Intelligent Transformation in Life Sciences: Driving a New Paradigm in Drug R&D

In recent years, digital innovative technologies such as cloud computing have flourished, and generative artificial intelligence (including ChatGPT) has ignited global imagination regarding AI. Against the backdrop of a new era in which China prioritizes high-quality development, the digital economy has become a powerful engine driving the country’s economic growth. In February 2023, the Central Committee of the Communist Party of China and the State Council issued the Overall Layout Plan for Building a Digital China, hailed by industry observers as ushering in “the era of digital leadership.” Focusing on the field of new drug research and development, the Chinese government is actively promoting the advanced application of artificial intelligence. In July 2022, six departments, including the Ministry of Science and Technology, released the Guiding Opinions on Accelerating Scenario Innovation to Promote High-Quality Economic Development through Advanced Applications of Artificial Intelligence. The document proposes fully leveraging AI technologies in literature and data acquisition, experimental prediction, and result analysis, with a focus on creating AI application scenarios in key areas such as novel drug creation.

Driven by supportive policies, an increasing number of life sciences companies are focusing on artificial intelligence and digital innovation. The rise of AI and digital technologies has also provided a historic opportunity for the “intelligent transformation” of the life sciences industry.

In 2020, Dassault Systèmes introduced the concept of the “Virtual Twin.” It is not merely a digital representation of real-world entities but also encompasses the evolutionary history of digital objects through design, simulation, and validation. Today, the concept of the “Virtual Twin” has been widely adopted in the life sciences industry, covering the entire new drug development process—from R&D activities such as molecular synthesis, to Chemistry, Manufacturing, and Controls (CMC), clinical trials, and ultimately to production and commercialization.

Patient-specific virtual twins have long been in use. As early as 2016, Dassault Systèmes’ Living Heart virtual heart technology was implemented in the Department of Cardiology at Fuwai Hospital, Chinese Academy of Medical Sciences, where it helped physicians conduct preoperative testing and surgical planning for patients with complex cardiac conditions by simulating human heart physiology. Beyond anatomical simulation, patient virtual twins are also employed to address the lack of randomized control groups in clinical trials for rare or severe diseases. Dassault Systèmes’ Medidata AI Synthetic Control Arm solution leverages big data and artificial intelligence to generate synthetic control arms and constructs external control groups using historical clinical trial data from Medidata, thereby helping to overcome challenges such as patient recruitment in clinical trials. As early as 2021, the U.S. Food and Drug Administration (FDA) approved the use of this solution in a Phase III registrational trial for recurrent glioblastoma (rGBM).

Virtual twins have long been applied in the early stages of drug discovery. During this phase, researchers need to screen tens of thousands of molecules to identify the most promising drug candidates. Leveraging drug molecule databases and specific pharmacological requirements, big data technologies facilitate the construction of ideal molecular architectures and help researchers understand molecular stability, particularly in response to viral challenges. In 2021, researchers from Dassault Systèmes BIOVIA and its academic partner, the University of Paris, utilized Dassault Systèmes’ BIOVIA Discovery Studio to gain deeper insights into spike protein structural data, aiming to improve vaccine design and predict the impact of different variants. The team extracted antibodies from COVID-19 patients undergoing treatment, sequenced these antibodies, and used BIOVIA Discovery Studio to build three-dimensional models of the antibodies. This enabled them to investigate whether the antibodies would bind to and neutralize the spike protein. By modeling the three-dimensional structures of proteins, BIOVIA Discovery Studio brings protein structures to life.

Furthermore, virtual twins of factory production have been developed for various aspects of the manufacturing process, including pharmaceutical processes, assembly lines, logistics, and quality management. In 2020, Dassault Systèmes’ SIMULIA brand leveraged computational fluid dynamics (CFD) and HVAC simulation technologies to assist in designing the HVAC system for Wuhan Leishenshan Hospital’s isolation wards. This effort was featured on CCTV’s Xinwen Lianbo (News Broadcast) program and contributed to preventing viral transmission between patient rooms as well as to surrounding communities.

“Digital twins” closely align with the national agenda for industrial digitalization. In the life sciences sector, digital twins have emerged as one of the “key tools” for overcoming bottlenecks in novel drug development.

Laboratories are a critical hub for drug R&D in the life sciences sector. Unifying and digitizing laboratory workflows minimizes workload, enabling drug R&D professionals to devote more time to interpreting key insights from digital tools and making informed decisions.

Laboratory daily workflows encompass management and planning processes at all levels. However, research data indicate that researchers spend only 23% of their time on actual experimental procedures, with the remainder devoted to meetings, data analysis, experiment documentation, report writing, and experimental planning. Furthermore, in traditional laboratory operations, fragmented data and paper-based processes are prone to errors, leading to reduced research efficiency and compliance risks. In multi-stakeholder settings, these issues often result in disconnected workflows, posing risks to data accuracy.

The BIOVIA ONE Lab solution is built on a unified, integrated platform that supports the integration of multiple solutions—including ELN, LIMS, LES, inventory management, and instrument management—to maximize process optimization. By managing multiple processes and checkpoints through a single platform, it not only enhances data analysis but also better centralizes laboratory information, facilitating seamless interaction among data sets. By breaking down data silos via this comprehensive platform, researchers can establish information flows across multiple levels, enabling more convenient tracking through task assignment and execution, thereby reducing redundant work and minimizing communication errors.

Laboratories generate vast amounts of data on a daily basis. An increasing number of pharmaceutical companies are demanding further analysis and mining of this data. Leveraging the existing data mining and analytical tools within BIOVIA ONE Lab, data from different business units can be integrated. Through modeling, artificial intelligence, and other methods, researchers can gain deeper insights to facilitate clear and informed decision-making.

The BIOVIA ONE Lab solution is a unified, integrated platform. If viewed as a mobile operating system, the various solutions correspond to functional modules within it. It features separate modules covering everything from materials and equipment to instruments and final data processing, which can be selected based on specific needs. For instance, for an R&D laboratory, one only needs to deploy BIOVIA Workbook and the registration system on the platform. If analytical applications are involved, systems for editing and executing analytical methods will be required.

Statistical data shows that BIOVIA customers have achieved efficiency gains of up to 35% by streamlining workflows. In other words, the BIOVIA ONE Lab solution significantly enhances the efficiency, accuracy, and reliability of laboratory data and processes in product R&D, serving as a powerful enabler for life sciences organizations to accelerate the market launch of new therapies.

As competition in the life sciences industry intensifies, pharmaceutical companies both domestically and internationally are either enriching their drug pipelines or shifting their focus to address gaps in precision medicine, aiming to find breakthroughs and stand out from the fierce competition. Confronted with the “three major challenges” of high risk, high investment, and long development cycles, the ability to accelerate R&D efficiency and data insights during the highly competitive new drug development process—while keeping pace with evolving regulatory requirements—will become a core competitive advantage for pharmaceutical companies, CROs, and CDMOs. In this context, artificial intelligence and digital tools will play a significant supportive role.

From drug discovery to the transformation of development, manufacturing, and quality control, Dassault Systèmes BIOVIA is committed to providing digital and intelligent innovative solutions that cover the entire drug lifecycle. Together with brands such as Medidata, it delivers comprehensive digital solutions for the life sciences industry, empowering breakthrough innovations in its digital and intelligent transformation and facilitating “digital-intelligent upgrading.”