinical practice requires responsible conduct and considerations of safety and ethics.

Good clinical practice demands both responsible conduct and a focus on safety and ethics. At Abzu, we proactively help customers elevate the success rates of their clinical trials through data science. We routinely optimize inclusion/exclusion criteria, delve into why patients react to treatments, and pinpoint safe, easily accessible biomarkers for tracking responses or remissions.

Responsible data science for clinical studies.

Good clinical practice is essential for data science that has an impact on human lives.

Data science must be responsible, especially when impacting human lives, making good clinical practice a necessity. This becomes particularly important for maintaining the safety and confidentiality of participants in clinical studies while ensuring statistically valid analyses.

Our QLattice® is purpose-built to satisfy the quality demands of conscientious scientists in high-stakes fields. The technology we’ve developed aims for reproducible and interpretable outcomes, fitting the needs of regulated industries. We take pride in contributing to scientific discovery as part of Forskermaskinen and gaining approval from the UK Biobank.

Our expert team covers the pharmaceutical value chain, providing meticulous statistical and biological analyses along with unwavering scientific support. We offer an extensive range of services, from disease understanding to drug discovery, spanning pre-clinical to clinical stages. This approach leads to a comprehensive understanding of how to bring better, safer drugs to market, adhering to safety and ethical guidelines throughout.

Key aspects of good clinical practice.

When tackling any clinical data analysis project, we scrutinize it through the lens of Good Clinical Practice (GCP) guidelines.

Data management.

We ensure that clinical data remains on the designated machine for the analysis. You have the option to conduct the analyses yourself or enlist our support, always meeting regulatory requirements.

We offer various options to meet your specific needs:

  • Your scientists’ computers or our secure ones.
  • Dedicated machines at our offices or in our ISO-27001 certified, GDPR-compliant server cluster in Germany.
  • A GxP-validated machine you provide, located at our office.
  • A computer at your location with either physical or secure remote VPN access for specified team members

In essence, you dictate the access and confidentiality level for your data.

Participant confidentiality.

Should we discover information that could identify individuals, we strictly adhere to GCP guidelines and report any breaches. We also possess the capabilities to anonymize data securely.

Data quality assurance.

Clinicians and patients can easily interpret the outcomes of our QLattice models. These models have received high trustworthiness ratings from external assessors, including disease experts and key opinion leaders. They yield reproducible, transparent, and highly interpretable results, assisting in defining inclusion/exclusion criteria for clinical trials’ statistical analysis plans.

We also adhere to CHP ICH E9 + E9(R1) (Statistical Principles for Clinical Trials). Every clinical data project includes at least one GCP-certified team member and oversight by one of our data protection officers.

If you require a custom solution, feel free to contact us.

Share some perspective.

Beyond the algorithm: The human impact of AI.

Abzu's perspective on accelerating R&D with explainable AI.

We ditched the traditional swag option for a more personal and green approach: We encouraged Abzoids to bring their preferred textile – preferably pre-loved – to screen-print our logo on.
Explainable AI has huge potential to accelerate disease understanding and drug design by revealing the biological mechanisms that drive drug activity, stability, safety, and delivery.
In the life sciences sector, many AI applications fall under the high-risk category.

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