A South African-developed artificial intelligence (AI) platform designed to help researchers prepare clinical trial databases faster has placed second in the 2026 CDISC AI Innovation Challenge, earning international recognition for African-developed technology to address a key bottleneck in clinical research worldwide.
Created by Johannesburg-based clinical data management organisation BioInformatiCo, the platform called “Leova” automates aspects of building and testing the digital databases used to collect information during trials of new medicines and vaccines. By reducing the time and manual effort required to prepare these systems, the platform aims to help research teams identify database errors and protocol inconsistencies earlier and devote more resources to the research itself.
For Shirley Collie, Founder and CEO of BioInformatiCo, the global recognition is an important milestone for the company and a demonstration of how African-developed technology can contribute to clinical research globally:
“Placing second in the CDISC AI Innovation Challenge is an important endorsement of what we have built. It shows that technology developed in Africa can help tackle challenges in clinical research worldwide, while supporting the continent’s ability to generate evidence that reflects the health needs of its own populations,” says Collie.
BioInformatiCo developed Leova within its existing clinical research operations, drawing on the practical demands of building reliable databases for clinical trials. The company currently supports first-in-human to Phase 3 vaccine research for infectious diseases, including HIV, TB, Ebola and COVID-19.
The global recognition from CDISC also comes at a time when US funding cuts have disrupted health programmes and medical research in South Africa, adding pressure to an already stretched research ecosystem. HIV programmes, clinical studies and research infrastructure have especially been affected,
while universities and research organisations face funding shortfalls and uncertainty over grants. In this environment, automating time-consuming manual work, such as building and testing a study database, can cut both hours and costs, helping limited resources go further. That is what Leova is designed to do.
“Before a new medicine or vaccine can reach patients, clinical trials must establish whether it is safe and effective. But before the first participant can enrol, researchers need reliable systems to collect and manage the study data. Building and validating these databases can take 10 to 20 weeks of specialist work, with each system tailored to the trial’s specific research protocol. Errors at this stage can compromise data quality, create costly rework and delay the trial,” adds Collie.
Built to support clinical data management capacity on the African continent, Leova brings much of this preparation into a single workflow. Using a study protocol, the platform drafts data collection forms and validation rules, builds the database and then tests it using simulated participants deliberately designed to break those rules.
This allows research teams to identify weaknesses before the system is used in a live trial.
“Leova was born out of a real operational need. We understand the pressure clinical research teams face to deliver reliable data, meet demanding standards and make every Rand count. While automation cannot replace sustainable funding or specialist expertise, it can help research teams work more efficiently while maintaining the quality and reliability of clinical data,” adds Collie.
Standards Consortium (CDISC), a global non-profit organisation that develops standards for clinical research data. These standards help ensure that data can be collected, exchanged and submitted consistently, including for regulatory review by the US Food and Drug Administration (FDA).
The challenge attracted 50 competitive submissions from 30 organisations and individual entrants, placing African-developed technology alongside several leading global innovators. Leova placed second among 19 entries in Use Case 1, which focused on using AI-generated synthetic data to automate software testing, demonstrating the potential for African innovation to compete on an international stage.
