ReviewClinical pharmacology and therapeutics2026
Digital Transformation of Medicines Regulation in Africa-Perspectives from a Stakeholder Convening.
Review in Clinical pharmacology and therapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- The Governance Gap: Democratizing Drug Development Through Decision Architecture.Clinical pharmacology and therapeutics · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Regulatory authorities worldwide are developing strategies to integrate artificial intelligence (AI) into the lifecycle of health products, technologies, and medicines. While regulators share goals of improving efficiency, strengthening decision-making, and protecting public health, their approaches differ according to institutional structures, capacity, maturity, and regional priorities. In the United States, the FDA adopts a model-focused approach, treating AI primarily as a regulatory science tool to strengthen analytical components of decisions such as patient selection, biomarker substitution, and predictive modeling. The agency emphasizes credibility and validation through a risk-based framework that evaluates AI models according to their influence on regulatory decisions and potential consequences of error. In Europe, the EMA pursues system-level digital transformation, embedding AI within a broader data and analytics strategy emphasizing interoperability, data structuring, automation, and governance supported by legislation. African national regulatory authorities are advancing AI through pragmatic pilot initiatives. The South African Health Products Regulatory Authority (SAHPRA) is implementing AI within a structured digitization strategy, including AI-assisted dossier screening and automated GMP review to address backlogs and workflow inefficiencies. The Medicines Control Authority of Zimbabwe (MCAZ) deploys AI-driven dossier screening through its in-house digital systems, while Kenya's Pharmacy and Poisons Board has proposed a risk-based framework for regulating AI-enabled medical devices. At the continental level, the African Medicines Agency and AUDA-NEPAD aim to harmonize digital transformation and responsible AI adoption through reliance and cross-border data sharing. This paper summarizes discussions from a convening to identify priorities for digitization and digital transformation of African medicines regulation.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.