Evolution of artificial intelligence in biotechnology: From discovery to ethical and beyond

The convergence of artificial intelligence (AI) and biotechnology catalyses a transformative shift in scientific discovery and healthcare. This review article explores the multifaceted impact of AI on various domains within biotechnology, highlighting its potential to reshape drug discovery, biomedical imaging, predictive analytics, and healthcare delivery. In AI-driven drug discovery, machine learning and deep learning algorithms expedite compound screening, molecular modelling, and compound design. AI-powered biomedical imaging enhances disease detection and interpretation accuracy across modalities such as X-rays, MRIs, and histopathology slides. Predictive analytics fueled by AI usher in proactive healthcare by analysing diverse patient data to predict diseases and tailor interventions. While this technological fusion holds immense promise, ethical, regulatory, and societal considerations loom large. Challenges of data privacy, algorithmic bias, transparency, and patient consent must be addressed. Regulatory frameworks need to evolve to ensure AI’s responsible and safe deployment. Moreover, societal implications encompass equitable access and potential workforce displacement. Collaboration among diverse stakeholders is essential to navigate these challenges and shape an ethical, equitable, and innovative AI-infused future in biotechnology.