Going green is the new black. Everyone is getting involved, from the world’s Governments pledging to cut carbon emissions to supermarkets doing away with plastic bags. Being more environmentally friendly is high on the agenda and it’s no different in the research and development (R&D) sector.
‘Green R&D’ or ‘green science’ makes sense. It saves companies significant cash in the long run but it does take investment upfront. A real drive to change the way scientists think and work is essential. Companies are under pressure from regulatory bodies to reduce industrial waste and pollution. Replacing the ‘nasties’ which are highly polluting and hard, or costly, to dispose of is a must. So how easy is it for scientists or engineers to change their day-to-day work and substitute less harmful reagents for those ‘nasties’?
It could be a synthetic chemist looking to remove harsh solvents; or a biologist looking for a different way to label something other than a radioactive isotope; or a materials scientist might be looking to use a less toxic heavy metal in a catalyst or alloy. A product developer may try to produce something new that uses less bleaching agents or synthetic ingredients. There are ways to support these needs and it involves building knowledge-bases that are science optimized. They must contain information and structured data that allows the information to be leveraged in decision-making and exploration.
Process and ingredient optimization is an essential strategy in any new product environment. As part of this, scientists and engineers must have access to a full knowledge-base to review historical data, in context, with provenance. They can then trace through previous experiments and work to increase their knowledge far more rapidly, and at far lower cost, than if they were to do the normal thing of repeating some or all the experiments/tests again. A domain-centric market vertical optimized knowledge-base, which is consumable and enables data reporting, aggregation and comparison, enables scientists and engineers to really leverage the historical experimental information to help reduce, or hopefully eliminate, an offending substance. It will also help to reduce the amount of experiment duplication, view outcomes and support bringing new or amended products to market with reduced environmental impact.
For example, Cosmetics Europe recently recommended discontinuing the use of Methylisothiazolinone (MIT) in skin products and cosmetic wet wipes. How can you quickly take this requirement, find all the current products that use MIT and then rapidly develop new ones without it in? Organizations with an extensive knowledge-base and strong process optimization in place are ahead of the pack. Those with good IP and structured data capture in place, coupled with documenting both failure and success as a culture, are likely to find it easier to tweak reagents or ingredients to achieve success.