Initially grounded in engineering principles and approximations, digital twins today use vast historical datasets and machine learning to replicate and predict system dynamics. This evolution has made them indispensable across industries, especially in pharmaceutical manufacturing. Building a digital twin requires robust data infrastructure, including high-quality datasets, fast data access, and advanced computational capabilities.
The global digital twin market is on the rise, projected to grow at a compound annual growth rate (CAGR) exceeding 40 per cent through 2028, according to Stratview Research. This growth reflects its adoption in sectors seeking to enhance efficiency and reduce costs. In pharmaceuticals, digital twins offer a solution to pressing challenges, such as the need for faster drug development cycles — a demand highlighted during the COVID-19 pandemic.
The technology’s potential for cost reduction and operational optimization is substantial. According to McKinsey, digitally enabled labs can cut chemical quality control costs by 25-45 per cent and microbiology lab costs by 15-35 per cent, while eliminating up to 80 per cent of manual documentation tasks. Such efficiency gains highlight the technology’s transformative potential for pharmaceutical quality control and production.
Digital twins are being integrated into various stages of pharmaceutical production, yielding impressive results. In drug manufacturing, by simulating production processes, digital twins optimize operations, predict maintenance needs, and enhance productivity. GlaxoSmithKline (GSK) has used digital twin technology to refine its vaccine adjuvant production. This involved integrating real-time data and simulation in a closed loop and optimizing vaccine manufacturing, ultimately achieving significant process improvements.
AI-driven digital twins also have the potential to redefine clinical trials by simulating placebo-control groups, reducing reliance on human participants, and accelerating timelines. Merck’s collaboration with Unlearn.AI demonstrates this, using digital twins to streamline immunology trials while maintaining robust regulatory compliance.
By incorporating genetic and lifestyle data, digital twins can also support the development of personalized medicine and enable tailored treatments for individual patients designed around their individual clinical needs, enhancing therapeutic precision and improving outcomes. They can also help to improve the overall quality of patient care. Organ-specific digital twins, such as 3D heart models, are advancing research into disease progression and treatment responses, facilitating innovations in diagnostics and therapeutics and allowing clinicians to study disease progression and treatment efficacy more accurately.
Digital twin technology in pharmaceutical manufacturing offers many benefits. Real-time monitoring enables proactive interventions, reducing downtime and avoiding costly delays by anticipating any potential failures. By minimizing waste and supporting sustainability efforts, digital twins also drive greater resource efficiency. Virtual testing not only ensures adherence to Food and Drug Administration (FDA) and good manufacturing practice (GMP) standards but also simplifies inspections and enhances traceability across processes. These simulations accelerate testing, adjustments, and implementation, significantly shortening the time-to-market for new products.
Data integration also refines performance, reduces qualification runs, and lowers overall costs, so manufacturers can achieve operational excellence. Advanced control strategies and automation further improve productivity, while real-time insights into any potential production bottlenecks support continuous process improvement. The seamless combination of real-time simulations with data collection creates optimal production strategies, and the incorporation of cloud-based IoT solutions simplifies data management and enhances operational control.
Advanced automation solutions like COPA-DATA’s zenon software platform can help manufacturers to embrace digital twin technology through real-time data integration, process visualization, and advanced analytics. By facilitating predictive maintenance, resource optimization, and regulatory compliance, zenon enhances data-driven decision-making and operational efficiency. The platform’s robust features, such as automated reporting and seamless integration with existing production systems, make it a valuable tool for digitized pharmaceutical operations.
Digital twin technology is revolutionizing pharmaceutical production, offering a pathway to greater efficiency, reduced costs, and faster drug development. Integrating advanced digital solutions into the production lifecycle allows companies to meet the growing demands of the healthcare sector while ensuring the highest standards of quality and compliance. The ability to simulate, predict, and optimize processes in real time not only accelerates innovation but also paves the way for groundbreaking advancements in personalized medicine and patient care. By adopting platforms like zenon, pharmaceutical companies can harness the full potential of digital twins, ensuring a future of innovation and excellence in healthcare.