Dr Cheryl Lund of Dassault Systèmes Biovia looks at how chemicals companies can accelerate product development
Companies in the speciality chemicals industry are in a constant race to innovate. Not only must they speed new products to market ahead of competitors, they must also keep pace with the latest regulations. They need agility to adapt quickly to shifting materials costs, swings in energy prices and other market factors. Winners in the race to innovate have mastered the ability to capture and retain knowledge so that professionals can make intelligent decisions and collaborate effectively.
In my work consulting with leaders in the chemicals industry, I see many companies that have made steps to modernise their methodologies and have come a long way with personal productivity tools. These companies are beginning to see the advantages of digital information systems, though many are still hindered by a combination of mismatched technology and manual processes that do not integrate with each other or with the overall enterprise workflow.
Scientists at these companies may use applications such as Lotus Notes to document laboratory procedures, various email programmes for collaboration with other team members and Excel spreadsheets to track the results of tests and experiments. These solutions work fine for transitory data. But information collected by these niche applications is not integrated with the enterprise knowledge base, nor is it easily shared among teams.
Data thus becomes isolated, compromising its potential for usefulness. This explains why many of these companies are not yet using simulated experiments or computational models at any stage in their processes. They lag so far behind on simply organising their work that they are unable to focus on improving product innovation.
Officials at these companies seek a way to organise this chaos. They want a way to unify information throughout the development process so they can get to the final product sooner. To stay competitive, chemicals companies need a more holistic and sustainable approach to product development.
Lund – More holistic and sustainable approach needed
Do the right thing
In the race to innovate, having orderly processes is not enough. I recently met with some directors from a science-driven company who were looking for technology that would help their staff do things right. They believed that a laboratory information management system (LIMS) was the best way to achieve that.
They were correct in thinking that is what a LIMS does. It helps laboratory workers to do things correctly in a very particular order. But that is only valuable if scientists can identify the right thing to do at each stage in development. We proposed that the company’s goal should be to do the right thing, rather than merely doing things right.
The foundational element for achieving that goal is the ability to preserve and share knowledge through the entire innovation and development lifecycle - from ideation through downstream processes. Information should not be isolated in detached systems, applications, or paper records.
If senior staff members leave, they should not take knowledge with them and leave behind a hole in the knowledge base. This is a genuine concern as Baby Boomers are expected to retire in droves over the coming years.
A standard LIMS is suitable for helping people in chemicals companies keep track of laboratory activities. But it does not recommend what actions should be performed next. What is needed is a holistic solution that can add intelligence to the process by suggesting what to do next, based on end-to-end enterprise knowledge, including the results of previous and real-time ongoing experiments performed by various teams across the extended enterprise.
To support this collaborative platform, information and context must flow from end to end through various systems, leveraging real-time data and process metadata from laboratory instruments, methods, and supplies. If knowledge is available at every decision point in the chemical development process, scientists can identify the best action to take at each stage so they can do the right thing.
Fuelling an innovation engine
Using enterprise-wide knowledge, speciality chemical companies can implement tools that help scientists know when to perform a virtual experiment or simulation instead of running a physical experiment. Such tools can also help them to analyse data across those perspectives. Chemical companies can learn from best practices in the automotive industry that validate this strategy. With virtual testing, auto manufacturers have substantially reduced the number of expensive physical crash tests required to evaluate new products.
Laboratory operations, scientific documentation and virtual experimentation work in harmony to fast-track product development and provide a competitive advantage in the race to innovate
This approach can help chemical companies to fast-track innovation. Supported by data that has been contextualised by an integrated information system, a single virtual test can bring chemists closer to the answer they seek than numerous costly physical tests. Integrated data in a scientifically aware information system enables chemists to throw a net over a wide range of potential experiments and then get advice from the system as to which avenues of experimentation are likely to be the most productive.
Instead of following a predetermined course from A to Z, they can consider many possible paths and take the one that is likely to accelerate innovation. That often involves failing a chemical product earlier in its development cycle. Because it becomes more expensive to fail in later stages of development, the goal is to identify and eliminate unsuitable candidates sooner.
To do that, companies need to build computational models for virtual experiments that are supported by the entire enterprise knowledge base, not mere fragments of it. Information that is isolated in various departments, applications or systems or in the minds of experts cannot sustain the models necessary for virtual testing.
A computational model cannot be built without physical experimentation. Data from physical experiments feeds the computational model for virtual experiments. And then the model feeds the next round of physical experiments in a dynamic cycle. Only when knowledge is accurately captured, contextualised and interpreted can physical and virtual experimentation feed each other.
This cycle helps build an innovation engine. Data is leveraged from both the physical and virtual sides of the equation to build intelligence into the process. Chemists fuel the innovation engine by feeding it more data from physical experimentation to improve the accuracy and precision of virtual experimentation. The computational model improves every time chemists go through the process. This provides a platform for collaboration among experts in multiple domains to further fuel the engine that helps everyone make smarter decisions.
Enterprise knowledge including data from physical experimentation feeds the computational model for virtual experiments, fuelling the next round of physical experiments in a continually improving cycle
Three key strategies combine to sustain and feed the innovation engine. We can think of these elements as corners of a triangle. One corner is LIMS, another is electronic laboratory notebooks (ELNs) and the third is virtual experimentation. Each of these foundational strategies is useful, but on their own they tend to isolate information. Companies need all three working in harmony to drive sustainable innovation.
LIMS helps manage information in the laboratory to ensure that chemists do things right. That drives efficiency, but on its own it does not drive innovation. ELNs ensure that knowledge does not escape and that context accompanies data wherever it is shared.
Virtual experimentation provides a deeper conceptual understanding in less time than physical prototyping. Innovation accelerates when all three elements work together as part of a holistic system that manages the entire development process from ideation to production.
An opportunity to evolve
New technology approaches to solving challenges in the lab provide the opportunity for companies in the chemicals industry to accelerate product development. Strategies such as LIMS and ELNs that once represented the cutting edge are now foundational elements for a more holistic approach that includes virtual experimentation and computational models.
An integrated and scientifically aware system that enables information and context to flow from end to end can add intelligence to the chemicals development process by suggesting what to do next, based on the results of previous and real-time ongoing activities.
To keep pace and prosper in the race to innovate, chemicals companies must capture and retain information to help them build computational models that are supported by the entire enterprise knowledge base. In this way, physical and virtual experimentation can feed each other to build an innovation engine that supports effective collaboration and intelligent decision-making.
Dr Cheryl Lund
Principal Product Manager
Dassault Systèmes Biovia
Tel: + 1 925 931 3414