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<p>Medical biotechnology serves as a foundational platform for identifying disease markers and developing specific diagnostic assays. Complementing this, biosensors and medical devices translate these biomarkers into quantifiable signals enabling real-time health assessment. Artificial intelligence (AI) augments this framework by processing vast datasets to recognize patterns and generate predictive insights thereby aiding clinicians in decision-making and streamlining personalized disease management. The integration of molecular-based companion diagnostics, biosensor technology, and medical AI forms the cornerstone of contemporary, data-driven precision medicine. This review explores the synergistic convergence of these fields specifically examining how AI-based approaches enhance molecular diagnostics and biosensor devices to optimize clinical outcomes. This interdisciplinary collaboration facilitates advancing precision medicine. Consequently, these discovery technologies profoundly impact disease prevention, early diagnosis, and targeted therapeutic strategies. Despite challenges such as data privacy and technology accessibility, this cross-disciplinary approach holds tremendous potential for transforming the future of precision healthcare.</p>

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Medical biotechnology and artificial intelligence powered companion diagnostics: indispensable pillars driving next generation precision health care

  • 期刊论文

  • 发表日期：

    2026年4月10日

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  • Priyanka Sonar,
  • K. R. Mathuvanti,
  • Amoha Venkataramanan,
  • Harish Reddy,
  • Abhishek Mohanty

摘要

Medical biotechnology serves as a foundational platform for identifying disease markers and developing specific diagnostic assays. Complementing this, biosensors and medical devices translate these biomarkers into quantifiable signals enabling real-time health assessment. Artificial intelligence (AI) augments this framework by processing vast datasets to recognize patterns and generate predictive insights thereby aiding clinicians in decision-making and streamlining personalized disease management. The integration of molecular-based companion diagnostics, biosensor technology, and medical AI forms the cornerstone of contemporary, data-driven precision medicine. This review explores the synergistic convergence of these fields specifically examining how AI-based approaches enhance molecular diagnostics and biosensor devices to optimize clinical outcomes. This interdisciplinary collaboration facilitates advancing precision medicine. Consequently, these discovery technologies profoundly impact disease prevention, early diagnosis, and targeted therapeutic strategies. Despite challenges such as data privacy and technology accessibility, this cross-disciplinary approach holds tremendous potential for transforming the future of precision healthcare.