Innovation
Strategic innovation continues to drive progress and advancement across the healthcare industry. Specifically, innovation in pharmaceutical manufacturing directly impacts the market by providing critical tools to support the future success of novel drug candidates. By boosting efficiency and effectiveness in healthcare manufacturing, innovation enables developers to focus on the rapid development of novel and complex modalities that target unmet medical needs.
As a preferred CDMO, we leverage our substantial expertise and experience to drive innovation across multiple modalities and throughout the drug development process from discovery to development, manufacturing, and commercialization.
We believe that investing in research and development (R&D) is essential to meeting our customers’ long-term needs. Our R&D network supports innovation across all our divisions and modalities, leading to strong synergies and inventive projects that have the potential to deliver benefits to the wider industry and – ultimately – to the lives of our customers’ patients. Our key cross-divisional innovation areas are summarized below.
Integrating artificial intelligence, machine learning and robotics into the drug development and manufacturing journey
In recent years, digitalization and industry 4.0 has become the cornerstone of innovation. This global trend has wide-reaching implications for many industries including medicine, life sciences and healthcare manufacturing.
At Lonza, we are integrating various digital technologies into the drug development and manufacturing journey. “Bioprocessing 4.0” is about digitally connected process that supports improved speed, flexibility and efficiency, while managing cost. Such connected and integrated technologies can unlock greater depth of process knowledge, supported by advanced data management capabilities, which can be used to optimize and control processes.
We are already implementing machine learning algorithms (ML) and artificial intelligence (AI) into our processes to navigate the complexity and speed requirements of manufacturing novel treatments. Examples of how AI has been implemented include using computer vision technologies in quality assurance for product quality optimization, and developing hybrid approaches for process scale-ups that combine AI, mechanistic models and statistics.
AI, ML and big data management are used in our R&D teams to support computer-aided drug design, protein profile assessment, engineering mammalian expression systems with DNA element design, and for predicting side effects for novel therapies. In small molecule development and manufacturing, ML algorithms and automated solutions are implemented in retrosynthesis and synthetic route optimization, toxicological assessment of new chemical entities, and formulation design.
In addition, our Drug Products Services team has developed an AI image analysis tool that aids in the fast detection and classification of particles. There is a primary focus on detecting polysorbate degradation products, which are crucial for maintaining the stability of proteins to extend their shelf-life. This detection technology aims to deliver therapeutics of the highest quality by optimizing sub-visible particle imaging for formulation development.
Another application of digitalization lies in workflow automation. Digitally sustainable operations for managing laboratory work and documentation can facilitate a smooth transition from manual, paper-based documentation processes to a fully electronic system that meets regulatory requirements. Lonza’s MODA® Platform represents a comprehensive laboratory data and manufacturing management solution across multiple systems and scales. It has been implemented across selected areas of our manufacturing network to boost process efficiency and quality.