A New Turning Point in Biotechnology: The State of AI-Based Drug Development and Personalized Medicine in 2026
Editor
As of early 2026, the global biotechnology industry is undergoing fundamental changes due to the integration of artificial intelligence and gene editing technologies. According to the latest report from market research firm McKinsey, the global biotech market is projected to grow by 22%, from $980 billion in 2025 to $1.2 trillion in 2026, driven by rapid advancements in AI-based drug development and personalized medicine. Notably, the traditional drug development process is being shortened from an average of 15 years to 8-10 years. This transformation is fundamentally improving the pharmaceutical industry’s ROI (Return on Investment), attracting significant interest from venture capital and institutional investors.
The most notable trend in the biotech field is the commercialization of AI-driven drug discovery platforms. Following the release of AlphaFold 3.0 by the UK’s DeepMind at the end of 2025, the accuracy of protein structure prediction has exceeded 95%, significantly improving the initial stages of drug development. Consequently, the US FDA announced new guidelines for AI-based drug development in December 2025, which have been in full effect since 2026. Industry experts predict that these regulatory improvements will trigger an IPO rush among AI biotech startups.
Korea’s biotech ecosystem is also rapidly evolving in line with these global trends. Samsung Biologics, headquartered in Seongnam, Gyeonggi Province, reported a 28% year-on-year increase in revenue, reaching 2.18 trillion won in Q4 2025. This growth is primarily due to increased contract manufacturing orders for biopharmaceuticals from global pharmaceutical companies. Notably, Samsung Biologics improved production efficiency by 15% by implementing an AI-based process optimization system in the second half of 2025. Similarly, Celltrion, based in Incheon, achieved annual revenue of 3.2 trillion won in 2025, further solidifying its global presence in the biosimilar sector.
The Convergence of AI and Biotechnology: The Emergence of a New Paradigm
In 2026, the most innovative example of AI-based biotechnology is emerging in the field of personalized gene therapy. Gilead Sciences, headquartered in California, received FDA approval for its personalized CAR-T cell therapy using AI algorithms at the end of 2025, improving treatment success rates from 78% to 89% compared to existing therapies. This achievement is thanks to an AI system that analyzes individual genomic data in real-time to generate optimal treatment protocols. Market analysts predict that this technology will create a personalized treatment market worth $45 billion annually.
Roche, headquartered in Basel, Switzerland, announced that its proprietary AI platform ‘NaviFy’ reduced the time to discover new drug candidates from an average of 3.2 years to 1.8 years in 2025. This platform uses machine learning algorithms to predict drug-target interactions at the molecular level, with 12 new drug candidates entering phase 1 clinical trials to date. Roche CEO Thomas Schinecker stated, “AI-based drug development will account for more than 60% of the company’s pipeline over the next five years.” This technological advancement is also why Roche’s R&D investment in 2025 increased by 18% year-on-year to 13.4 billion Swiss francs.
US pharmaceutical giant Johnson & Johnson has been actively pursuing a drug development project combining quantum computing and AI through its subsidiary Janssen since the second half of 2025. This project uses IBM’s quantum computer to perform complex molecular structure simulations, achieving a calculation speed 1,000 times faster than conventional supercomputers. Paul Stofford, Johnson & Johnson’s Senior Vice President of R&D, predicted, “Quantum-AI convergence technology will be a breakthrough in developing treatments for intractable diseases like Alzheimer’s.” Currently, three new drug candidates using this technology are in the preclinical stage, aiming for clinical entry by 2027.
Meanwhile, in the field of gene editing technology, next-generation technologies beyond CRISPR-Cas9 are entering the commercialization stage. Editas Medicine, headquartered in Massachusetts, announced that 87% of patients showed vision improvement in a phase 2 clinical trial of ‘EDIT-101’, a hereditary blindness treatment using Prime Editing technology in 2025. This result significantly mitigates the side effect issues of existing CRISPR technology, and the FDA is reviewing conditional approval in the first half of 2026. Market research firm Grand View Research predicts that the next-generation gene editing market will grow from $8.9 billion in 2026 to $28.5 billion by 2030.
