Synergizing Big Data and Biotechnology for Innovation in Healthcare, Pharmaceutical Development, and Fungal Research

The convergence of big data and biotechnology is transforming the landscape of healthcare, pharmaceutical research, and fungal biology. This review explores the emerging synergy across these domains, emphasizing predictive analytics, artificial intelligence (AI), and machine learning (ML) enabling real-time decision-making, accelerating drug discovery, and advancing ecological and mycological research. In healthcare, big data collected from electronic health records (EHRs), wearable devices, and population-level datasets support early disease detection, risk stratification, and personalized treatment plans. In pharmaceuticals, AI models including deep learning and generative framework streamline drug development by facilitating target identification, virtual screening, and predictive ADMET modeling. These innovations have significantly reduced development timelines and improved precision in therapeutic design. Parallel advancements in fungal biotechnology, driven by image-based classification and genomic analysis, are revealing fungi as critical sources of bioactive compounds, enzymes, and ecological indicators. Predictive models are now capable of identifying fungal species, mapping metabolic pathways, and forecasting ecological patterns, thus positioning fungi at the intersection of environmental monitoring and drug discovery. Despite these advances, challenges persist including data interoperability, algorithmic bias, regulatory barriers, and ethical concerns related to privacy, equity, and bioprospecting. This review also discusses the infrastructure needed to support cross-sector innovation, such as cloud computing, graph neural networks, FAIR data standards, and open science platforms. It outlines strategic priorities for building integrated, explainable, and accessible AI systems, particularly in underserved regions. By highlighting case studies, shared challenges, and future directions, the review underscores the importance of interdisciplinary collaboration in leveraging big data–biotech synergy.