Study by Nigerian Researcher Innocent Opara Examines AI and Cloud Cybersecurity in Rare Genetic Disease Treatment

By Tosin Clegg

Recent research by Nigerian researcher Innocent Opara is examining how artificial intelligence can be integrated with cloud cybersecurity frameworks to support therapeutic development for rare genetic diseases while protecting sensitive genomic data.

The study, Integrating AI-Based Therapeutic Design and Cloud Cybersecurity for Rare Genetic Diseases: A Systematic Review, analyzes how AI-driven therapeutic design can be deployed alongside secure cloud infrastructures in precision medicine. The review addresses growing concerns related to data privacy, ethical governance, and cybersecurity risks in genomic research.

Opara’s analysis reviewed 208 peer-reviewed studies published between 2015 and 2025, selected from an initial pool of more than 1,000 articles indexed in PubMed, Scopus, IEEE Xplore, SpringerLink, and Web of Science. Using the PRISMA framework, the research evaluated how AI and cloud technologies are shaping diagnostic and therapeutic discovery while introducing new technical and security challenges.

The findings indicate that deep learning techniques are increasingly applied to phenotype-genotype mapping, while generative adversarial networks support therapeutic molecule design. Natural language processing has expanded the ability to analyze biomedical literature at scale, and federated learning is emerging as a method for enabling decentralized, privacy-preserving research collaborations.

The study also notes that AI-based diagnostic tools, including facial phenotype analysis systems, have demonstrated improved accuracy in identifying certain genetic syndromes compared to traditional clinical evaluations. However, Opara highlights vulnerabilities such as adversarial attacks, model inversion, and data poisoning, which pose risks to both model reliability and patient data security.

“Artificial intelligence holds significant potential for advancing rare disease research,” Opara noted, “but its effectiveness depends on the strength of the cybersecurity frameworks that protect sensitive genomic information.”

Ethical and regulatory challenges were also identified across the literature, including informed consent, algorithmic bias, data ownership, and compliance with international data-protection standards such as the GDPR. Opara’s review emphasizes that ethical governance must evolve alongside technological innovation to ensure transparency and equity in AI-driven healthcare.

To mitigate these risks, the study discusses technical safeguards such as differential privacy, homomorphic encryption, federated learning, and adversarial training as viable approaches for strengthening cloud-based genomic systems.

The findings reflect a broader shift toward interdisciplinary collaboration in biomedical research, where advances in artificial intelligence increasingly rely on secure digital infrastructure. As global investment in AI-driven genomics continues to grow, Opara’s research contributes to ongoing discussions on how cybersecurity and ethical oversight can support responsible innovation in precision medicine.