by Markus Gershater, Co-Founder of Synthace
As 2022 has come to a close, we reflect on the progress made in life sciences, but also look forward to the advancements and possibilities to come. There is an opportunity for automation to play a bigger role in overall scientific progress and for artificial intelligence (AI) and machine learning (ML) to support this. But because these technologies rely heavily on the quality and quantity of data available to them, and because the work that goes on in labs is hard to digitize and represent in code, this represents a significant challenge. Generally, we can expect to see digitization efforts continue and begin to bear fruit, but we may hopefully also see labs moving toward what we would call a post- “point solution” world. If this works, there is even potential for the barrier between wet and dry labs to finally show signs of change. Below, we’ve detailed further how these trends could impact R&D labs, the scientists that run them, and the experiments of the future.
Read more on Labcompare.