Optimising Operations & Processes in Biotech Labs
Recent developments in computational tools and how these can solve operational challenges in biotech labs.
Interview published by Lab Manager: – Biotechnology labs face many challenges, such as operations and process issues, taking risks when pursuing innovative ideas, constantly changing and advancing technologies, and data and security challenges. However, both labs and companies involved in the biotech field seem up to these challenges and are equipped to carry out a variety of solutions.
Recent developments in computational tools and how these can solve operational challenges in biotech labs.
Q: What are some of the key challenges when it comes to the operations/process side of the biotech lab?
A: The ability to generate new data and efficiently process, interpret, and share large volumes of complex information across an organization is a key enabler for drug discovery and biotech in general. Research has shifted from being process-driven to data-driven. Biotech companies that are maximizing the knowledge gained from each discovery cycle and effectively informing decision-making for the next cycle have the highest chance of project success. Computational tools, particularly AI [artificial intelligence], increasingly support these insights and impact decision-making. However, challenges relating to the nature of the data being gathered in drug discovery remain, thus limiting the potential of many computational approaches, including AI methods…