Trisha Pillay speaks with Adriaan Kruger, CEO of nuvoteQ, as they unpack why clinical research is still heavily reliant on paper-based systems in many regions.
Across many parts of Africa, clinical research still depends heavily on paper-based workflows. For pharmaceutical companies managing global trial portfolios, this can create operational challenges around data quality, monitoring, and regulatory readiness, particularly when studies contribute to submissions in the US and Europe.
Adriaan Kruger, founder and CEO of nuvoteQhas spent twelve years building the infrastructure to close that gap. His conversation with Trisha Pillay on Digital Pulse is one of the more candid accounts available of what digital adoption in clinical research actually looks like when the constraints are real.
Why Paper Persists and What It Actually Costs
The persistence of paper in LMIC clinical research settings is not a technology problem. The technology exists.
"Our industry is so hesitant and so resistant to change," he says. "They are so risk-averse — which we totally get in this highly regulated world. These researchers are so worried about potentially using a system and then the data gets lost, or the system is down. So they go back to their tried and tested way of doing things, which is on paper."
The financial dimension compounds the risk-aversion. Funding does not flow to research sites in sufficient volumes to support digital infrastructure investment. The result is double data entry, a risk mitigation practice where patient data recorded on paper is manually typed into a centralised system twice by different operators, then compared for discrepancies. In developed markets, this practice has largely been eliminated. Across much of Africa, it remains the norm.
The downstream cost is significant as data science teams spend extensive time converting inconsistent paper records, Excel files, and incorrectly formatted entries into globally standardised formats before a single submission can be filed.
Real-Time Visibility Changes the Risk Calculation
The operational case for digital infrastructure is sharpest when Kruger describes what real-time data visibility actually enables at the trial level. Clinical trials running across multiple countries like South Africa, Mozambique, Ghana, Finland, and Australia simultaneously have historically operated with delayed information flows. A serious adverse event occurring overnight in South America might take days to trigger a coordinated global response. The pharmaceutical company, the investigators, and the data safety monitoring board are all operating on different information timelines.
"If they don't have real-time data, often there's a delayed reaction on how you deal with things," Kruger says. "Now if they have a real-time view of everything happening globally, they can make insightful decisions, let's pivot, let's change the dosage, or there was a serious adverse event, it happened last night in South America. The morning we wake up, everyone knows."
For pharma executives managing trial costs, trials are expensive precisely because they run long, across many sites, with significant overhead. The ability to make earlier decisions about dosage adjustment, site performance, or trial termination is a direct cost lever. "You can make decisions on whether to move faster, change direction, or potentially stop a study so that you don't spend more money on it."
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AI Where It Works in Clinical Research
Kruger's position on AI in clinical research is one of the more technically grounded takes in the current conversation. nuvoteQis not AI-averse, but the firm is precise about where AI delivers and where the industry's enthusiasm is running ahead of its readiness.
The clearest proof point is a regulatory review tool built for South Africa's medicines regulator, SAHPRA, in partnership with a Seattle-based philanthropic funder. The challenge was a generic drug dossier, submissions that can run to 15,000 pages, were sitting in regulatory queues for up to nine years across Africa, delaying the availability of affordable medicines for the patients who need them most.
The tech company deployed an open-source LLM locally within SAHPRA's data centre, with no external internet access, trained to analyse dossiers and produce a two-page risk summary with hyperlinked references to the source document. "That has reduced the timeline to review from where it typically takes five to six weeks. We can do it in about 45 minutes now."
The model works because the data never leaves a closed environment, the task is well-defined and repetitive, and human reviewers remain in the loop for final decisions. That last point is deliberate. "You will always have a human in the loop. There will always be a healthcare professional. AI will help do some of the number crunching, but ultimately, when it comes to patient care, the ethical component is how patients are being treated. I don't think AI is going to be there for a long time."
The liability question Kruger raises for clinical AI tools mirrors what is emerging elsewhere in regulated industries: the responsibility for an AI-assisted decision sits with the clinician or researcher who acted on it, not the software provider.
Africa as a Strategic Asset
Kruger closes with a reframe that deserves attention from anyone structuring a global trial portfolio. South Africa's clinical research infrastructure, built over decades around institutions like the University of the Free State in Bloemfontein, is world-class, not despite its context but in part because of it.
"Because of our diverse population just in our country, we are world leaders when it comes to clinical research. During the COVID pandemic, the fact that we discovered some of those strains that's not by chance. It's because we are world-class."
Africa's genetic diversity is, he argues, an asset that the global pharmaceutical industry has consistently undervalued. As precision medicine and genomic-driven treatment personalisation move from oncology into broader therapeutic areas, that diversity becomes a competitive advantage for trial design and drug development that no other region can replicate.
The infrastructure to unlock it is digital, connected, and validated to FDA and EMA standards, which is what Kruger is building. The industry's willingness to fund and support it is what will determine how quickly African patients stop waiting.
Learn more about nuvoteQand connect with Adriaan Kruger on LinkedIn.
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Chapters
00:00 Transforming Clinical Research: The Digital Shift
03:01 Barriers to Digital Adoption in Pharma
08:13 Data Accuracy and Double Data Entry Risks
11:07 The Role of AI in Clinical Research
19:21 Real-Time Data Visibility in Trials
23:44 Scaling Tech Solutions in Africa
28:36 The Future of Clinical Research: A Vision for 5 Years
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Trisha Pillay is an award-winning journalist, Editor-in-Chief, and Head of Content with 14 years of experience across media, editorial leadership, and storytelling. She is a podcast host and content strategist specialising in healthcare, pharmaceuticals, and emerging technology, where she moderates across all the Pharmatica podcast series, including Clinical Compass, Digital Pulse, Chain Reaction, and The Discovery Loop. She loves speaking with global leaders across pharma, biotech, medtech, and HealthTech.
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