Changes in Global Competition and Market Dynamics
In 2026, the competitive landscape of the biotech industry is characterized by a complex interplay of collaboration and competition between traditional big pharma and AI technology companies. Novartis, headquartered in Basel, Switzerland, entered into a $5 billion strategic partnership with Microsoft in 2025 to build a cloud-based AI drug development platform. This platform is currently connected to 120 research institutions in 15 countries worldwide, forming a global network for real-time clinical data sharing and analysis. Novartis reported Q4 2025 revenue of $12.7 billion, a 12% year-on-year increase, with the AI-based drug development segment accounting for $2.3 billion.
AbbVie, headquartered in Chicago, Illinois, achieved groundbreaking results in the immuno-oncology field through its proprietary AI platform in 2025. The next-generation version of its flagship product, Imbruvica, features a function that adjusts the optimal dosage for each patient in real-time using AI algorithms, reducing side effects by 40% while improving treatment efficacy by 15% in phase 3 clinical trials. AbbVie’s annual revenue in 2025 was $58.7 billion, an 8.3% increase from the previous year, with the personalized treatment segment growing by 24%.
In the Asian market, Chinese and Korean companies are experiencing rapid growth in the biotech sector. BioGenex, headquartered in Shanghai, China, simultaneously entered clinical trials with four new drug candidates using its AI-based antibody drug development platform in 2025, the largest scale among Chinese biotech companies. In Korea, SK Bioscience developed a next-generation vaccine platform combining mRNA vaccine technology and AI in 2025, being selected as a pandemic response vaccine development partner by the WHO. This platform can design vaccines for new variant viruses within 72 hours, attracting significant attention from a global health security perspective.
Examining venture capital investment trends, the global biotech sector’s investment scale in 2025 increased by 34% year-on-year to $89.2 billion. Among this, investment in AI-based biotech startups accounted for $26.7 billion, or 30% of the total, a significant increase from 18% in 2024. Notably, the average investment size in Series A stages increased by 50%, from $28 million to $42 million, due to the increased initial capital requirements for AI technology development. The main investment areas were personalized treatment development (32%), AI-driven drug discovery (28%), gene editing technology (23%), and digital healthcare (17%).
In terms of regulatory environment, major governments are actively establishing regulatory frameworks for AI biotechnology as of 2026. The European Union passed the ‘AI in Healthcare Act’ in December 2025, establishing an integrated regulatory system for AI-based medical devices and drugs. This legislation strengthens the transparency and explainability of AI algorithms while simplifying approval processes to promote innovation through a balanced approach. The US FDA also expanded the ‘Digital Health Software Precertification Program’ in January 2026, providing expedited approval pathways for AI-based biotech products. Korea’s Ministry of Food and Drug Safety has been implementing ‘AI Medical Device Approval and Review Guidelines’ since the second half of 2025 to support the global competitiveness of domestic biotech companies.
The main challenges facing the biotech industry today include data quality and security issues, high technology development costs, and regulatory uncertainty. Particularly, securing high-quality biological data necessary for AI model training is challenging, leading many companies to invest significant resources in building data partnerships. According to McKinsey’s analysis, successful AI biotech companies allocate an average of 35% of their total R&D budget to data infrastructure, a stark contrast to the 12% of traditional biotech companies. Additionally, the regulatory approval delays caused by the black-box nature of AI models remain a challenge to be addressed.
Nevertheless, the industry outlook is highly positive. Market research firm Frost & Sullivan predicts that the AI-based biotech market will grow from $34 billion in 2026 to $125 billion by 2030, with an average annual growth rate of 38%. This growth is primarily attributed to the popularization of personalized medicine, increased success stories of AI-based drug development, and the expansion of the digital healthcare ecosystem. Notably, the first blockbuster drugs developed with AI are expected to hit the market from 2027, further increasing investor interest. A recent report from Goldman Sachs forecasts that “2026 will be the inaugural year of commercial success for AI biotechnology,” predicting an average 45% increase in the stock prices of related listed companies over the next two years.
This analysis is intended for general informational purposes and does not constitute investment advice or recommendations. Investment decisions should be made at your own discretion and responsibility, and it is advisable to consult with a professional before making any decisions.
