Preprint Review Version 1 This version is not peer-reviewed

Holomics and AI-Driven Precision Oncology for Medullary Thyroid Carcinoma: Addressing Challenges of a Rare and Aggressive Disease

Version 1 : Received: 3 September 2024 / Approved: 3 September 2024 / Online: 3 September 2024 (14:38:17 CEST)

How to cite: Luvhengo, T. E.; Moeng, M. S.; Sishuba, N.; Makgoka, M.; Jonas, L.; Mamathuntsha, T. G.; Mbambo, T.; Kagodora, S. B.; Dlamini, Z. Holomics and AI-Driven Precision Oncology for Medullary Thyroid Carcinoma: Addressing Challenges of a Rare and Aggressive Disease. Preprints 2024, 2024090223. https://doi.org/10.20944/preprints202409.0223.v1 Luvhengo, T. E.; Moeng, M. S.; Sishuba, N.; Makgoka, M.; Jonas, L.; Mamathuntsha, T. G.; Mbambo, T.; Kagodora, S. B.; Dlamini, Z. Holomics and AI-Driven Precision Oncology for Medullary Thyroid Carcinoma: Addressing Challenges of a Rare and Aggressive Disease. Preprints 2024, 2024090223. https://doi.org/10.20944/preprints202409.0223.v1

Abstract

Medullary thyroid carcinoma (MTC) is a rare yet aggressive form of thyroid cancer, comprising a disproportionate share of thyroid cancer-related mortalities despite its low prevalence. MTC differs from other differentiated thyroid malignancies due to its heterogeneous nature, presenting complexities in both hereditary and sporadic cases. Traditional management guidelines, designed primarily for papillary thyroid carcinoma (PTC), fall short in providing the individualized care required for MTC patients. In recent years, the sheer volume of data generated from clinical evaluations, radiological imaging, pathological assessments, genetic mutations, and immunological profiles has made it humanly impossible for clinicians to simultaneously analyze and integrate these diverse data streams effectively. This data deluge necessitates the adoption of advanced technologies to assist in decision-making processes. Holomics, an integrated approach that combines various omics technologies, along with artificial intelligence (AI), emerges as a powerful solution to address these challenges. AI-driven precision oncology can significantly enhance the diagnostic work-up, staging, risk stratification, management, and follow-up care of MTC patients by processing vast amounts of complex data quickly and accurately. AI algorithms can identify patterns and correlations that may not be apparent to human clinicians, thereby improving the precision of personalized treatment plans. Moreover, the implementation of AI in MTC management enables the collation and synthesis of clinical experiences from across the globe, facilitating a more comprehensive understanding of the disease and its treatment outcomes. This global approach aligns with the United Nations Sustainable Development Goal 3, which aims to ensure healthy lives and promote well-being for all at all ages. By leveraging AI and holomics, we can strive towards making personalized healthcare accessible to every individual, regardless of their economic status, thereby improving overall survival rates and quality of life for MTC patients worldwide. In conclusion, the integration of holomics and AI in the management of medullary thyroid carcinoma represents a significant advancement in precision oncology. This innovative approach not only addresses the complexities of a rare and aggressive disease but also paves the way for global collaboration and equitable healthcare solutions, ultimately transforming the landscape of MTC treatment and care.

Keywords

Artificial intelligence, holomics, medullary thyroid carcinoma, precision oncology

Subject

Medicine and Pharmacology, Oncology and Oncogenics

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