Ecolab Continues Mission to Protect What's Vital With Deep Investment in Life Sciences

Artificial intelligence (AI) can improve risk assessment and decision-making in drug development by applying objective, data-driven criteria consistently. Companies should focus on the quality of data, selecting the right AI use cases, and leveraging external partners to maximize the potential of AI.

Explore the latest pharmaceutical validation developments with industry experts from Barry-Wehmiller Design Group, Kneat Solutions, and No Deviation. You’ll gain valuable data-driven insights and discover emerging trends from the State of Validation 2024 industry report that are shaping the validation landscape.

In the pharmaceutical industry, patient engagement should be centered in health education, communication, and strategy during drug discovery and throughout the product lifecycle. Cheryl Lubbert, CEO of Reverba, discusses the importance of a patient-first mindset in the industry.

Traci Miller (Director, Sonexus™ Access and Patient Support, Cardinal Health) discusses current digital trends in the patient services industry, as well as how the optimal balance of technology and talent can transform manufacturer-sponsored patient support programs. Cardinal Health combines best-in-class program and pharmacy operations with smart digital tools to ensure product and patient success and reduce operational costs.

As today’s labs continue to evolve, the software solutions that support them must too. Likewise, laboratory and organization leadership must be open to the advance¬ments available to them from modern technologies. In this white paper, learn how a SaaS-based LIMS modernization program optimizes data management, fosters collaboration, and improves decision-making to stay at the forefront of scientific innovation.

Innovation is the engine that powers a company’s growth and product development, and for enterprises with R&D laboratories, those lab environments are the greatest source of this innovation. In this white paper, learn how a platform approach to scientific data management, including semantic search, advanced analytics, and lab automation, leads to better enterprise decisions at the executive level, optimized lab performance, more discoveries, and stronger product pipelines.