Create a new data standard to increase the business value of your digital lab

By improving data management practices in the lab, pharma organizations will see improvements in process waste elimination, workflows of arbitrary complexity and regulatory validation.  

With the industry seeing more than US$2.4 trillion being invested into pharma research and development globally due to an increase in the number of experiments coming into the lab, ensuring data is well-managed and accessible for scientists is vital for preventing errors, increasing the quality of large-scale analyses, replicating findings more efficiently and accelerating time-to-market.

In this online mini-series event, Merck and other big pharma names, will be exploring how to apply the Analytical Information Markup Language (AnIML) data standard, so scientists can bring together data from many different instruments and measurement techniques in a single place.

Join us live and discover how to:

• Implement a new universal data standard to support experiment automation, data interchange, and long-term storage. 
• Advance the digital economy of the pharma lab by using artificial intelligence (AI) to transform chemical synthesis. 
• Facilitate regulatory compliance best practices using AnIML. 
• Scale up increasingly complex experiments and allow for accessible, real-time monitoring of centralized and synched lab data. 
• Overcome challenges in the lab such as manual data transcription and review by exploring real-world use cases of AnIML. 

Agenda
Wednesday 13th October

2pm BST | Building on the AnIML standard to support experiment automation
Considering the benefits automation brings to lab environments such as increased productivity, improved product quality and inventory management, it is unsurprising it has become a key component to connect labs. In this session, Merck will dive into case study examples of how to achieve a high level of experiment automation, data interchange and long-term storage, regardless of what instruments or measurement techniques are used in the lab, using AnIML concepts and applications.

Developing drug molecules is a slow, costly and iterative process that involves sifting through thousands of candidates to find the most suitable. Unfortunately, most compounds never make it to market. On average, the cost of taking a new medicine to market is US$2.6bn, while it can take up to 12 years from concept to delivery. In this session, Merck alongside a special guest from a big pharma company will be answering your questions live on how to accelerate drug discovery in the lab with an AI-based solution.

Instrument software today offers many features for analysis and post-processing of result data. However, every software manufacturer implements algorithms slightly differently. This makes it hard to compare results from different instruments. In this interactive workshop with experts from Merck and big pharma companies, discover how to improve consistency and solve challenges around workflow standardization using AnIML.